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Sample records for aqua modis reflectance

  1. On-Orbit Calibration and Performance of Aqua MODIS Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Sun, Junqiang; Xie, Xiaobo; Barnes, William; Salomonson, Vincent

    2009-01-01

    Aqua MODIS has successfully operated on-orbit for more than 6 years since its launch in May 2002, continuously making global observations and improving studies of changes in the Earth's climate and environment. 20 of the 36 MODIS spectral bands, covering wavelengths from 0.41 to 2.2 microns, are the reflective solar bands (RSB). They are calibrated on-orbit using an on-board solar diffuser (SD) and a solar diffuser stability monitor (SDSM). In addition, regularly scheduled lunar observations are made to track the RSB calibration stability. This paper presents Aqua MODIS RSB on-orbit calibration and characterization activities, methodologies, and performance. Included in this study are characterizations of detector signal-to-noise ratio (SNR), short-term stability, and long-term response change. Spectral wavelength dependent degradation of the SD bidirectional reflectance factor (BRF) and scan mirror reflectance, which also varies with angle of incidence (AOI), are examined. On-orbit results show that Aqua MODIS onboard calibrators have performed well, enabling accurate calibration coefficients to be derived and updated for the Level 1B (L1B) production and assuring high quality science data products to be continuously generated and distributed. Since launch, the short-term response, on a scan-by-scan basis, has remained extremely stable for most RSB detectors. With the exception of band 6, there have been no new RSB noisy or inoperable detectors. Like its predecessor, Terra MODIS, launched in December 1999, the Aqua MODIS visible (VIS) spectral bands have experienced relatively large changes, with an annual response decrease (mirror side 1) of 3.6% for band 8 at 0.412 microns, 2.3% for band 9 at 0.443 microns, 1.6% for band 3 at 0.469 microns, and 1.2% for band 10 at 0.488 microns. For other RSB bands with wavelengths greater than 0.5 microns, the annual response changes are typically less than 0.5%. In general, Aqua MODIS optics degradation is smaller than Terra

  2. Global space-based inter-calibration system reflective solar calibration reference: from Aqua MODIS to S-NPP VIIRS

    NASA Astrophysics Data System (ADS)

    Xiong, Xiaoxiong; Angal, Amit; Butler, James; Cao, Changyong; Doelling, David; Wu, Aisheng; Wu, Xiangqian

    2016-05-01

    The MODIS has successfully operated on-board the NASA's EOS Terra and Aqua spacecraft for more than 16 and 14 years, respectively. MODIS instrument was designed with stringent calibration requirements and comprehensive on-board calibration capability. In the reflective solar spectral region, Aqua MODIS has performed better than Terra MODIS and, therefore, has been chosen by the Global Space-based Inter- Calibration System (GSICS) operational community as the calibration reference sensor in cross-sensor calibration and calibration inter-comparisons. For the same reason, it has also been used by a number of earth-observing sensors as their calibration reference. Considering that Aqua MODIS has already operated for nearly 14 years, it is essential to transfer its calibration to a follow-on reference sensor with a similar calibration capability and stable performance. The VIIRS is a follow-on instrument to MODIS and has many similar design features as MODIS, including their on-board calibrators (OBC). As a result, VIIRS is an ideal candidate to replace MODIS to serve as the future GSICS reference sensor. Since launch, the S-NPP VIIRS has already operated for more than 4 years and its overall performance has been extensively characterized and demonstrated to meet its overall design requirements. This paper provides an overview of Aqua MODIS and S-NPP VIIRS reflective solar bands (RSB) calibration methodologies and strategies, traceability, and their on-orbit performance. It describes and illustrates different methods and approaches that can be used to facilitate the calibration reference transfer, including the use of desert and Antarctic sites, deep convective clouds (DCC), and the lunar observations.

  3. On-orbit performance and calibration improvements for the reflective solar bands of Terra and Aqua MODIS

    NASA Astrophysics Data System (ADS)

    Angal, Amit; Xiong, Xiaoxiong (Jack); Wu, Aisheng; Chen, Hongda; Geng, Xu; Link, Daniel; Li, Yonghong; Wald, Andrew; Brinkmann, Jake

    2016-05-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) is the keystone instrument for NASA's EOS Terra and Aqua missions, designed to extend and improve heritage sensor measurements and data records of the land, oceans and atmosphere. The reflective solar bands (RSB) of MODIS covering wavelengths from 0.41 μm to 2.2 μm, are calibrated on-orbit using a solar diffuser (SD), with its on-orbit bi-directional reflectance factor (BRF) changes tracked using a solar diffuser stability monitor (SDSM). MODIS is a scanning radiometer using a two-sided paddle-wheel mirror to collect earth view (EV) data over a range of +/-55° off instrument nadir. In addition to the solar calibration provided by the SD and SDSM system, lunar observations at nearly constant phase angles are regularly scheduled to monitor the RSB calibration stability. For both Terra and Aqua MODIS, the SD and lunar observations are used together to track the on-orbit changes of RSB response versus scan angle (RVS) as the SD and SV port are viewed at different angles of incidence (AOI) on the scan mirror. The MODIS Level 1B (L1B) Collection 6 (C6) algorithm incorporated several enhancements over its predecessor Collection 5 (C5) algorithm. A notable improvement was the use of the earth-view (EV) response trends from pseudo-invariant desert targets to characterize the on-orbit RVS for select RSB (Terra bands 1-4, 8, 9 and Aqua bands 8, 9) and the time, AOI, and wavelength-dependent uncertainty. The MODIS Characterization Support Team (MCST) has been maintaining and enhancing the C6 algorithm since its first update in November, 2011 for Aqua MODIS, and February, 2012 for Terra MODIS. Several calibration improvements have been incorporated that include extending the EV-based RVS approach to other RSB, additional correction for SD degradation at SWIR wavelengths, and alternative approaches for on-orbit RVS characterization. In addition to the on-orbit performance of the MODIS RSB, this paper also discusses in

  4. Summary of Terra and Aqua MODIS Long-Term Performance

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong (Jack); Wenny, Brian N.; Angal, Amit; Barnes, William; Salomonson, Vincent

    2011-01-01

    Since launch in December 1999, the MODIS ProtoFlight Model (PFM) onboard the Terra spacecraft has successfully operated for more than 11 years. Its Flight Model (FM) onboard the Aqua spacecraft, launched in May 2002, has also successfully operated for over 9 years. MODIS observations are made in 36 spectral bands at three nadir spatial resolutions and are calibrated and characterized regularly by a set of on-board calibrators (OBC). Nearly 40 science products, supporting a variety of land, ocean, and atmospheric applications, are continuously derived from the calibrated reflectances and radiances of each MODIS instrument and widely distributed to the world-wide user community. Following an overview of MODIS instrument operation and calibration activities, this paper provides a summary of both Terra and Aqua MODIS long-term performance. Special considerations that are critical to maintaining MODIS data quality and beneficial for future missions are also discussed.

  5. Comparison of Reflected Solar Radiance Using Aqua Modis and Airborne Remote Sensing (case : Deep Convective Clouds and Cirrus Clouds)

    NASA Astrophysics Data System (ADS)

    Krisna, T. C.; Ehrlich, A.; Werner, F.; Wendisch, M.

    2015-12-01

    Deep Convective Clouds (DCCs) have key role in the tropical region. Despite they only have small spatial coverage, but they account most of the total precipitation in these region which often make flooding. There are such of aviation accidents caused by strong vertical wind, hailing, icing and lightning inside the clouds. Pollutions caused by biomass burning and land degradation can change the aerosol properties as well as cloud properties, therefore will influence the radiation and formation of the DCCs. Those are the major reasons that better understanding of DCCs formation and life cycle are necessary. Between Sept. 01 - Oct. 14, ACRIDICON (Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Concevtive Clouds Systems) campaign was conducted over Amazonia. It is suitable area to be the site-study due to has strong contrast environtment (pristine and polluted), regular convection activities and stable meteorological condition. In this study we focus on the 2 satellite validation missions designed to fly collocated but in different altitude with A-TRAIN constellation. In order to study DCCs-solar radiation interaction, we use SMART (Spectral Modular Airborne Radiation Measurements System) installed on HALO (High Altitude and Long-Range Research Aircraft) which measures spectral Irradiance (F) and Radiance (I) at the wavelength between 300-2200 nm corresponding to satellite. Due to the limitation in spatial and temporal, airborne measurements only give snapshots of atmosphere condition and DCCs formation, therefore we use multi-satellite data as DCCs have high vertical and horizontal distance, long temporal development and complex form. The comparison of AQUA MODIS and SMART Radiance at 645 nm (non-absorbing) in the clear-sky condition gives strong agreement, but in the multilayer-cloud condition gives worse and results in high underestimation (-86%) in SMART data especially at lower altitude. The bias is caused by interference from clouds

  6. Corrections to the MODIS Aqua Calibration Derived From MODIS Aqua Ocean Color Products

    NASA Technical Reports Server (NTRS)

    Meister, Gerhard; Franz, Bryan Alden

    2013-01-01

    Ocean color products such as, e.g., chlorophyll-a concentration, can be derived from the top-of-atmosphere radiances measured by imaging sensors on earth-orbiting satellites. There are currently three National Aeronautics and Space Administration sensors in orbit capable of providing ocean color products. One of these sensors is the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, whose ocean color products are currently the most widely used of the three. A recent improvement to the MODIS calibration methodology has used land targets to improve the calibration accuracy. This study evaluates the new calibration methodology and describes further calibration improvements that are built upon the new methodology by including ocean measurements in the form of global temporally averaged water-leaving reflectance measurements. The calibration improvements presented here mainly modify the calibration at the scan edges, taking advantage of the good performance of the land target trending in the center of the scan.

  7. Status of Aqua MODIS On-orbit Calibration and Characterization

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Barnes, W.; Chiang, K.; Erives, H.; Che, N.; Sun, J.; Isaacman, A.; Salomonson, V.

    2004-01-01

    The MODIS Flight Model 1 (FM1) has been in operation for more than two years since its launch onboard the NASA's Earth Observing System (EOS) Aqua spacecraft on May 4, 2002. The MODIS has 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.2 micron and 16 thermal emissive bands (TEB) from 3.7 to 14.5 micron. It provides the science community observations (data products) of the Earth's land, oceans, and atmosphere for a board range of applications. Its primary on-orbit calibration and characterization activities are performed using a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) system for the RSB and a blackbody for the TEB. Another on-board calibrator (OBC) known as the spectro-radiometric calibration assembly (SRCA) is used for the instrument's spatial (TEB and RSB) and spectral (RSB only) characterization. We present in this paper the status of Aqua MODIS calibration and characterization during its first two years of on-orbit operation. Discussions will be focused on the calibration activities executed on-orbit in order to maintain and enhance the instrument's performance and the quality of its Level 1B (L1B) data products. We also provide comparisons between Aqua MODIS and Terra MODIS (launched in December, 1999), including their similarity and difference in response trending and optics degradation. Existing data and results show that Aqua MODIS bands 8 (0.412 micron) and 9 (0.443 micron) have much smaller degradation than Terra MODIS bands 8 and 9. The most noticeable feature shown in the RSB trending is that the mirror side differences in Aqua MODIS are extremely small and stable (<0.1%) while the Terra MODIS RSB trending has shown significant mirror side difference and wavelength dependent degradation. The overall stability of the Aqua MODIS TEB is also better than that of the Terra MODIS during their first two years of on-orbit operation.

  8. Surface Albedo/BRDF Parameters (Terra/Aqua MODIS)

    DOE Data Explorer

    Trishchenko, Alexander

    2008-01-15

    Spatially and temporally complete surface spectral albedo/BRDF products over the ARM SGP area were generated using data from two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on Terra and Aqua satellites. A landcover-based fitting (LBF) algorithm is developed to derive the BRDF model parameters and albedo product (Luo et al., 2004a). The approach employs a landcover map and multi-day clearsky composites of directional surface reflectance. The landcover map is derived from the Landsat TM 30-meter data set (Trishchenko et al., 2004a), and the surface reflectances are from MODIS 500m-resolution 8-day composite products (MOD09/MYD09). The MOD09/MYD09 data are re-arranged into 10-day intervals for compatibility with other satellite products, such as those from the NOVA/AVHRR and SPOT/VGT sensors. The LBF method increases the success rate of the BRDF fitting process and enables more accurate monitoring of surface temporal changes during periods of rapid spring vegetation green-up and autumn leaf-fall, as well as changes due to agricultural practices and snowcover variations (Luo et al., 2004b, Trishchenko et al., 2004b). Albedo/BRDF products for MODIS on Terra and MODIS on Aqua, as well as for Terra/Aqua combined dataset, are generated at 500m spatial resolution and every 10-day since March 2000 (Terra) and July 2002 (Aqua and combined), respectively. The purpose for the latter product is to obtain a more comprehensive dataset that takes advantages of multi-sensor observations (Trishchenko et al., 2002). To fill data gaps due to cloud presence, various interpolation procedures are applied based on a multi-year observation database and referring to results from other locations with similar landcover property. Special seasonal smoothing procedure is also applied to further remove outliers and artifacts in data series.

  9. Calibration Adjustments to the MODIS Aqua Ocean Color Bands

    NASA Technical Reports Server (NTRS)

    Meister, Gerhard

    2012-01-01

    After the end of the SeaWiFS mission in 2010 and the MERIS mission in 2012, the ocean color products of the MODIS on Aqua are the only remaining source to continue the ocean color climate data record until the VIIRS ocean color products become operational (expected for summer 2013). The MODIS on Aqua is well beyond its expected lifetime, and the calibration accuracy of the short wavelengths (412nm and 443nm) has deteriorated in recent years_ Initially, SeaWiFS data were used to improve the MODIS Aqua calibration, but this solution was not applicable after the end of the SeaWiFS mission_ In 2012, a new calibration methodology was applied by the MODIS calibration and support team using desert sites to improve the degradation trending_ This presentation presents further improvements to this new approach. The 2012 reprocessing of the MODIS Aqua ocean color products is based on the new methodology.

  10. Cross-calibration of the Oceansat-2 Ocean Colour Monitor (OCM) with Terra and Aqua MODIS

    NASA Astrophysics Data System (ADS)

    Angal, Amit; Brinkmann, Jake; Kumar, A. Senthil; Xiong, Xiaoxiong

    2016-05-01

    The Ocean Colour Monitor (OCM) sensor on-board the Oceansat-2 spacecraft has been operational since its launch in September, 2009. The Oceansat 2 OCM primary design goal is to provide continuity to Oceansat-1 OCM to obtain information regarding various ocean-colour variables. OCM acquires Earth scene measurements in eight multi-spectral bands in the range from 402 to 885 nm. The MODIS sensor on the Terra and Aqua spacecraft has been successfully operating for over a decade collecting measurements of the earth's land, ocean surface and atmosphere. The MODIS spectral bands, designed for land and ocean applications, cover the spectral range from 412 to 869 nm. This study focuses on comparing the radiometric calibration stability of OCM using near-simultaneous TOA measurements with Terra and Aqua MODIS acquired over the Libya 4 target. Same-day scene-pairs from all three sensors (OCM, Terra and Aqua MODIS) between August, 2014 and September, 2015 were chosen for this analysis. On a given day, the OCM overpass is approximately an hour after the Terra overpass and an hour before the Aqua overpass. Due to the orbital differences between Terra and Aqua, MODIS images the Libya 4 site at different scan-angles on a given day. Some of the high-gain ocean bands for MODIS tend to saturate while viewing the bright Libya 4 target, but bands 8-10 (412 nm - 486 nm) provide an unsaturated response and are used for comparison with the spectrally similar OCM bands. All the standard corrections such as bidirectional reflectance factor (BRDF), relative spectral response mismatch, and impact for atmospheric water-vapor are applied to obtain the reflectance differences between OCM and the two MODIS instruments. Furthermore, OCM is used as a transfer radiometer to obtain the calibration differences between Terra and Aqua MODIS reflective solar bands.

  11. Retrieval of Aerosol Properties from MODIS Terra, MODIS Aqua, and VIIRS SNPP: Calibration Focus

    NASA Technical Reports Server (NTRS)

    Levy, Robert C.; Mattoo, Shana; Sawyer, Virginia; Kleidman, Richard; Patadia, Falguni; Zhou, Yaping; Gupta, Pawan; Shi, Yingxi; Remer, Lorraine; Holz, Robert

    2016-01-01

    MODIS-DT Collection 6 - Aqua/Terra level 2, 3; entire record processed - "Trending" issues reduced - Still a 15% or 0.02 Terra vs Aqua offset. - Terra/Aqua convergence improved with C6+, but bias remains. - Other calibration efforts yield mixed results. VIIRS-­-DT in development - VIIRS is similar, yet different then MODIS - With 50% wider swath, VIIRS has daily coverage - Ensures algorithm consistency with MODIS. - Currently: 20% NPP vs Aqua offset over ocean. - Only small bias (%) over land (2012-­-2016) - Can VIIRS/MODIS create aerosol CDR? Calibration for MODIS - VIIRS continues to fundamentally important. It's not just Terra, or just Aqua, or just NPP-­-VIIRS, I really want to push synergistic calibration.

  12. Overview of Terra and Aqua MODIS Status

    NASA Technical Reports Server (NTRS)

    Salomonson, Vincent V.

    2005-01-01

    This presentation will consist of two one-hour lectures. The first lecture will review the characteristics of the MODIS instrument and how it responds to the performance specifications. The pre-launch and on-orbit procedures and results to characterize and maintain instrument output so as to allow the prescribed science to be done will also be outlined. This will include defining the equations used to account for gain changes and any degradation in the optics of the instrument or the on-board calibration devices themselves. The changes in the solar diffuser and the radiance versus scan angle performance of the scan mirror will also be reviewed. Overall it will be shown that the instrument has and is meeting specifications of 2% reflectance relative to the sun, 5% in the radiance observed in the reflected solar radiation bands, and 0.5-1% in the thermal bands. The second lecture will review and describe highlights in the geophysical products and related science results. There are approximately 40 geophysical products related to observations of land, ocean and atmosphere features. Many of the results are unprecedented and offer considerable advances over those achievable with heritage instruments such as the NOAA Advanced Very High Resolution Radiometer (AVHRR). The literature is showing a steady growth of publications in scientific journals using MODIS data or products. The future is also bright in that a follow-on instrument based on the MODIS will be flown on the National Polar-Orbiting Environmental Satellite Series (NPOESS) starting around 2010.

  13. MODIS Solar Reflective Calibration Traceability

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Butler, Jim

    2009-01-01

    Long-term climate data records often consist of observations made by multiple sensors. It is, therefore, extremely important to have instrument overlap, to be able to track instrument stability, to quantify, measurement uncertainties, and to establish absolute scale traceable to the International System of Units (SI). The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument for both the Terra and Aqua missions, which were launched in December 1999 and May 2002, respectively. It has 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers and observes the Earth at three nadir spatial resolutions: 0.25km, 0.5km, and 1km. MODIS RSB on-orbit calibration is reflectance based with reference to the bidirectional reflectance factor (BRF) of its on-board solar diffuser (SD). The SD BRF characterization was made pre-launch by the instrument vendor using reference samples traceable directly to the National Institute of Standards and Technology (NIST). On-orbit SD reflectance degradation is tracked by an on-board solar diffuser monitor (SDSM). This paper provides details of this calibration chain, from prelaunch to on-orbit operation, and associated uncertainty assessments. Using MODIS as an example, this paper also discusses challenges and key design requirements for future missions developed for accurate climate studies.

  14. Synergism of MODIS Aerosol Remote Sensing from Terra and Aqua

    NASA Technical Reports Server (NTRS)

    Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.

    2003-01-01

    The MODerate-resolution Imaging Spectro-radiometer (MODIS) sensors, aboard the Earth Observing System (EOS) Terra and Aqua satellites, are showing excellent competence at measuring the global distribution and properties of aerosols. Terra and Aqua were launched on December 18, 1999 and May 4, 2002 respectively, with daytime equator crossing times of approximately 10:30 am and 1:30 pm respectively. Several aerosol parameters are retrieved at 10-km spatial resolution from MODIS daytime data over land and ocean surfaces. The parameters retrieved include: aerosol optical thickness (AOT) at 0.47, 0.55 and 0.66 micron wavelengths over land, and at 0.47, 0.55, 0.66, 0.87, 1.2, 1.6, and 2.1 microns over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. Since the beginning of its operation, the quality of Terra-MODIS aerosol products (especially AOT) have been evaluated periodically by cross-correlation with equivalent data sets acquired by ground-based (and occasionally also airborne) sunphotometers, particularly those coordinated within the framework of the AErosol Robotic NETwork (AERONET). Terra-MODIS AOT data have been found to meet or exceed pre-launch accuracy expectations, and have been applied to various studies dealing with local, regional, and global aerosol monitoring. The results of these Terra-MODIS aerosol data validation efforts and studies have been reported in several scientific papers and conferences. Although Aqua-MODIS is still young, it is already yielding formidable aerosol data products, which are also subjected to careful periodic evaluation similar to that implemented for the Terra-MODIS products. This paper presents results of validation of Aqua-MODIS aerosol products with AERONET, as well as comparative evaluation against corresponding Terra-MODIS data. In addition, we show interesting independent and synergistic applications of MODIS aerosol data from

  15. Adjusting Aqua MODIS TEB nonlinear calibration coefficients using iterative solution

    NASA Astrophysics Data System (ADS)

    Wu, Aisheng; Wang, Zhipeng; Li, Yonghong; Madhavan, Sriharsha; Wenny, Brian N.; Chen, Na; Xiong, Xiaoxiong

    2014-11-01

    Radiometric calibration is important for continuity and reliability of any optical sensor data. The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA EOS (Earth Observing System) Aqua satellite has been nominally operating since its launch on May 4, 2002. The MODIS thermal emissive bands (TEB) are calibrated using a quadratic calibration algorithm and the dominant gain term is determined every scan by reference to a temperature-controlled blackbody (BB) with known emissivity. On a quarterly basis, a BB warm-up and cool-down (WUCD) process is scheduled to provide measurements to determine the offset and nonlinear coefficients used in the TEB calibration algorithm. For Aqua MODIS, the offset and nonlinear terms are based on the results from prelaunch thermal vacuum tests. However, on-orbit trending results show that they have small but noticeable drifts. To maintain data quality and consistency, an iterative approach is applied to adjust the prelaunch based nonlinear terms, which are currently used to produce Aqua MODIS Collection-6 L1B. This paper provides details on how to use an iterative solution to determine these calibration coefficients based on BB WUCD measurements. Validation is performed using simultaneous nadir overpasses (SNO) of Aqua MODIS and the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Metop-A satellite and near surface temperature measurements at Dome C on the Antarctic Plateau.

  16. Cross-calibration of Landsat 5 TM and Landsat 8 OLI with Aqua MODIS using PICS

    NASA Astrophysics Data System (ADS)

    Angal, Amit; Mishra, Nischal; Xiong, Xiaoxiong; Helder, Dennis

    2014-09-01

    The Thematic Mapper (TM) onboard the Landsat 5 (L5) has provided an unprecedented amount of earth observations for more than 25 years since its launch on March 1, 1984. The MODIS sensor onboard the Aqua satellite is a part of the afternoon constellation of spacecraft and has been successfully providing near-continuous observations of the earth's surface and atmosphere since July 2002. A synergistic use of TM and MODIS reflective solar bands (RSB) measurements is immensely beneficial to the broad user community for different land cover change and global climate studies. A consistent radiometric calibration between the sensors is a prerequisite for creating high quality science products. Various pseudo-invariant calibration sites (PICS) identified by CEOS have been widely used to monitor the on-orbit calibration consistency for a number of sensors. Near-simultaneous observations of the Saharan PICS by L5 TM and Aqua MODIS are used in this study. The top-of-atmosphere (TOA) reflectance from the spectrally matching RSB are corrected for test site Bi-directional Reflectance Distribution Function (BRDF), relative spectral response (RSR) mismatch, and impacts for atmospheric water-vapor, and used to estimate the long-term calibration differences between the two sensors. The Operational Land Imager (OLI) onboard the Landsat 8 (L8) launched in February, 2013, is a follow-on mission to maintain the continuity of Landsat acquisitions. A similar cross-calibration methodology was extended to compare the spectrally matching bands of Aqua MODIS with OLI. A long-term drift is observed in bands 1 (3.7%) and 3 (1.86%) of L5 TM, which is expected to be mitigated in the next calibration coefficient update. With the exception of the SWIR-2 band (L5 TM band 7), the agreement with Aqua MODIS is seen to be within 4%. The L8 OLI and Aqua MODIS agreement is seen within 4% across all wavelengths.

  17. Assessment of MODIS Reflected Solar Calibration Uncertainty

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Sun, Junqiang; Butler, James

    2011-01-01

    Determination of the calibration accuracy and traceability of a remote sensing instrument is a driving issue in the use of satellite data for calibration inter-comparisons and studying climate change. The Terra and Aqua MODerate Resolution Imaging Spectroradiometer (MODIS) instruments have successfully operated for more than 11 and 9 years, respectively. Twenty of the thirty six MODIS spectral bands are in the reflected solar region with center wavelengths ranging from 0.41 to 2.2 microns. MODIS reflective solar band (RSB) on-orbit calibration is reflectance based through the use of an on-board solar diffuser (SO). The calibration uncertainty requirements are +/-2.0% for the RSB reflectance factors at sensor specified typical scene reflectances or radiances. The SO bi-directional reflectance factor (BRF) was characterized pre-launch and its on-orbit changes are tracked by an on-board solar diffuser stability monitor (SDSM). This paper provides an assessment of MODIS RSB on-orbit calibration traceability and uncertainty for its Level 1B (L1B) reflectance factors. It examines in details each of the uncertainty contributors, including those from pre-launch measurements as well as on-orbit observations. Common challenging issues and differences due to individual sensors' specific characteristics and on-orbit performance are also discussed in this paper. Guidance and recommendations are presented, based on lessons from MODIS RSB calibration uncertainty assessment, for the development of future instrument calibration and validation plans.

  18. Assessment of the Visible Channel Calibrations of the TRMM VIRS and MODIS on Aqua and Terra

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Doelling, David R.; Nguyen, Louis; Miller, Walter F.; Chakrapani, Venketesan

    2007-01-01

    Several recent research satellites carry self-calibrating multispectral imagers that can be used for calibrating operational imagers lacking complete self-calibrating capabilities. In particular, the visible (VIS, 0.65 m) channels on operational meteorological satellites are generally calibrated before launch, but require vicarious calibration techniques to monitor the gains and offsets once they are in orbit. To ensure that the self-calibrating instruments are performing as expected, this paper examines the consistencies between the VIS channel (channel 1) reflectances of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites and the Version 5a and 6 reflectances of the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission using a variety of techniques. These include comparisons of Terra and Aqua VIS radiances with coincident broadband shortwave radiances from the well-calibrated Clouds and the Earth s Radiant Energy System (CERES), time series of deep convective cloud (DCC) albedos, and ray-matching intercalibrations between each of the three satellites. Time series of matched Terra and VIRS data, Aqua and VIRS data, and DCC reflected fluxes reveal that an older version (Version 5a, ending in early 2004) of the VIRS calibration produced a highly stable record, while the latest version (Version 6) appears to overestimate the sensor gain change by approx.1%/y as the result of a manually induced gain adjustment. Comparisons with the CERES shortwave radiances unearthed a sudden change in the Terra MODIS calibration that caused a 1.17% decrease in the gain on 19 November 2003 that can be easily reversed. After correction for these manual adjustments, the trends in the VIRS and Terra channels are no greater than 0.1%/y. Although the results were more ambiguous, no statistically significant trends were found in the Aqua MODIS channel-1 gain. The Aqua radiances are 1% greater, on average, than their

  19. Overview of Aqua MODIS 10-year On-orbit Calibration and Performance

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Wenny, B.; Sun, J.; Wu, A.; Chen, H.; Angal, A.; Choi, T.; Madhavan, S.; Geng, X.; Link, D.; Toller, G.; Barnes, W.; Salomonson, V.

    2012-01-01

    Since launch in May 2002, Aqua MODIS has successfully operated for nearly 10 years, continuously collecting global datasets for scientific studies of key parameters of the earth's land, ocean, and atmospheric properties and their changes over time. The quality of these geophysical parameters relies on the input quality of sensor calibrated radiances. MODIS observations are made in 36 spectral bands with wavelengths ranging from visible (VIS) to longwave infrared (LWIR). Its reflective solar bands (RSB) are calibrated using data collected from its on-board solar diffuser and regularly scheduled lunar views. The thermal emissive bands (TEB) are calibrated using an on-board blackbody (BB). The changes in the sensor's spectral and spatial characteristics are monitored by an on-board spectroradiometric calibration assembly (SRCA). This paper presents an overview of Aqua MODIS 10-year on-orbit operation and calibration activities, from launch to present, and summarizes its on-orbit radiometric, spectral, and spatial calibration and characterization performance. In addition, it will illustrate and discuss on-orbit changes in sensor characteristics and corrections applied to continuously maintain the sensor level 1B (L1B) data quality, as well as lessons learned that could benefit future calibration efforts.

  20. NPP VIIRS and Aqua MODIS RSB Comparison Using Observations from Simultaneous Nadir Overpasses (SNO)

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Wu, A.

    2012-01-01

    Suomi NPP (National Polar-orbiting Partnership) satellite (http://npp.gsfc.nasa.gov/viirs.html) began to daily collect global data following its successful launch on October 28, 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key NPP sensor. Similar to the design of the OLS, SeaWiFS and MODIS instruments, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background subtraction. Immediately after the VIIRS nadir door s opening on November 21, 2011, anomalously large degradation in the SD response was identified in the near-IR wavelength region, which was unexpected as decreases in the SD reflectance usually occur gradually in the blue (0.4 m) wavelength region based on past experience. In this study, we use a well-calibrated Aqua MODIS as reference to track and evaluate VIIRS RSB stability and performance. Reflectances observed by both sensors from simultaneous nadir overpasses (SNO) are used to determine VIIRS to MODIS reflectance ratios for their spectral matching bands. Results of this study provide an immediate post-launch assessment, independent validation of the anomalous degradation observed in SD measurements at near-IR wavelengths and initial analysis of calibration stability and consistency.

  1. Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Hubanks, Paul A.

    2012-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to

  2. Evaluation of high resolution MODIS-Aqua data for oil spill monitoring

    NASA Astrophysics Data System (ADS)

    Lotliker, Aneesh A.; Mupparthy, Raghavendra S.; Tummala, Srinivasa K.; Nayak, Shailesh R.

    2009-01-01

    The MODIS - Aqua high-resolution imagery were exploited to detect and monitor oil spills. An evaluation criterion has been established to study its potential. The study focused on two oil spill events: Lake Maracaibo, Venezuela (January 18-20, 2003) and Jiyeh power station oil spill, Lebanon (July 15-31, 2006). The images were examined at level-1B (only geometrically corrected) and level-2 (geometrically and atmospherically corrected) data processing levels. The level-2 data lacked the sufficient contrast range, because of the rigorous atmospheric correction, while the level-1B data were found to be suitable. The 250-m data at 645 and 859 nm and 500-m, interpolated to 250-m, at 469, 555, 1240, and 2130 nm were analyzed. The methodology included examination of individual bands and evaluation of 30 band ratioing combinations to improve the contrast of oil spills in the images. The evaluation criteria were based on both visual and parametric. The metrics involved are: mean contrast function and feature matching. In addition, bi-directional reflectance distribution function (BRDF) at 469, 555, and 645 nm wavelengths, were also evaluated using the same criteria. The study found that at appropriate view-angle, MODIS-Aqua high-resolution is suitable for oil spill detection at 250-m band. When the view-angle is not appropriate, the combination of mid-IR bands with shorter wavelengths improved the feature matching.

  3. Terra and Aqua MODIS Thermal Emissive Bands On-Orbit Calibration and Performance

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Wu, Aisheng; Wenny, Brian N.; Madhavan, Sriharsha; Wang, Zhipeng; Li, Yonghong; Chen, Na; Barnes, William L.; Salomonson, Vincent V.

    2015-01-01

    Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua spacecraft have operated successfully for more than 14 and 12 years, respectively. A key instrument for National Aeronautics and Space Administration Earth Observing System missions, MODIS was designed to make continuous observations for studies of Earth's land, ocean, and atmospheric properties and to extend existing data records from heritage Earth observing sensors. The 16 thermal emissive bands (TEBs) (3.75-14.24 micrometers) are calibrated on orbit using a temperature controlled blackbody (BB). Both Terra and Aqua MODIS BBs have displayed minimal drift over the mission lifetime, and the seasonal variations of the BB temperature are extremely small in Aqua MODIS. The long-term gain and noise equivalent difference in temperature performance of the 160 TEB detectors on both MODIS instruments have been well behaved and generally very stable. Small but noticeable variations of Aqua MODIS bands 33-36 (13.34-14.24 micrometer) response in recent years are primarily due to loss of temperature control margin of its passive cryoradiative cooler. As a result, fixed calibration coefficients, previously used by bands when the BB temperature is above their saturation temperatures, are replaced by the focal-plane-temperature-dependent calibration coefficients. This paper presents an overview of the MODIS TEB calibration, the on-orbit performance, and the challenging issues likely to impact the instruments as they continue operating well past their designed lifetime of six years.

  4. Lidar Ratios for Dust Aerosols Derived From Retrievals of CALIPSO Visible Extinction Profiles Constrained by Optical Depths from MODIS-Aqua and CALIPSO/CloudSat Ocean Surface Reflectance Measurements

    NASA Technical Reports Server (NTRS)

    Young, Stuart A.; Josset, Damien B.; Vaughan, Mark A.

    2010-01-01

    CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

  5. Assessment of the Collection 6 Terra and Aqua MODIS bands 1 and 2 calibration performance

    NASA Astrophysics Data System (ADS)

    Wu, A.; Chen, X.; Angal, A.; Li, Y.; Xiong, X.

    2015-09-01

    MODIS (Moderate Resolution Imaging Spectroradiometer) is a key sensor aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. MODIS collects data in 36 spectral bands and generates over 40 data products for land, atmosphere, cryosphere and oceans. MODIS bands 1 and 2 have nadir spatial resolution of 250 m, compared with 500 m for bands 3 to 7 and 1000 m for all the remaining bands, and their measurements are crucial to derive key land surface products. This study evaluates the calibration performance of the Collection-6 L1B for both Terra and Aqua MODIS bands 1 and 2 using three vicarious approaches. The first and second approaches focus on stability assessment using data collected from two pseudo-invariant sites, Libya 4 desert and Antarctic Dome C snow surface. The third approach examines the relative stability between Terra and Aqua in reference to a third sensor from a series of NOAA 15-19 Advanced Very High Resolution Radiometer (AVHRR). The comparison is based on measurements from MODIS and AVHRR Simultaneous Nadir Overpasses (SNO) over a thirteen-year period from 2002 to 2015. Results from this study provide a quantitative assessment of Terra and Aqua MODIS bands 1 and 2 calibration stability and the relative calibration differences between the two sensors.

  6. Inter-satellite comparison and evaluation of Navy SNPP VIIRS and MODIS-Aqua ocean color properties

    NASA Astrophysics Data System (ADS)

    Ladner, S. D.; Arnone, R.; Vandermeulen, R.; Martinolich, P.; Lawson, A.; Bowers, J.; Crout, R.; Ondrusek, M.; Fargion, G.

    2014-05-01

    Navy operational ocean color products of inherent optical properties and radiances are evaluated for the Suomi-NPP VIIRS and MODIS-Aqua sensors. Statistical comparisons with shipboard measurements were determined in a wide variety of coastal, shelf and offshore locations in the Northern Gulf of Mexico during two cruises in 2013. Product consistency between MODIS-Aqua, nearing its end-of-life expectancy, and Suomi-NPP VIIRS is being evaluated for the Navy to retrieve accurate ocean color properties operationally from VIIRS in a variety of water types. Currently, the existence, accuracy and consistency of multiple ocean color sensors (VIIRS, MODIS-Aqua) provides multiple looks per day for monitoring the temporal and spatial variability of coastal waters. Consistent processing methods and algorithms are used in the Navy's Automated Processing System (APS) for both sensors for this evaluation. The inherent optical properties from both sensors are derived using a coupled ocean-atmosphere NIR correction extending well into the bays and estuaries where high sediment and CDOM absorption dominate the optical signature. Coastal optical properties are more complex and vary from chlorophyll-dominated waters offshore. The in-water optical properties were derived using vicariously calibrated remote sensing reflectances and the Quasi Analytical Algorithm (QAA) to derive the Inherent Optical Properties (IOP's). The Naval Research Laboratory (NRL) and the JPSS program have been actively engaged in calibration/validation activities for Visible Infrared Imager Radiometer Suite (VIIRS) ocean color products.

  7. On-Orbit Noise Characterization of MODIS Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Angal, Amit; Xiong, Xiaoxiong; Sun, Junqiang; Geng, Xu

    2015-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS), launched on the Terra and Aqua spacecrafts, was designed to collect complementary and comprehensive measurements of the Earth's properties on a global scale. The 20 reflective solar bands (RSBs), covering a wavelength range from 0.41 to 2.1 micrometers, are calibrated on-orbit using regularly scheduled solar diffuser (SD) observations. Although primarily used for on-orbit gain derivation, the SD observations also facilitate the characterization of the detector signal-to-noise ratio (SNR). In addition to the calibration requirement of 2% for the reflectance factors and 5% for the radiances, the required SNRs are also specified for all RSB at their typical scene radiances. A methodology to characterize the on-orbit SNR for the MODIS RSB is presented. Overall performance shows that a majority of the RSB continue to meet the specification, therefore performing well. A temporal decrease in the SNR, observed in the short-wavelength bands, is attributed primarily to the decrease in their detector responses. With the exception of the inoperable and noisy detectors in band 6 identified prelaunch, the detectors of AquaMODIS RSB perform better than TerraMODIS. The approach formulated for on-orbit SNR characterization can also be used by other sensors that use on-board SDs for their on-orbit calibration (e.g., Suomi National Polar-Orbiting Partnership [SNPP]-Visible Infrared Imaging Radiometer Suite).

  8. Terra and Aqua MODIS Design, Radiometry, and Geometry in Support of Land Remote Sensing

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Wolfe, Robert; Barnes, William; Guenther, Bruce; Vermote, Eric; Saleous, Nazmi; Salomonson, Vincent

    2011-01-01

    The NASA Earth Observing System (EOS) mission includes the construction and launch of two nearly identical Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. The MODIS proto-flight model (PFM) is onboard the EOS Terra satellite (formerly EOS AM-1) launched on December 18, 1999 and hereafter referred to as Terra MODIS. Flight model-1 (FM1) is onboard the EOS Aqua satellite (formerly EOS PM-1) launched on May 04, 2002 and referred to as Aqua MODIS. MODIS was developed based on the science community s desire to collect multiyear continuous datasets for monitoring changes in the Earth s land, oceans and atmosphere, and the human contributions to these changes. It was designed to measure discrete spectral bands, which includes many used by a number of heritage sensors, and thus extends the heritage datasets to better understand both long- and short-term changes in the global environment (Barnes and Salomonson 1993; Salomonson et al. 2002; Barnes et al. 2002). The MODIS development, launch, and operation were managed by NASA/Goddard Space Flight Center (GSFC), Greenbelt, Maryland. The sensors were designed, built, and tested by Raytheon/ Santa Barbara Remote Sensing (SBRS), Goleta, California. Each MODIS instrument offers 36 spectral bands, which span the spectral region from the visible (0.41 m) to long-wave infrared (14.4 m). MODIS collects data at three different nadir spatial resolutions: 0.25, 0.5, and 1 km. Key design specifications, such as spectral bandwidths, typical scene radiances, required signal-to-noise ratios (SNR) or noise equivalent temperature differences (NEDT), and primary applications of each MODIS spectral band are summarized in Table 7.1. These parameters were the basis for the MODIS design. More details on the evolution of the NASA EOS and development of the MODIS instruments are provided in Chap. 1. This chapter focuses on the MODIS sensor design, radiometry, and geometry as they apply to land remote sensing. With near

  9. Two MODIS Aerosol Products Over Ocean on the Terra and Aqua CERES SSF Datasets

    NASA Technical Reports Server (NTRS)

    Ignatov, Alexander; Minnis, Patrick; Loeb, Norman; Wielicki, Bruce; Miller, Walter; Sun-Mack, Sunny; Tanre, Didier; Remer, Lorraine; Laszlo, Istvan; Geier, Erika

    2004-01-01

    Over ocean, two aerosol products are reported on the Terra and Aqua CERES SSFs. Both are derived from MODIS, but using different sampling and aerosol algorithms. This study briefly summarizes these products, and compares using 2 weeks of global Terra data from 15-21 December 2000, and 1-7 June 2001.

  10. Validation of MODIS Terra and Aqua Ice Surface Temperatures at Summit, Greenland

    NASA Astrophysics Data System (ADS)

    Hall, D. K.; Shuman, C. A.; Xiong, X.; Wenny, B. N.; DiGirolamo, N. E.

    2014-12-01

    Ice-surface temperature (IST) is used in many studies, for example for validation of model output and for detection of leads and thin ice in sea ice. The MODerate-resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites are useful for mapping IST of sea ice and the Greenland ice sheet (Hall et al., 2012), and validation of the ISTs derived from MODIS has been an ongoing effort (e.g., Koenig & Hall, 2010; Shuman et al., 2014). Recent results call into question the calibration of the MODIS-derived ISTs at very cold temperatures that are characteristic of the Greenland ice sheet high interior during winter (Shuman et al., 2014). In the present work, we investigate the calibration of MODIS IR bands 31 (10.780 - 11.280 µm) and 32 (11.770 - 12.270 µm) under very cold conditions. MODIS IR bands are calibrated using a quadratic algorithm. In Collection 6 (C6), the offset and nonlinear calibration coefficients are computed from data collected during the blackbody cool-down vs the warm-up data used in Collection 5 (C5). To improve the calibration accuracy for low-temperature scenes, the offset terms are set to 0. In general, Aqua MODIS bands 31 and 32 perform better than Terra MODIS bands 31 and 32. One of the reasons is that the Aqua bands have a lower saturation temperature (~340 K) than the Terra (~380 K) bands, and lower saturation or smaller dynamic range means better resolution. As compared to ~2-m NOAA air temperatures (TA) at Summit, Greenland, Shuman et al. (2014) show a small (~0.5°C) offset in Terra MODIS-derived IST vs TA near 0°C, and an increasingly larger offset (up to ~5°C) as TA drops to -60°C. To investigate this further, we compare Terra and Aqua C5 and C6 ISTs with TA data from Summit. This work will document the calibration of bands 31 and 32 at very low temperatures in C5 and C6. Hall, D.K., et al., 2012: Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

  11. Spatial and Temporal Distribution of Clouds as Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Menzel, Paul; Ackerman, Steven A.

    2006-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24,2000 for Terra and June 24,2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Over the last year, extensive improvements and enhancements in the global cloud products have been implemented, and reprocessing of all MODIS data on Terra has commenced since first light in February 2000. In the cloud mask algorithm, the most extensive improvements were in distinguishing clouds at nighttime, including the challenging polar darkness regions of the world. Additional improvements have been made to properly distinguish sunglint from clouds in the tropical ocean regions, and to improve the identification of clouds from snow during daytime in Polar Regions. We will show global monthly mean cloud fraction for both Terra and Aqua, and show how similar the global daytime cloud fraction is from these morning and afternoon orbits, respectively. We will also show the zonal distribution of cloud fraction over land and ocean regions for both Terra and Aqua, and show the time series of global cloud fraction from July 2002 through June 2006.

  12. Assessment of diverse algorithms applied on MODIS Aqua and Terra data over land surfaces in Europe

    NASA Astrophysics Data System (ADS)

    Glantz, P.; Tesche, M.

    2012-04-01

    Beside an increase of greenhouse gases (e.g., carbon dioxide, methane and nitrous oxide) human activities (for instance fossil fuel and biomass burning) have lead to perturbation of the atmospheric content of aerosol particles. Aerosols exhibits high spatial and temporal variability in the atmosphere. Therefore, aerosol investigation for climate research and environmental control require the identification of source regions, their strength and aerosol type, which can be retrieved based on space-borne observations. The aim of the present study is to validate and evaluate AOT (aerosol optical thickness) and Ångström exponent, obtained with the SAER (Satellite AErosol Retrieval) algorithm for MODIS (MODerate resolution Imaging Spectroradiometer) Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground), against AERONET (AErosol RObotic NETwork) observations and MODIS Collection 5 (c005) standard product retrievals (10 km), respectively, over land surfaces in Europe for the seasons; early spring (period 1), mid spring (period 2) and summer (period 3). For several of the cases analyzed here the Aqua and Terra satellites passed the investigation area twice during a day. Thus, beside a variation in the sun elevation the satellite aerosol retrievals have also on a daily basis been performed with a significant variation in the satellite-viewing geometry. An inter-comparison of the two algorithms has also been performed. The validation with AERONET shows that the MODIS c005 retrieved AOT is, for the wavelengths 0.469 and 0.500 nm, on the whole within the expected uncertainty for one standard deviation of the MODIS retrievals over Europe (Δτ = ±0.05 ± 0.15τ). The SAER estimated AOT for the wavelength 0.443 nm also agree reasonable well with AERONET. Thus, the majority of the SAER AOT values are within the MODIS expected uncertainty range, although somewhat larger RMSD (root mean square deviation) occurs compared to the results obtained with the

  13. Consistency of Global Modis Aerosol Optical Depths over Ocean on Terra and Aqua Ceres SSF Datasets

    NASA Technical Reports Server (NTRS)

    Ignatov, Alexander; Minnis, Patrick; Miller, Walter F.; Wielicki, Bruce A.; Remer, Lorraine

    2006-01-01

    Aerosol retrievals over ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side-by-side. The primary M product is generated by sub-setting and remapping the multi-spectral (0.47-2.1 micrometer) MODIS produced oceanic aerosol (MOD04/MYD04 for Terra/Aqua) onto CERES footprints. M*D04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary AVHRR-like A product is generated in only two MODIS bands 1 and 6 (on Aqua, bands 1 and 7). The A processing uses the CERES cloud screening algorithm, and NOAA/NESDIS glint identification, and single-channel aerosol retrieval algorithms. The M and A products have been documented elsewhere and preliminarily compared using 2 weeks of global Terra CERES SSF Edition 1A data in which the M product was based on MOD04 collection 3. In this study, the comparisons between the M and A aerosol optical depths (AOD) in MODIS band 1 (0.64 micrometers), tau(sub 1M) and tau(sub 1A) are re-examined using 9 days of global CERES SSF Terra Edition 2A and Aqua Edition 1B data from 13 - 21 October 2002, and extended to include cross-platform comparisons. The M and A products on the new CERES SSF release are generated using the same aerosol algorithms as before, but with different preprocessing and sampling procedures, lending themselves to a simple sensitivity check to non-aerosol factors. Both tau(sub 1M) and tau(sub 1A) generally compare well across platforms. However, the M product shows some differences, which increase with ambient cloud amount and towards the solar side of the orbit. Three types of comparisons conducted in this study - cross-platform, cross-product, and cross-release confirm the previously made observation that the major area for

  14. Evaluation of monthwise and overall trends of AOD over Indian cities using MODIS Aqua and Terra retrievals

    NASA Astrophysics Data System (ADS)

    Banerjee, Subhasis; Ghosh, Sanjay

    2016-07-01

    Atmospheric aerosols have been shown to have profound impact on climate system and human health. Regular and systematic monitoring of ambient air is thus necessary in order to asses its impact. There are several ground based stations worldwide employed in this service but still their numbers are inadequate and it is even almost impossible to have such stations at difficult geographical terrains and take measurement throughout the year. Aerosol optical depth or AOD, which is a measure of extinction of incoming solar radiation, serves as proxy to atmospheric aerosol loading. Various sensors onboard different satellites take routine measurement of AOD throughout the year. Satellite based AOD is used in many studies due to their wide coverage and availability for a longer time period. Satellite measures reflected solar radiation at the top of the atmosphere. Column integrated value of aerosol are routinely estimated from those measurements using suitable inversion algorithms. MODIS instrument onboard Aqua and Terra satellites of Earth Observing System takes routine measurement in wide spectral range. We used those data to evaluate trend of AOD over almost fifty Indian cities having population more than a million. The cities we have chosen spread over almost entire length and breadth of the country. Few such studies have already been conducted using MODIS data. They typically used level 3 data. Since Level 3 data comes in 1x 1 degree gridded form they provide average value over a vast geographical region. We used level 2 dataset to enable us taking smaller region(1/2 x 1/2 degree here) centering the region of our interest . We used seasonal Mann-Kendall (M-K) statistics coupled with Sen's non-parametric slope estimation procedure to estimate monthwise and overall(i.e., yearly trend taking seasonality into account) AOD trend. We used median AOD for each month of every year to discard very high AOD's which we often get due to cloud contamination. Seasonal M-K test takes

  15. Surface circulation patterns in the Gulf of California derived from MODIS Aqua 250 m

    NASA Astrophysics Data System (ADS)

    Martínez-Flores, G.; Salinas-González, F.; Gutiérrez de Velasco-Sanromán, G.; Godínez-Orta, L.

    2009-04-01

    The Gulf of California (GC) is a marginal elongated and semi-enclosed sea located at northwest of Mexico, between the Peninsula of Baja California and the mainland Mexico. The considered area average 150 km in width and 1500 km in length, from the mouth of the Colorado River to Cabo Corrientes, Jalisco. It has a maximum depth of 3600 m at the southern inlet and the northern region average 200 m in deep. The study of superficial circulation patterns in the GC is of interest because its relevance to the mechanisms of transport for distribution of a variety of materials -plankton, contaminants, microalgae, etc.- and its association with areas of sedimentary deposits, zones where there is a higher probability for fishing or related to the presence of certain species of marine life. Recent studies explain the circulation of the GC as a result of the Pacific Ocean's forcing, wind, heat fluxes on the sea surface and the interaction between the flow produced by these agents and bathymetry. The objective of this work was to obtain evidence of the patterns of surface circulation using a spatial resolution of 250 m over a period of two to seven days (depending on cloud cover), which offered images from the MODIS Level 1B. This essay is an attempt to contribute with more information to the understanding of the regional dynamics of the GC and its local influence on the zones bordering the coast. Thus, MODIS Aqua 250 m data was used, to which algorithms were applied in order to enhance the contrast of reflectance levels of these bands (0.620-0.670 and 0.841-0.876 µm) within the marine environment. The results are associated with suspended particulate matter (SPM), which we used as tracers of the surface circulation, using a sequence of images from January 2004 to December 2008. Algorithms for dust and cloud detection were used and incorporated with thermal band images, in which zones of terrigenous contribution by eolian transport were identified. Furthermore, pluvial

  16. Response versus scan-angle corrections for MODIS reflective solar bands using deep convective clouds

    NASA Astrophysics Data System (ADS)

    Bhatt, Rajendra; Angal, Amit; Doelling, David R.; Xiong, Xiaoxiong; Wu, Aisheng; Haney, Conor O.; Scarino, Benjamin R.; Gopalan, Arun

    2016-05-01

    The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the degradation of the SD over time, provides the baseline for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the background, respectively. The MODIS instrument views the Earth's surface using a two-sided scan mirror, whose reflectance is a function of the angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different AOIs. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two AOIs. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from the pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for select short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent at the beginning of the earth-view scan.

  17. The NASA Earth Observing System (EOS) Terra and Aqua Mission Moderate Resolution Imaging Spectroradiometer (MODIS: Science and Applications

    NASA Technical Reports Server (NTRS)

    Salomnson, Vincent V.

    2003-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. The EOS Aqua mission was launched successfully May 4,2002 with another MODIS on it and "first light" observations occurred on June 24,2002. The Terra MODIS is in a sun-synchronous orbit going north to south in the daylight portion of the orbit crossing the equator at about 1030 hours local time. The Aqua spacecraft operates in a sun-synchronous orbit going south to north in the daylight portion of the orbit crossing the equator at approximately 1330 hours local time. The spacecraft, instrument, and data systems for both MODIS instruments are performing well and are producing a wide variety of data products useful for scientific and applications studies in relatively consistent fashion extending from November 2000 to the present. Within the approximately 40 MODIS data products, several are new and represent powerful and exciting capabilities such the ability to provide observations over the globe of fire occurrences, microphysical properties of clouds and sun-stimulated fluorescence from phytoplankton in the surface waters of the ocean. The remainder of the MODIS products exceeds or, at a minimum, matches the capabilities of products from heritage sensors such as, for example, the Advanced Very High Resolution Radiometer (AVHRR). Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAAC's) or through Direct Broadcast (DB) stations.

  18. Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency

    NASA Astrophysics Data System (ADS)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G.

    2015-12-01

    The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by ˜0.04 over bright (e.g., desert) and ˜0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by ˜10% and ˜5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

  19. Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

    NASA Technical Reports Server (NTRS)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G.

    2015-01-01

    The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by approximately 0.04 over bright (e.g., desert) and approximately 0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by approximately 10% and approximately 5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

  20. The Characterization of Deep Convective Cloud Albedo as a Calibration Target Using MODIS Reflectances

    NASA Technical Reports Server (NTRS)

    Doelling, David R.; Hong, Gang; Morstad, Daniel; Bhatt, Rajendra; Gopalan, Arun; Xiong, Jack

    2010-01-01

    There are over 25 years of historical satellite data available to climate analysis. The historical satellite data needs to be well calibrated, especially in the visible, where there is no onboard calibration on operational satellites. The key to the vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard black-bodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean. Functionality between particle size and ozone absorption with DCC albedo will be examined. Although DCC clouds are nearly Lambertion, the angular distribution of reflectances will be sampled and compared with theoretical models. Both Aqua and Terra MODIS DCC angular models will be compared for consistency. Normalizing angular geostationary DCC reflectances, which were calibrated against MODIS, with SCIAMACHY spectral reflectances and comparing them to MODIS DCC reflectances will inspect the usage of DCC albedos as an absolute calibration target.

  1. Tracking daily land surface albedo and reflectance anisotropy with moderate-resolution imaging spectroradiometer (MODIS)

    NASA Astrophysics Data System (ADS)

    Shuai, Yanmin

    A new algorithm provides daily values of land surface albedo and angular reflectance at a 500-m spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently in orbit on NASA's Terra and Aqua satellite platforms. To overcome the day-to-day variance in observed surface reflectance induced by differences in view and solar illumination angles, the algorithm uses the RossThickLiSparse-Reciprocal bidirectional reflectance model, which is fitted to all MODIS observations of a 500-m resolution cell acquired during a 16-day moving window. Individual observations are weighted by their quality, observation coverage, and proximity to the production date of interest. Product quality is measured by (1) the root mean square error (RMSE) of observations against the best model fit; and (2) the ability of the angular sampling pattern of the observations at hand to determine reflectance model parameters accurately. A regional analysis of model fits to data from selected MODIS data tiles establishes the bounds of these quality measures for application in the daily algorithm. The algorithm, which is now available to users of direct broadcast satellite data from MODIS, allows daily monitoring of rapid surface radiation and land surface change phenomena such as crop development and forest foliage cycles. In two demonstrations, the daily algorithm captured rapid change in plant phenology. The growth phases of a winter wheat crop, as monitored at the Yucheng agricultural research station in Yucheng, China, matched MODIS daily multispectral reflectance data very well, especially during the flowering and heading stages. The daily algorithm also captured the daily change in autumn leaf color in New England, documenting the ability of the algorithm to work well over large regions with varying degrees of cloud cover and atmospheric conditions. Daily surface albedos measured using ground-based instruments on towers at the agricultural and

  2. Spatial and Temporal Characteristics of Aerosols from Collection 6 Aqua and Terra MODIS e-Deep Blue Products

    NASA Astrophysics Data System (ADS)

    Bettenhausen, C.; Hsu, N. Y. C.; Sayer, A. M.; Lee, J.; Carletta, N.

    2015-12-01

    Aerosols continue to attract a significant amount of attention from researchers worldwide due to their extensive effects on Earth's climate, ecology, public health, and even energy production. In order to truly understand these effects, a long, stable, and well-calibrated data record is required. Since 2000 and 2002, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites together with the e-Deep Blue aerosol retrieval algorithm have been providing such a data record. After a multi-year development effort, the production of both Aqua and Terra MODIS Collection 6 (C6) atmosphere products successfully completed earlier this year and the data was released to the public shortly thereafter. The C6 Deep Blue products (now enhanced Deep Blue or e-Deep Blue) have been significantly improved over the previous Collection 5.1 version. In this poster we provide an overview of the latest C6 e-Deep Blue products and the improvements implemented since the previous collection including coverage over dark surfaces and updates to the Terra calibration. Validation results utilizing Aerosol Robotic Network (AERONET) data are also summarized. We then use the C6 e-Deep Blue products from both Aqua and Terra to explore the spatial characteristics in addition to the seasonal and inter-annual variability of aerosols on both regional and global scales. We also use this as an opportunity to compare these results and investigate any differences found between the two instruments.

  3. Time-Dependent Response Versus Scan Angle for MODIS Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Sun, Junqiang; Xiong, Xiaoxiong; Angal, Amit; Chen, Hongda; Wu, Aisheng; Geng, Xu

    2014-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently operate onboard the National Aeronautics and Space Administration (NASA's) Terra and Aqua spacecraft, launched on December 18, 1999 and May 4, 2002, respectively. MODIS has 36 spectral bands, among which 20 are reflective solar bands (RSBs) covering a spectral range from 0.412 to 2.13 µm. The RSBs are calibrated on orbit using a solar diffuser (SD) and an SD stability monitor and with additional measurements from lunar observations via a space view (SV) port. Selected pseudo-invariant desert sites are also used to track the RSB on-orbit gain change, particularly for short-wavelength bands. MODIS views the Earth surface, SV, and the onboard calibrators using a two-sided scan mirror. The response versus scan angle (RVS) of the scan mirror was characterized prior to launch, and its changes are tracked using observations made at different angles of incidence from onboard SD, lunar, and Earth view (EV) measurements. These observations show that the optical properties of the scan mirror have experienced large wavelength-dependent degradation in both the visible and near infrared spectral regions. Algorithms have been developed to track the on-orbit RVS change using the calibrators and the selected desert sites. These algorithms have been applied to both Terra and Aqua MODIS Level 1B (L1B) to improve the EV data accuracy since L1B Collection 4, refined in Collection 5, and further improved in the latest Collection 6 (C6). In C6, two approaches have been used to derive the time-dependent RVS for MODIS RSB. The first approach relies on data collected from sensor onboard calibrators and mirror side ratios from EV observations. The second approach uses onboard calibrators and EV response trending from selected desert sites. This approach is mainly used for the bands with much larger changes in their time-dependent RVS, such as the Terra MODIS bands 1-4, 8, and 9 and the Aqua MODIS bands 8- and 9

  4. Modeling and Mapping Oyster Norovirus Outbreak Risks in Gulf of Mexico Using NASA MODIS Aqua Data

    NASA Astrophysics Data System (ADS)

    Deng, Z.; Wang, J.

    2015-12-01

    Norovirus is a highly infectious virus and the leading cause of foodborne disease outbreaks such as oyster norovirus outbreaks. Currently, there is no vaccine to prevent norovirus infection and no drug to treat it. This paper presents an integrated modeling and mapping framework for predicting the risk of norovirus outbreaks in oyster harvesting waters in the Northern Gulf of Mexico coast. The framework involves (1) the construction of three novel remote sensing algorithms for the retrieval of sea surface salinity, sea surface temperature, and gage height (tide level) using NASA MODIS Aqua data; (2) the development of probability-based Artificial Neural Network (ANN) model for the prediction of oyster norovirus outbreak risk, and (3) the application of the Local Indicators of Spatial Association (LISA) for mapping norovirus outbreak risks in oyster harvesting areas in the Northern Gulf of Mexico using the remotely sensed NASA data, retrieved data from the three remote sensing algorithms, and the ANN model predictions. The three remote sensing algorithms are able to correctly retrieve 94.1% of sea surface salinity, 94.0% of sea surface temperature, and 77.8% of gage height observed along the US coast, including the Pacific coast, the Gulf of Mexico coast, and the Atlantic coast. The gage height, temperature, and salinity are the three most important explanatory variables of the ANN model in terms of spatially distributed input variables. The ANN model is capable of hindcasting/predicting all oyster norovirus outbreaks occurred in oyster growing areas along the Gulf of Mexico coast where environmental data are available. The integrated modeling and mapping framework makes it possible to map daily risks of norovirus outbreaks in all oyster harvesting waters and particularly the oyster growing areas where no in-situ environmental data are available, greatly improving the safety of seafood and reducing outbreaks of foodborne disease.

  5. Monitoring ice break-up on the Mackenzie River, Canada, from MODIS Aqua and Terra observations

    NASA Astrophysics Data System (ADS)

    Muhammad, P.; Duguay, C. R.; Kang, K.

    2013-12-01

    Monitoring the response of river ice phenology to variability and changes in high-latitude climate conditions is critical for improving our understanding of northern hydrology and related impacts on geochemical and biological processes. Shorter ice cover duration, thinner ice, and earlier break-up also influence the winter road season, thereby influencing industrial development and the delivery of goods to northern communities. Increased upstream temperatures over the Mackenzie River Basin have caused shorter ice cover seasons, consequently changing the timing and severity of river ice flow in this high-latitude region. This study involves the analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 500-m snow products (Aqua and Terra), complemented with 250-m Level 1b data, to monitor ice cover during the break-up period on the Mackenzie River over the 2001-2013 period. Results from the analysis of 10 ice seasons (2003-2012) show that first day ice-off was observed between day of year (DY) 115-125 and ended between DY 145-155, resulting in average melt durations of about 30-40 days. Additional ice-on and ice-off days observed during 2003-2012 resulted from northern flowing entrained river ice that extended the break-up season until DY 155-163. Floating ice flowing northbound could therefore generate multiple periods of ice-cover and ice-free days at the same geographic location. During the ice break-up seasons from 2003-2012, ice melt was initiated by in situ melt over drainage basin (thermodynamic), especially between 61-62o N. However, ice break-up above the 62o N was more dynamically driven. In addition, ice jams were found to be largely controlled by river morphology.

  6. MODIS-Aqua detects Noctiluca scintillans and hotspots in the central Arabian Sea.

    PubMed

    Dwivedi, R; Priyaja, P; Rafeeq, M; Sudhakar, M

    2016-01-01

    Northern Arabian Sea is considered as an ecologically sensitive area as it experiences a massive upwelling and long-lasting algal bloom, Noctiluca scintillans (green tide) during summer and spring-winter, respectively. Diatom bloom is also found to be co-located with N. scintillans and both have an impact on ecology of the basin. In-house technique of detecting species of these blooms from Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua data was used to generate a time-series of images revealing their spatial distribution. A study of spatial-temporal variability of these blooms using satellite data expressed a cyclic pattern of their spread over a period of 13 years. An average distribution of the blooms for January-March period revealed a peak in 2015 and minimum in 2013. Subsequently, a time-series of phytoplankton species images were generated for these 2 years to study their inter-annual variability and the associated factors. Species images during active phase of the bloom (February) in 2015 indicated development of N. scintillans and diatom in the central Arabian Sea also, up to 12° N. This observation was substantiated with relevant oceanic parameters measured from the ship as well as satellite data and the same is highlight of the paper. While oxygen depletion and release of ammonia associated with N. scintillans are detrimental for waters on the western side; it is relatively less extreme and supports the entire food chain on the eastern side. In view of these contrasting eco-sensitive events, it is a matter of concern to identify biologically active persistent areas, hot spots, in order to study their ecology in detail. An ecological index, persistence of the bloom, was derived from the time-series of species images and it is another highlight of our study. PMID:26690080

  7. MODIS-Aqua detects Noctiluca scintillans and hotspots in the central Arabian Sea.

    PubMed

    Dwivedi, R; Priyaja, P; Rafeeq, M; Sudhakar, M

    2016-01-01

    Northern Arabian Sea is considered as an ecologically sensitive area as it experiences a massive upwelling and long-lasting algal bloom, Noctiluca scintillans (green tide) during summer and spring-winter, respectively. Diatom bloom is also found to be co-located with N. scintillans and both have an impact on ecology of the basin. In-house technique of detecting species of these blooms from Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua data was used to generate a time-series of images revealing their spatial distribution. A study of spatial-temporal variability of these blooms using satellite data expressed a cyclic pattern of their spread over a period of 13 years. An average distribution of the blooms for January-March period revealed a peak in 2015 and minimum in 2013. Subsequently, a time-series of phytoplankton species images were generated for these 2 years to study their inter-annual variability and the associated factors. Species images during active phase of the bloom (February) in 2015 indicated development of N. scintillans and diatom in the central Arabian Sea also, up to 12° N. This observation was substantiated with relevant oceanic parameters measured from the ship as well as satellite data and the same is highlight of the paper. While oxygen depletion and release of ammonia associated with N. scintillans are detrimental for waters on the western side; it is relatively less extreme and supports the entire food chain on the eastern side. In view of these contrasting eco-sensitive events, it is a matter of concern to identify biologically active persistent areas, hot spots, in order to study their ecology in detail. An ecological index, persistence of the bloom, was derived from the time-series of species images and it is another highlight of our study.

  8. Decadal changes of water properties in the Aral Sea observed by MODIS-Aqua

    NASA Astrophysics Data System (ADS)

    Shi, Wei; Wang, Menghua

    2015-07-01

    Twelve-year satellite observations between 2002 and 2013 from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the satellite Aqua are used to quantitatively assess the water property changes in the Aral Sea. The shortwave infrared (SWIR) atmospheric correction algorithm is required and used to derive normalized water-leaving radiance spectra nLw(λ) in the Aral Sea. We used radiance ratio nLw(555)/nLw(443) as a surrogate to characterize the spatial and temporal variations of chlorophyll-a (Chl-a) in the Aral Sea. Both seasonal variability and significant interannual changes were observed when the Aral Sea desiccated between 2002 and 2013. All three separated regions of the Aral Sea show increased nLw(555)/nLw(443) ratio (a surrogate for Chl-a) and the diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)) during the fall season. Of the three regions, the North Aral Sea has had the least interannual variability, while South-East (SE) Aral Sea experienced drastic changes. Waters in the SE Aral Sea are the most turbid with significantly higher Kd(490) than those in the other two subregions. Kd(490) gradually increased from ˜2 m-1 in 2002 to ˜3.5 m-1 after 2008 in the SE Aral Sea. In comparison, both radiance ratio nLw(555)/nLw(443) and Kd(490) were relatively stable for the North Aral Sea. In the South-West (SW) Aral Sea, however, nLw(555)/nLw(443) values reached peaks in the fall of 2007 and 2010. A possible link between the Aral Sea water property change and the regional climate variation is also discussed.

  9. Evaluation of MODIS surface reflectance products for wheat leaf area index (LAI) retrieval

    NASA Astrophysics Data System (ADS)

    Yi, Yonghong; Yang, Dawen; Huang, Jingfeng; Chen, Daoyi

    The accuracy of leaf area index (LAI) retrieval depends critically on the quality of the input reflectance. MODIS Collection 4 (C4) and Collection 5 (C5) land surface reflectance data are used for wheat LAI retrieval. Results are compared with in situ measurements. The uncertainty in the reflectance data of the two collections (C4 and C5) from both Terra and Aqua sensors is analyzed and its influence on LAI retrieval is discussed. The discrepancies of blue and near infrared reflectances between Terra and Aqua in the C5 data are less than the discrepancies between the sensors in the C4 data. For both Terra and Aqua, the C5 data have much lower blue reflectance than do the C4 data. This can be attributed to improvements in the atmospheric correction algorithm for the C5 data including cloud mask definition and aerosol retrieval. Using both empirical vegetation indices and inversion methods, the LAI is derived from the C4 and C5 surface reflectances. For daily C4 data, only Aqua Normalized difference water indices (NDWI) have significant correlations with the LAI (at a 99% confidence level); in contrast, for the daily C5 data, all the vegetation indices have significant correlations with the LAI. A three-layer neural network is used to invert a one-dimensional (1-D) radiative transfer model for LAI estimation. For the daily C4 data, the correlation between the modeled and measured LAIs is poor and the root mean square error (RMSE) is larger than 1.1; in comparison, the RMSE for the daily C5 data is 0.7. For both C4 and C5 collections, the LAI tends to be overestimated when the sensor is operated with a large view zenith angle in the backscattering direction. The error is either due to the mismatch between the measured reflectance and the modeled reflectance from the simple 1-D radiative transfer model in this direction or due to the assumption of a Lambertian surface in the MODIS atmospheric correction. Additionally, for both methods the results from the 8-day

  10. Sea ice properties in the Bohai Sea measured by MODIS-Aqua: 2. Study of sea ice seasonal and interannual variability

    NASA Astrophysics Data System (ADS)

    Shi, Wei; Wang, Menghua

    2012-07-01

    During the 2009-2010 winter, the Bohai Sea experienced its most severe sea ice event in four decades, which caused significant economic losses, affected marine transportation and fishery, and impacted the entire marine ecosystem in the region. Measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite from 2002 to 2010 and surface atmosphere temperature (SAT) data from the National Centers for Environmental Prediction (NCEP) are used to study and quantify the extreme sea ice event in the 2009-2010 winter and the interannual variability of the regional sea ice properties, as well as the relationship between sea ice and the climate variability in the Bohai Sea. The mean sea ice reflectance from MODIS-Aqua visible and near-infrared wavelengths are 9.33%, 13.26%, and 12.60% in the months of December 2009, January 2010, and February 2010, respectively, compared with the monthly average sea ice reflectance values (from 2002 to 2010) of 9.35%, 11.21%, and 11.41% in the same three winter months. The sea ice monthly average coverages are ~ 5427, ~ 27,414, and ~ 21,156 km2 in these three winter months. These values are significantly higher than the averages of monthly sea ice coverage of ~ 2735, ~ 11,119, and ~ 10,287 km2 in the Bohai Sea in December, January, and February between 2002 and 2010. Most of the sea ice coverage was located in the northern Bohai Sea. Both the intra-seasonal and interannual sea ice variability in the Bohai Sea is found to be related closely to SAT. The mechanism of anomalous SAT and intense sea ice severity are also discussed and attributed to large-scale climate changes due to the variability of the Arctic Oscillation (AO) and Siberian High (SH).

  11. On the Relative Stability of CERES Reflected Shortwave and MISR and MODIS Visible Radiance Measurements During the Terra Satellite Mission

    NASA Technical Reports Server (NTRS)

    Corbett, J. G.; Loeb, N. G.

    2015-01-01

    Fifteen years of visible, near-infrared, and broadband shortwave radiance measurements from Clouds and the Earth's Radiant Energy System (CERES), Multiangle Imaging Spectroradiometer (MISR), and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on board NASA's Terra satellite are analyzed in order to assess their long-term relative stability for climate purposes. A regression-based approach between CERES, MODIS, and MISR (An camera only) reflectances is used to calculate the bias between the different reflectances relative to a reference year. When compared to the CERES shortwave broadband reflectance, relative drift between the MISR narrowbands is within 1%/decade. Compared to the CERES shortwave reflectance, the MODIS narrowband reflectances show a relative drift of less than -1.33%/decade. When compared to MISR, the MODIS reflectances show a relative drift of between -0.36%/decade and -2.66%/decade. We show that the CERES Terra SW measurements are stable over the time period relative to CERES Aqua. Using this as evidence that CERES Terra may be absolutely stable, we suggest that the CERES, MISR, and MODIS instruments meet the radiometric stability goals for climate applications set out in Ohring et al. (2005).

  12. Evaluation of model simulated and MODIS-Aqua retrieved sea surface chlorophyll in the eastern Arabian Sea

    NASA Astrophysics Data System (ADS)

    Chakraborty, Kunal; Gupta, Anubhav; Lotliker, Aneesh A.; Tilstone, Gavin

    2016-11-01

    In this study we assess the accuracy of sea surface Chlorophyll-a (Chla) retrieved from satellite (MODIS-Aqua), using standard OC3M algorithm, and from a Regional Ocean Modelling System (ROMS) biophysical model against in situ data, measured in surface waters of the eastern Arabian Sea, from April 2009 to December 2012. MODIS-Aqua OC3M Chla concentrations showed a high correlation with the in situ data with slope close to unity and low root mean square error. In comparison, the ROMS model underestimated Chla, though the correlation was significant indicating that the model is capable of reproducing the trend in in situ Chla. Time Series trends in Chla were examined against wind driven Upwelling Indices (UIW) from April 2009 to December 2012 in north-eastern (Gujarat) and south-eastern (Kochi) coastal waters of the Arabian Sea. The annual peak in Chla along the Kochi coast during the summer monsoon was adequately captured by the model. It is well known that the peak in surface Chla along the Kochi and Gujarat coasts during the summer monsoon is the result of coastal upwelling, which the ROMS model was able to reproduce accurately. The maximum surface Chla along the Gujarat coast during the winter monsoon is due to convective mixing, which was also significantly captured by ROMS biophysical model. There was a lag of approximately one week between the maximum surface Chla and the peak in the Upwelling Index.

  13. Aerosol optical depth over central north Asia based on MODIS-Aqua data

    NASA Astrophysics Data System (ADS)

    Avgousta Foutsi, Athina; Korras Carraca, Marios Bruno; Matsoukas, Christos; Biskos, George

    2016-04-01

    Atmospheric aerosols, both natural and anthropogenic, can affect the regional and global climate through their direct, indirect, and semi-direct effects on the radiative energy budget of the Earth-atmosphere system. To quantify these effects it is important to determine the aerosol load, and an effective way to do that is by measuring the aerosol optical depth (AOD). The central Asia region (mainly the Caspian and Aral sea basins), the arid and semi-arid regions of Western China as well as Siberia are of great interest due to the significant natural sources of mineral aerosols originating from local deserts and biomass burning from wildfires in boreal forests. What is of particular interest in the region is the phenomenal shrinking and desertification of the Aral Sea that drives an intense salt and dust transport from the exposed sea-bed to the surrounding regions with important implications in regional air quality. Anthropogenic particles are also observed due to fossil-fuel combustion occurring mainly at oil refineries in the Caspian Sea basin. Here we investigate the spatial and temporal variability of the AOD at 550 nm over central Asia, Siberia and western China, in the region located between 35° N - 65° N and 45° E - 110° E. For our analysis we use Level-3 daily MODIS - Aqua Dark Target - Deep Blue combined product, from the latest collection (006), available in a 1°×1° resolution (ca. 100 km × 100 km) over the period 2002-2014. Our results indicate a significant spatial variability of the aerosol load over the study region. The highest AODs are observed over the Aral Sea year-round, with extreme values reaching 2.1 during July. In the rest of our study region a clear seasonal cycle with highest AOD values (up to 1.2 over the Taklamakan Desert) during spring and summer is observed. The arid parts of central north Asia are characterized by larger aerosol loads during spring, lower but still high AOD in summer and much lower values in autumn and spring

  14. Land Surface Albedo from MERIS Reflectances Using MODIS Directional Factors

    NASA Technical Reports Server (NTRS)

    Schaaf, Crystal L. B.; Gao, Feng; Strahler, Alan H.

    2004-01-01

    MERIS Level 2 surface reflectance products are now available to the scientific community. This paper demonstrates the production of MERIS-derived surface albedo and Nadir Bidirectional Reflectance Distribution Function (BRDF) adjusted reflectances by coupling the MERIS data with MODIS BRDF products. Initial efforts rely on the specification of surface anisotropy as provided by the global MODIS BRDF product for a first guess of the shape of the BRDF and then make use all of the coincidently available, partially atmospherically corrected, cloud cleared, MERIS observations to generate MERIS-derived BRDF and surface albedo quantities for each location. Comparisons between MODIS (aerosol-corrected) and MERIS (not-yet aerosol-corrected) surface values from April and May 2003 are also presented for case studies in Spain and California as well as preliminary comparisons with field data from the Devil's Rock Surfrad/BSRN site.

  15. Ocean Color Data at the Goddard Earth Sciences (GES) DAAC: CZCS, SeaWiFS, OCTS, MODIS-Terra, MODIS-Aqua

    NASA Technical Reports Server (NTRS)

    2002-01-01

    The Goddard Earth Sciences Distributed Active Archive Center (DAAC) is the designated archive for all of the ocean color data produced by NASA satellite missions. The DAAC is a long-term, high volume, secure repository for many different kinds of environmental data. With respect to ocean color, the Goddard DAAC holds all the data obtained during the eight-year mission of the Coastal Zone Color Scanner (CZCS). The DAAC is currently receiving data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and the MODIS-Terra instrument. The DAAC recently received reformatted data from the Ocean Color and Temperature Scanner (OCTS) and will also archive MODIS-Aqua Ocean products. In addition to its archive and distribution services, the Goddard DAAC strives to improve data access, ease-of-use, and data applicability for a broad spectrum of customers. The DAAC's data support teams practice dual roles, both insuring the integrity of the DAAC data archive and serving the user community with answers to user inquiries, online and print documentation, and customized data services.

  16. Characterization of turbidity in Florida's Lake Okeechobee and Caloosahatchee and St. Lucie estuaries using MODIS-Aqua measurements.

    PubMed

    Wang, Menghua; Nim, Carl J; Son, Seunghyun; Shi, Wei

    2012-10-15

    This paper describes the use of ocean color remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to characterize turbidity in Lake Okeechobee and its primary drainage basins, the Caloosahatchee and St. Lucie estuaries from 2002 to 2010. Drainage modification and agricultural development in southern Florida transport sediments and nutrients from watershed agricultural areas to Lake Okeechobee. As a result of development around Lake Okeechobee and the estuaries that are connected to Lake Okeechobee, estuarine conditions have also been adversely impacted, resulting in salinity and nutrient fluctuations. The measurement of water turbidity in lacustrine and estuarine ecosystems allows researchers to understand important factors such as light limitation and the potential release of nutrients from re-suspended sediments. Based on a strong correlation between water turbidity and normalized water-leaving radiance at the near-infrared (NIR) band (nL(w)(869)), a new satellite water turbidity algorithm has been developed for Lake Okeechobee. This study has shown important applications with satellite-measured nL(w)(869) data for water quality monitoring and measurements for turbid inland lakes. MODIS-Aqua-measured water property data are derived using the shortwave infrared (SWIR)-based atmospheric correction algorithm in order to remotely obtain synoptic turbidity data in Lake Okeechobee and normalized water-leaving radiance using the red band (nL(w)(645)) in the Caloosahatchee and St. Lucie estuaries. We found varied, but distinct seasonal, spatial, and event driven turbidity trends in Lake Okeechobee and the Caloosahatchee and St. Lucie estuary regions. Wind waves and hurricanes have the largest influence on turbidity trends in Lake Okeechobee, while tides, currents, wind waves, and hurricanes influence the Caloosahatchee and St. Lucie estuarine areas.

  17. Characterization of turbidity in Florida's Lake Okeechobee and Caloosahatchee and St. Lucie estuaries using MODIS-Aqua measurements.

    PubMed

    Wang, Menghua; Nim, Carl J; Son, Seunghyun; Shi, Wei

    2012-10-15

    This paper describes the use of ocean color remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to characterize turbidity in Lake Okeechobee and its primary drainage basins, the Caloosahatchee and St. Lucie estuaries from 2002 to 2010. Drainage modification and agricultural development in southern Florida transport sediments and nutrients from watershed agricultural areas to Lake Okeechobee. As a result of development around Lake Okeechobee and the estuaries that are connected to Lake Okeechobee, estuarine conditions have also been adversely impacted, resulting in salinity and nutrient fluctuations. The measurement of water turbidity in lacustrine and estuarine ecosystems allows researchers to understand important factors such as light limitation and the potential release of nutrients from re-suspended sediments. Based on a strong correlation between water turbidity and normalized water-leaving radiance at the near-infrared (NIR) band (nL(w)(869)), a new satellite water turbidity algorithm has been developed for Lake Okeechobee. This study has shown important applications with satellite-measured nL(w)(869) data for water quality monitoring and measurements for turbid inland lakes. MODIS-Aqua-measured water property data are derived using the shortwave infrared (SWIR)-based atmospheric correction algorithm in order to remotely obtain synoptic turbidity data in Lake Okeechobee and normalized water-leaving radiance using the red band (nL(w)(645)) in the Caloosahatchee and St. Lucie estuaries. We found varied, but distinct seasonal, spatial, and event driven turbidity trends in Lake Okeechobee and the Caloosahatchee and St. Lucie estuary regions. Wind waves and hurricanes have the largest influence on turbidity trends in Lake Okeechobee, while tides, currents, wind waves, and hurricanes influence the Caloosahatchee and St. Lucie estuarine areas. PMID:22858282

  18. Seasonal nitrate algorithms for nitrate retrieval using OCEANSAT-2 and MODIS-AQUA satellite data.

    PubMed

    Durairaj, Poornima; Sarangi, Ranjit Kumar; Ramalingam, Shanthi; Thirunavukarassu, Thangaradjou; Chauhan, Prakash

    2015-04-01

    In situ datasets of nitrate, sea surface temperature (SST), and chlorophyll a (chl a) collected during the monthly coastal samplings and organized cruises along the Tamilnadu and Andhra Pradesh coast between 2009 and 2013 were used to develop seasonal nitrate algorithms. The nitrate algorithms have been built up based on the three-dimensional regressions between SST, chl a, and nitrate in situ data using linear, Gaussian, Lorentzian, and paraboloid function fittings. Among these four functions, paraboloid was found to be better with the highest co-efficient of determination (postmonsoon: R2=0.711, n=357; summer: R2=0.635, n=302; premonsoon: R2=0.829, n=249; and monsoon: R2=0.692, n=272) for all seasons. Based on these fittings, seasonal nitrate images were generated using the concurrent satellite data of SST from Moderate Resolution Imaging Spectroradiometer (MODIS) and chlorophyll (chl) from Ocean Color Monitor (OCM-2) and MODIS. The best retrieval of modeled nitrate (R2=0.527, root mean square error (RMSE)=3.72, and mean normalized bias (MNB)=0.821) was observed for the postmonsoon season due to the better retrieval of both SST MODIS (28 February 2012, R2=0.651, RMSE=2.037, and MNB=0.068) and chl OCM-2 (R2=0.534, RMSE=0.317, and MNB=0.27). Present results confirm that the chl OCM-2 and SST MODIS retrieve nitrate well than the MODIS-derived chl and SST largely due to the better retrieval of chl by OCM-2 than MODIS.

  19. Quality assessment of Landsat surface reflectance products using MODIS data

    NASA Astrophysics Data System (ADS)

    Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric F.; Masek, Jeffrey G.; Townshend, John R.

    2012-01-01

    Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat

  20. Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data

    NASA Technical Reports Server (NTRS)

    Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric; Masek, Jeffrey G.; Townshend, John R.

    2012-01-01

    Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat

  1. Constraining canopy biophysical simulations with daily MODIS reflectance data ensuring pixel-target adequacy

    NASA Astrophysics Data System (ADS)

    Drewry, D.; Duveiller, G.

    2013-12-01

    Aqua platforms. As a whiskbroom imaging instrument, MODIS has a complex viewing geometry which affects its spatial response, i.e. the way the electromagnetic radiation reflected from the surface is ultimately encoded in the remotely-sensed image. A model of this spatial response is used here to ensure that the footprint of the satellite observations matches adequately with the coupled model simulations of the target fields. The relationship between the purity of the remote sensing observation, with respect to the target field, and the quality of the biophysical variable inversion is also investigated.

  2. Comparison of C5 and C6 Aqua-MODIS Dark Target Aerosol Validation

    NASA Technical Reports Server (NTRS)

    Munchak, Leigh A.; Levy, Robert C.; Mattoo, Shana

    2014-01-01

    We compare C5 and C6 validation to compare the C6 10 km aerosol product against the well validated and trusted aerosol product on global and regional scales. Only the 10 km aerosol product is evaluated in this study, validation of the new C6 3 km aerosol product still needs to be performed. Not all of the time series has processed yet for C5 or C6, and the years processed for the 2 products is not exactly the same (this work is preliminary!). To reduce the impact of outlier observations, MODIS is spatially averaged within 27.5 km of the AERONET site, and AERONET is temporatally averaged within 30 minutes of the MODIS overpass time. Only high quality (QA = 3 over land, QA greater than 0 over ocean) pixels are included in the mean.

  3. Climatology and trends of aerosol optical depth over the Mediterranean basin during the last 12years (2002-2014) based on Collection 006 MODIS-Aqua data.

    PubMed

    Floutsi, A A; Korras-Carraca, M B; Matsoukas, C; Hatzianastassiou, N; Biskos, G

    2016-05-01

    The Mediterranean basin is a region of particular interest for studying atmospheric aerosols due to the large variety of air masses it receives, and its sensitivity to climate change. In this study we use the newest collection (C006) of aerosol optical depth from MODIS-Aqua, from which we also derived the fine-mode fraction and Ångström exponent over the last 12years (i.e., from 2002 to 2014), providing the longest analyzed dataset for this region. The long-term regional optical depth average is 0.20±0.05, with the indicated uncertainty reflecting the inter-annual variability. Overall, the aerosol optical depth exhibits a south-to-north decreasing gradient and an average decreasing trend of 0.0030 per year (19% total decrease over the study period). The correlation between the reported AOD observations with measurements from the ground AERONET stations is high (R=0.76-0.80 depending on the wavelength), with the MODIS-Aqua data being slightly overestimated. Both fine-fraction and Ångström exponent data highlight the dominance of anthropogenic aerosols over the northern, and of desert aerosols over the southern part of the region. Clear intrusions of desert dust over the Eastern Mediterranean are observed principally in spring, and in some cases in winter. Dust intrusions dominate the Western Mediterranean in the summer (and sometimes in autumn), whereas anthropogenic aerosols dominate the sub-region of the Black Sea in all seasons but especially during summer. Fine-mode optical depth is found to decrease over almost all areas of the study region during the 12-year period, marking the decreasing contribution of anthropogenic particulate matter emissions over the study area. Coarse-mode aerosol load also exhibits an overall decreasing trend. However, its decrease is smaller than that of fine aerosols and not as uniformly distributed, underlining that the overall decrease in the region arises mainly from reduced anthropogenic emissions. PMID:26878641

  4. A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Gupta, Pawan; Levy, Robert C.; Mattoo, Shana; Remer, Lorraine A.; Munchak, Leigh A.

    2016-07-01

    The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard the two Earth Observing System (EOS) satellites Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air-quality applications. However, the application of MODIS aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the MODIS Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.

  5. Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Remer, Lorraine A.

    2006-01-01

    Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Instruments that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that measure in the visible, near-infrared, and thermal infrared. The availability of thermal channels to enhance detection of cloud when estimating aerosol properties is an important improvement. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud particle effective radius) and highlight the global/regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective particle radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles (in cloud free regions) that are currently available from space-based observations, and show the latitudinal distribution of aerosol optical properties over both land and ocean surfaces.

  6. Contrail radiative forcing over the Northern Hemisphere from 2006 Aqua MODIS data

    NASA Astrophysics Data System (ADS)

    Spangenberg, Douglas A.; Minnis, Patrick; Bedka, Sarah T.; Palikonda, Rabindra; Duda, David P.; Rose, Fred G.

    2013-02-01

    Abstract Radiative forcing due to linear-shaped jet contrails is calculated over the Northern Hemisphere for four seasonal months using 2006 <span class="hlt">Aqua</span> Moderate-resolution Imaging Spectroradiometer cloud and contrail property retrieval data in a radiative transfer model. The 4 month mean shortwave, longwave, and net radiative forcings normalized to 100% contrail cover are -5.7, 14.2, and 8.5 Wm-2. Mean total net forcing over the northern half of the globe varies from 9.1 mW m-2 during October to 12.1 mW m-2 in January and is only representative at 01:30 and 13:30 LT in nonpolar regions. In some dense flight traffic corridors, the mean net forcing approaches 80 mW m-2. Scaling the 4 month average of 10.6 mW m-2 to the Southern Hemisphere air traffic yields global mean net forcing of 5.7 mW m-2, which is smaller than most model estimates. Nighttime net forcing is 3.6 times greater than during daytime, when net forcing is greatest over low clouds. Effects from contrail cirrus clouds that evolve from linear contrails are not considered in these results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070017450','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070017450"><span id="translatedtitle">A New Algorithm for Retrieving Aerosol Properties Over Land from <span class="hlt">MODIS</span> Spectral <span class="hlt">Reflectance</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Levy, Robert C.; Remer, Lorraine A.; Mattoo, Shana; Vermote, Eric F.; Kaufman, Yoram J.</p> <p>2006-01-01</p> <p>Since first light in early 2000, operational global quantitative retrievals of aerosol properties over land have been made from <span class="hlt">MODIS</span> observed spectral <span class="hlt">reflectance</span>. These products have been continuously evaluated and validated, and opportunities for improvements have been noted. We have replaced the original algorithm by improving surface <span class="hlt">reflectance</span> assumptions, the aerosol model optical properties and the radiative transfer code used to create the lookup tables. The new algorithm (known as Version 5.2 or V5.2) performs a simultaneous inversion of two visible (0.47 and 0.66 micron) and one shortwave-IR (2.12 micron) channel, making use of the coarse aerosol information content contained in the 2.12 micron channel. Inversion of the three channels yields three nearly independent parameters, the aerosol optical depth (tau) at 0.55 micron, the non-dust or fine weighting (eta) and the surface <span class="hlt">reflectance</span> at 2.12 micron. Finally, retrievals of small magnitude negative tau values (down to -0.05) are considered valid, thus normalizing the statistics of tau in near zero tau conditions. On a 'test bed' of 6300 granules from Terra and <span class="hlt">Aqua</span>, the products from V5.2 show marked improvement over those from the previous versions, including much improved retrievals of tau, where the <span class="hlt">MODIS</span>/AERONET tau (at 0.55 micron) regression has an equation of: y = 1.01+0.03, R = 0.90. Mean tau for the test bed is reduced from 0.28 to 0.21.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015718','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015718"><span id="translatedtitle">Accuracy Assessment of <span class="hlt">Aqua-MODIS</span> Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.</p> <p>2012-01-01</p> <p>Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from <span class="hlt">MODIS</span> aboard <span class="hlt">Aqua</span> satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the <span class="hlt">MODIS</span> Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the <span class="hlt">MODIS</span> AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the <span class="hlt">MODIS</span> AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the <span class="hlt">MODIS</span> Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the <span class="hlt">MODIS</span> Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JARS...10b4004C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JARS...10b4004C"><span id="translatedtitle">Alternative method of on-orbit response-versus-scan-angle characterization for <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Hongda; Xiong, Xiaoxiong; Angal, Amit; Geng, Xu; Wu, Aisheng</p> <p>2016-04-01</p> <p>The moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) has 20 <span class="hlt">reflective</span> solar bands (RSB), covering a spectral range from 0.41 to 2.2 μm, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the <span class="hlt">reflectance</span> of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's <span class="hlt">reflectance</span> over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the <span class="hlt">MODIS</span> characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160008400&hterms=solar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsolar','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160008400&hterms=solar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsolar"><span id="translatedtitle">Alternative Method of On-Orbit Response-Versus-Scan-Angle Characterization for <span class="hlt">MODIS</span> <span class="hlt">Reflective</span> Solar Bands</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chen, Hongda; Xiong, Xiaoxiong; Angal, Amit; Geng, Xu; Wu, Aisheng</p> <p>2016-01-01</p> <p>The moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) has 20 <span class="hlt">reflective</span> solar bands (RSB), covering a spectral range from 0.41 to 2.2 microns, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the <span class="hlt">reflectance</span> of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's <span class="hlt">reflectance</span> over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the <span class="hlt">MODIS</span> characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A11L..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A11L..06S"><span id="translatedtitle">Expanding the Estimation of Surface PM2.5 from <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> Aerosol Optical Depth in the EPA's AirNow Satellite Data Processor to Suomi NPP VIIRS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Szykman, J.; Kondragunta, S.; Zhang, H.; Dickerson, P.; van Donkelaar, A.; Martin, R. V.; Pasch, A. N.; White, J. E.; DeWinter, J. L.; Zahn, P. H.; Dye, T. S.; Haderman, M. D.</p> <p>2012-12-01</p> <p>The U.S. Environmental Protection Agency's (EPA) Air Quality Index (AQI) relies on hourly measurements of ground-based surface PM2.5 (particles smaller than 2.5 μm in median diameter) to develop daily AQI index maps. The EPA is improving the accuracy of AQI information and extending its coverage for reporting to the public by incorporating National Aeronautics and Space Administration (NASA) satellite-derived surface PM2.5 concentrations into daily AQI maps. The additional coverage will provide air quality information in regions without dense monitoring networks. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average <span class="hlt">Aqua</span> and Terra MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aerosol optical depth (AOD) in near real-time over the United States. The algorithm to derive surface PM2.5 from <span class="hlt">MODIS</span> AOD relies on linear relationships between AOD and PM2.5 generated from multi-year GEOS-Chem model simulations (van Donkelaar et al., 2012). Parameters from the regression equation (slopes and intercepts) are saved in a lookup table (LUT) with 4 km spatial resolution for each day of a given year. To improve data accuracy and continuity, a filter is applied to remove <span class="hlt">MODIS</span> AOD with low accuracy (e.g., over bright surfaces) and an inverse distance weighted average is applied to fill in gaps created by cloud coverage. Daily surface PM2.5 estimates and their uncertainties are generated at the National Oceanic and Atmospheric Administration (NOAA) using the van Donkelaar et al. algorithm and near real-time <span class="hlt">MODIS</span> AOD products from Terra and <span class="hlt">Aqua</span> and are provided to the EPA through its Infusing satellite Data into Environmental Applications (IDEA) website. The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on October 28, 2011, and similar to <span class="hlt">MODIS</span>, provides AOD products for real-time applications. NOAA plans to explore the value of VIIRS AOD products to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.A13F..05M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.A13F..05M"><span id="translatedtitle">Patterns and connections between aerosols, clouds and vegetation in the Amazon as seen by the twin <span class="hlt">MODIS</span> sensors aboard Terra and <span class="hlt">Aqua</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meskhidze, N.; Negrón Juárez, R.; Remer, L.; Platnick, S.; Aiyyer, A.</p> <p>2007-12-01</p> <p>In this study, twin Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors aboard NASA's Terra and <span class="hlt">Aqua</span> satellites are used for characterization of cloud development and identification of processes affecting cloud formation. We find that much of the development of microphysical properties of water clouds over the Brazilian Legal Amazon can be characterized by the simple difference between those properties observed at the two times of <span class="hlt">MODIS</span> overpass, only 3 hours apart. The time window is small enough that observed differences in cloud properties are primarily associated with the local events; therefore, it is ideal for exploring the effects of plant transpiration, biomass burning and Secondary Organic Aerosol (SOA) formation on regional cloud properties. In this region we find that the effective cloud droplet radius observed in the afternoon by <span class="hlt">Aqua-MODIS</span> is systematically higher than the effective radii observed in the morning by Terra-<span class="hlt">MODIS</span>. The difference corresponds to the invigoration of convection in the afternoon with the corresponding growth of droplet size. The monthly mean difference is 1 to 2 um, depending on season, but the overall pattern of the difference prevails throughout the Amazon, is repeated over other tropical rain forest regions globally, and is strikingly different from other types of cloud systems around the globe. Furthermore, we find that the effective radius difference found in the Amazon is inversely correlated to measures of evapotranspiration and all-sky solar radiation at the surface, but is not well-correlated to precipitation. The picture that emerges is a complex one that intertwines a light- limited forest, aerosols (both biogenic and anthropogenic) and cloud development.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160012486&hterms=surface&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsurface','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160012486&hterms=surface&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsurface"><span id="translatedtitle">Impact of Spatial Sampling on Continuity of <span class="hlt">MODIS</span>-VIIRS Land Surface <span class="hlt">Reflectance</span> Products: A Simulation Approach</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pahlevan, Nima; Sarkar, Sudipta; Devadiga, Sadashiva; Wolfe, Robert E.; Roman, Miguel; Vermote, Eric; Lin, Guoqing; Xiong, Xiaoxiong</p> <p>2016-01-01</p> <p>With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage <span class="hlt">MODIS</span> instruments onboard the National Aeronautics and Space Administrations Terra and <span class="hlt">Aqua</span> satellites. In this paper, we aim at quantifying the consistency of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface <span class="hlt">Reflectance</span> (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional <span class="hlt">reflectance</span> distribution function, the <span class="hlt">MODIS</span> and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface <span class="hlt">reflectance</span> at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and <span class="hlt">MODIS</span> footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1211733Z&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1211733Z&link_type=ABSTRACT"><span id="translatedtitle">A better understanding of cloud optical thickness derived from the passive sensors <span class="hlt">MODIS/AQUA</span> and POLDER/PARASOL in the A-train constellation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, S.; Cornet, C.; Parol, F.; Riedi, J.; Thieuleux, F.</p> <p>2012-05-01</p> <p>Cloud optical thickness (COT) is one of the most important parameter for the characterization of cloud in the Earth radiative budget. Its retrieval strongly depends on instrument characteristics and on many cloud and environment factors. Using coincident observations from POLDER/PARASOL and <span class="hlt">MODIS/AQUA</span> in the A-train constellation, geographical distributions and seasonal changes of COT are presented, in good agreement with general cloud climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial resolution, cloud inhomogeneity and microphysical assumptions are also discussed. Comparisons of COT derived from POLDER and <span class="hlt">MODIS</span> illustrate that as the primary factor, the sensor spatial resolution impacts COT retrievals and statistics through both cloud detection and sub-pixel cloud inhomogeneity sensitivity. The uncertainties associated to cloud microphysics assumptions, namely cloud phase, particle size and shape, also impact significantly COT retrievals. For clouds with unambiguous cloud phase, strong correlations exist between the two COTs, with <span class="hlt">MODIS</span> values comparable to POLDER ones for liquid clouds and <span class="hlt">MODIS</span> values larger than POLDER ones for ice clouds. The large differences observed in ice phase cases are due to the use of different microphysical models in the two retrieval schemes. In cases when the two sensors disagree on cloud phase decision, COT retrieved assuming liquid phase are systematically larger. The angular biases related to specific observation geometries are also quantified and discussed in particular based on POLDER observations. Those exhibit a clear increase of COT with decreasing sun elevation and a decrease of COT in forward scattering directions due to sub-pixel inhomogeneities and shadowing effects, this especially for lower sun. It also demonstrates unrealistic COT variations in the rainbow and backward directions due to inappropriate cloud optical properties representation and an important increase of COT in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120010478&hterms=snow&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsnow','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120010478&hterms=snow&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsnow"><span id="translatedtitle">An Algorithm for the Retrieval of 30-m Snow-Free Albedo from Landsat Surface <span class="hlt">Reflectance</span> and <span class="hlt">MODIS</span> BRDF</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.</p> <p>2011-01-01</p> <p>We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface <span class="hlt">reflectance</span> and anisotropy information from concurrent <span class="hlt">MODIS</span> 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day <span class="hlt">MODIS</span> albedo produced every 8-days from <span class="hlt">MODIS</span> on Terra and <span class="hlt">Aqua</span> (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.youtube.com/watch?v=P0uVV40Y2Pc','SCIGOVIMAGE-NASA'); return false;" href="http://www.youtube.com/watch?v=P0uVV40Y2Pc"><span id="translatedtitle"><span class="hlt">Aqua</span> satellite orbiting the Earth</span></a></p> <p><a target="_blank" href="http://www.nasa.gov/multimedia/videogallery/index.html">NASA Video Gallery</a></p> <p></p> <p></p> <p>This animation shows the <span class="hlt">Aqua</span> satellite orbiting the Earth on August 27, 2005 by revealing <span class="hlt">MODIS</span> true-color imagery for that day. This animation is on a cartesian map projection, so the satellite w...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023376','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023376"><span id="translatedtitle"><span class="hlt">MODIS</span> Radiometric Calibration and Uncertainty Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Chiang, Vincent; Sun, Junqiang; Wu, Aisheng</p> <p>2011-01-01</p> <p>Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have collected more than II and 9 years of datasets for comprehensive studies of the Earth's land, ocean, and atmospheric properties. <span class="hlt">MODIS</span> observations are made in 36 spectral bands: 20 <span class="hlt">reflective</span> solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, <span class="hlt">MODIS</span> was developed with very stringent calibration and uncertainty requirements. As a result, <span class="hlt">MODIS</span> was designed and built with a set of state of the art on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated if necessary. In terms of its calibration traceability, <span class="hlt">MODIS</span> RSB calibration is <span class="hlt">reflectance</span> based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of <span class="hlt">MODIS</span> calibration methodologies and discusses details of its on-orbit calibration uncertainties. It assesses uncertainty contributions from individual components and differences between Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> due to their design characteristics and on-orbit periormance. Also discussed in this paper is the use of <span class="hlt">MODIS</span> LIB uncertainty index CUI) product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15..705G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15..705G"><span id="translatedtitle">Inter-annual variability of aerosol optical depth over the tropical Atlantic Ocean based on <span class="hlt">MODIS-Aqua</span> observations over the period 2002-2012</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gkikas, Antonis; Hatzianastassiou, Nikolaos</p> <p>2013-04-01</p> <p>The tropical Atlantic Ocean is affected by dust and biomass burning aerosol loads transported from the western parts of the Saharan desert and the sub-Sahel regions, respectively. The spatial and temporal patterns of this transport are determined by the aerosol emission rates, their deposition (wet and dry), by the latitudinal shift of the Intertropical Convergence Zone (ITCZ) and the prevailing wind fields. More specifically, in summer, Saharan dust aerosols are transported towards the Atlantic Ocean, even reaching the Gulf of Mexico, while in winter the Atlantic Ocean transport takes place in more southern latitudes, near the equator, sometimes reaching the northern parts of South America. In the later case, dust is mixed with biomass burning aerosols originating from agricultural activities in the sub-Sahel, associated with prevailing north-easterly airflow (Harmattan winds). Satellite observations are the appropriate tool for describing this African aerosol export, which is important to atmospheric, oceanic and climate processes, offering the advantage of complete spatial coverage. In the present study, we use satellite measurements of aerosol optical depth at 550nm (AOD550nm), on a daily and monthly basis, derived from <span class="hlt">MODIS-Aqua</span> platform, at 1ox1o spatial resolution (Level 3), for the period 2002-2012. The primary objective is to determine the pixel-level and regional mean anomalies of AOD550nm over the entire study period. The regime of the anomalies of African export is interpreted in relation to the aerosol source areas, precipitation, wind patterns and temporal variability of the North Atlantic Oscillation Index (NAOI). In order to ensure availability of AOD over the Sahara desert, <span class="hlt">MODIS-Aqua</span> Deep Blue products are also used. As for precipitation, Global Precipitation Climatology Project (GPCP) data at 2.5ox2.5o are used. The wind fields are taken from the National Center for Environmental Prediction (NCEP). Apart from the regime of African aerosol export</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=328370','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=328370"><span id="translatedtitle">Compositing <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> 250m daily surface <span class="hlt">reflectance</span> data sets for vegetation monitoring</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Remote sensing based vegetation Indices have been proven valuable in providing a spatially complete view of crop’s vegetation condition, which also manifests the impact of the disastrous events such as massive flood and drought. VegScape, a web GIS application for crop vegetation condition monitorin...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A11G0120K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A11G0120K"><span id="translatedtitle">Long-term trend of aerosol optical depth derived from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> using linear regression and ensemble empirical mode decomposition over East Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>KIM, J.</p> <p>2015-12-01</p> <p>Aerosol has played an important role in air quality for short term and climate change for long term. Especially, it is important to understand how aerosol optical depth (AOD) has changed to date for the prognosis of future atmospheric state and radiation budget which are related to human life. In this study, the trend of AOD at 550 nm from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> (MYD08) was estimated for 10 years from 2004 to 2014 using linear regression method and ensemble empirical mode decomposition method (EEMD). Search region was selected to East Asia [18.5°N-51.5°N, 85.5°E-150.5°E] which is considered to be of great interest in emission source. The result of linear regression shows remarkably increasing trend in North and East China including Sanjiang, Hailun, Beijing, Beijing forest and Jinozhou Bay, than rather downward trend in other neighboring regions. Actually, however, AOD has seasonality itself and its trend is also affected by external source consistently, so non-linear trend analysis was conducted to analyze the changing tendency of AOD trends. Consequently, secular trends of AOD defined by EEMD showed almost similar values over the entire region, but their shapes over time are quite different with those of linear regression. Here, AOD linear trend in Beijing has monotonically increased [0.03% yr-1] since 2004, but its non-linear trend shows that initial increasing trend has alleviated and even turned into downward trend from about 2010. Lastly, the validation of <span class="hlt">MODIS</span> AOD with AErosol RObotic NETwork (AERONET) was conducted additionally which showed fairly good agreement with those of AERONET (R=0.901, RMSE=0.226, MAE=0.031, MBE=-0.001).</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_4 --> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013366','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013366"><span id="translatedtitle">Multitemporal Cross-Calibration of the Terra <span class="hlt">MODIS</span> and Landsat 7 ETM+ <span class="hlt">Reflective</span> Solar Bands</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Changler, Gyanesh; Choi, Taeyoyung</p> <p>2013-01-01</p> <p>In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between <span class="hlt">MODIS</span> and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) <span class="hlt">reflectance</span> due to surface and atmospheric bidirectional <span class="hlt">reflectance</span> distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA <span class="hlt">reflectance</span> to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding <span class="hlt">MODIS</span> and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all <span class="hlt">MODIS</span> and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A <span class="hlt">MODIS</span> split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the <span class="hlt">MODIS</span> precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with <span class="hlt">MODIS</span> band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 <span class="hlt">MODIS</span> processing.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040121164&hterms=Xiao&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DXiao','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040121164&hterms=Xiao&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DXiao"><span id="translatedtitle">Polarization Modeling of the <span class="hlt">MODIS</span> Instrument</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Waluschka, Eugene; Xiong, Xiao-Xiong; Esaias, Wayne E.; Voss, Kenneth; Souaidia, Nordine; Pellicori, Samuel; Moyer, David; Guenther, Bruce; Barnes, William</p> <p>2004-01-01</p> <p>Sunlight <span class="hlt">reflected</span> from the earth is, to a certain extent, polarized. Radiometers, such as the <span class="hlt">MODIS</span> instrument on board the TERRA and <span class="hlt">AQUA</span> spacecraft, are to a certain extent polarizers. Accurate radiometric measurements must take into account both the polarization state of the scene and the polarization sensitivity of the measuring instrument. The measured polarization characteristics of the <span class="hlt">MODIS</span> instruments are contained in various radiometric models. Continued use of these radiometric math models, over a number of years, have shown where these models can be improved. The current <span class="hlt">MODIS</span> polarization modeling effort is discussed in the context and limitations of past modeling efforts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011SPIE.8175E..02P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011SPIE.8175E..02P"><span id="translatedtitle">Sea surface temperature and ocean colour (<span class="hlt">MODIS/AQUA</span>) space and time variability in Indonesian Sea coral reef systems from 2002 to 2011</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Polónia, A. R.; Figueiredo, M.; Cleary, D. F. R.; de Voogd, N. J.; Martins, A.</p> <p>2011-11-01</p> <p>Presently, there are already Indonesian coral reefs experiencing massive destruction caused by anthropogenic localscale sources (sedimentation, eutrophication) and/or natural climatic global-scale sources (temperature) which can inflict acute and/or chronic impacts on these ecosystems. This study was carried out with the aim of identifying possible sources of impact in coral reef systems associated with two of the most populated Indonesian cities (Makassar and Jakarta). <span class="hlt">MODIS/AQUA</span> satellite-derived Ocean Colour (Chl a in mg m-3) and Sea Surface Temperature (SST in °C) data were used for the 2002-2011 period. These were related with large-scale atmospheric climatic indices, namely the Southern Oscillation Index (SOI), the Dipole Mode Index (DMI), and the North Atlantic Oscillation Index (NAOI). Beyond the expected influence of the El Niño Index over the Indonesian region, we present first evidence of the significant influence of the NAOI in Indonesian ecosystems. The results show strong seasonal correlation between the NAOI and two key parameters for the coral reef health: chlorophyll a (at Jakarta) and SST (at Makassar). During the dry season, and especially over the Spermonde coral reef system, a seasonal SST uptrend was observed culminating in the first bleaching event registered in this area during the hottest year (2010) since 2002.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130014484','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130014484"><span id="translatedtitle">Comparison Between NPP-VIIRS Aerosol Data Products and the <span class="hlt">MODIS</span> <span class="hlt">AQUA</span> Deep Blue Collection 6 Dataset Over Land</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sayer, Andrew M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Kondragunta, S.</p> <p>2013-01-01</p> <p>Aerosols are small particles suspended in the atmosphere and have a variety of natural and man-made sources. Knowledge of aerosol optical depth (AOD), which is a measure of the amount of aerosol in the atmosphere, and its change over time, is important for multiple reasons. These include climate change, air quality (pollution) monitoring, monitoring hazards such as dust storms and volcanic ash, monitoring smoke from biomass burning, determining potential energy yields from solar plants, determining visibility at sea, estimating fertilization of oceans and rainforests by transported mineral dust, understanding changes in weather brought upon by the interaction of aerosols and clouds, and more. The Suomi-NPP satellite was launched late in 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine AOD. This study compares the VIIRS dataset to ground-based measurements of AOD, along with a state-of-the-art satellite AOD dataset (the new version of the Moderate Resolution Imaging Spectrometer Deep Blue algorithm) to assess its reliability. The Suomi-NPP satellite was launched late in 2011, carrying several instruments designed to continue the biogeophysical data records of current and previous satellite sensors. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine aerosol optical depth (AOD), and related activities since launch have been focused towards validating and understanding this new dataset through comparisons with other satellite and ground-based products. The operational VIIRS AOD product is compared over land with AOD derived from Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) observations using the Deep Blue (DB) algorithm from the forthcoming Collection 6 of <span class="hlt">MODIS</span> data</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/984795','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/984795"><span id="translatedtitle">Assessment of biases in <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> due to Lambertian approximation</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Cook, Robert B; SanthanaVannan, Suresh K</p> <p>2010-08-01</p> <p>Using <span class="hlt">MODIS</span> data and the AERONET-based Surface <span class="hlt">Reflectance</span> Validation Network (ASRVN), this work studies errors of <span class="hlt">MODIS</span> atmospheric correction caused by the Lambertian approximation. On one hand, this approximation greatly simplifies the radiative transfer model, reduces the size of the look-up tables, and makes operational algorithm faster. On the other hand, uncompensated atmospheric scattering caused by Lambertian model systematically biases the results. For example, for a typical bowl-shaped bidirectional <span class="hlt">reflectance</span> distribution function (BRDF), the derived <span class="hlt">reflectance</span> is underestimated at high solar or view zenith angles, where BRDF is high, and is overestimated at low zenith angles where BRDF is low. The magnitude of biases grows with the amount of scattering in the atmosphere, i.e., at shorter wavelengths and at higher aerosol concentration. The slope of regression of Lambertian surface <span class="hlt">reflectance</span> vs. ASRVN bidirectional <span class="hlt">reflectance</span> factor (BRF) is about 0.85 in the red and 0.6 in the green bands. This error propagates into the <span class="hlt">MODIS</span> BRDF/albedo algorithm, slightly reducing the magnitude of overall <span class="hlt">reflectance</span> and anisotropy of BRDF. This results in a small negative bias of spectral surface albedo. An assessment for the GSFC (Greenbelt, USA) validation site shows the albedo reduction by 0.004 in the near infrared, 0.005 in the red, and 0.008 in the green <span class="hlt">MODIS</span> bands.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008491','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008491"><span id="translatedtitle">Biomass Burning Aerosol Absorption Measurements with <span class="hlt">MODIS</span> Using the Critical <span class="hlt">Reflectance</span> Method</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zhu, Li; Martins, Vanderlei J.; Remer, Lorraine A.</p> <p>2010-01-01</p> <p>This research uses the critical <span class="hlt">reflectance</span> technique, a space-based remote sensing method, to measure the spatial distribution of aerosol absorption properties over land. Choosing two regions dominated by biomass burning aerosols, a series of sensitivity studies were undertaken to analyze the potential limitations of this method for the type of aerosol to be encountered in the selected study areas, and to show that the retrieved results are relatively insensitive to uncertainties in the assumptions used in the retrieval of smoke aerosol. The critical <span class="hlt">reflectance</span> technique is then applied to Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) data to retrieve the spectral aerosol single scattering albedo (SSA) in South African and South American 35 biomass burning events. The retrieved results were validated with collocated Aerosol Robotic Network (AERONET) retrievals. One standard deviation of mean <span class="hlt">MODIS</span> retrievals match AERONET products to within 0.03, the magnitude of the AERONET uncertainty. The overlap of the two retrievals increases to 88%, allowing for measurement variance in the <span class="hlt">MODIS</span> retrievals as well. The ensemble average of <span class="hlt">MODIS</span>-derived SSA for the Amazon forest station is 0.92 at 670 nm, and 0.84-0.89 for the southern African savanna stations. The critical <span class="hlt">reflectance</span> technique allows evaluation of the spatial variability of SSA, and shows that SSA in South America exhibits higher spatial variation than in South Africa. The accuracy of the retrieved aerosol SSA from <span class="hlt">MODIS</span> data indicates that this product can help to better understand 44 how aerosols affect the regional and global climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22473302','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22473302"><span id="translatedtitle">Variation of <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> and vegetation indices with viewing geometry and soybean development.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N</p> <p>2012-06-01</p> <p>Directional effects introduce a variability in <span class="hlt">reflectance</span> and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - <span class="hlt">MODIS</span>). In this study, we evaluated directional effects on <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The <span class="hlt">reflectance</span> of the first seven <span class="hlt">MODIS</span> bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010301','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010301"><span id="translatedtitle">The Normalization of Surface Anisotropy Effects Present in SEVIRI <span class="hlt">Reflectances</span> by Using the <span class="hlt">MODIS</span> BRDF Method</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Proud, Simon Richard; Zhang, Qingling; Schaaf, Crystal; Fensholt, Rasmus; Rasmussen, Mads Olander; Shisanya, Chris; Mutero, Wycliffe; Mbow, Cheikh; Anyamba, Assaf; Pak, Ed; Sandholt, Inge</p> <p>2014-01-01</p> <p>A modified version of the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) algorithm is presented for use in the angular normalization of surface <span class="hlt">reflectance</span> data gathered by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellites. We present early and provisional daily nadir BRDFadjusted <span class="hlt">reflectance</span> (NBAR) data in the visible and near-infrared MSG channels. These utilize the high temporal resolution of MSG to produce BRDF retrievals with a greatly reduced acquisition period than the comparable <span class="hlt">MODIS</span> products while, at the same time, removing many of the angular perturbations present within the original MSG data. The NBAR data are validated against <span class="hlt">reflectance</span> data from the <span class="hlt">MODIS</span> instrument and in situ data gathered at a field location in Africa throughout 2008. It is found that the MSG retrievals are stable and are of high-quality across much of the SEVIRI disk while maintaining a higher temporal resolution than the <span class="hlt">MODIS</span> BRDF products. However, a number of circumstances are discovered whereby the BRDF model is unable to function correctly with the SEVIRI observations-primarily because of an insufficient spread of angular data due to the fixed sensor location or localized cloud contamination.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150019885','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150019885"><span id="translatedtitle"><span class="hlt">MODIS</span> Instrument Operation and Calibration Improvements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Angal, A.; Madhavan, S.; Link, D.; Geng, X.; Wenny, B.; Wu, A.; Chen, H.; Salomonson, V.</p> <p>2014-01-01</p> <p>Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for over 14 and 12 years since their respective launches in 1999 and 2002. The <span class="hlt">MODIS</span> on-orbit calibration is performed using a set of on-board calibrators, which include a solar diffuser for calibrating the <span class="hlt">reflective</span> solar bands (RSB) and a blackbody for the thermal emissive bands (TEB). On-orbit changes in the sensor responses as well as key performance parameters are monitored using the measurements of these on-board calibrators. This paper provides an overview of <span class="hlt">MODIS</span> on-orbit operation and calibration activities, and instrument long-term performance. It presents a brief summary of the calibration enhancements made in the latest <span class="hlt">MODIS</span> data collection 6 (C6). Future improvements in the <span class="hlt">MODIS</span> calibration and their potential applications to the S-NPP VIIRS are also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011PhDT.........2W&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011PhDT.........2W&link_type=ABSTRACT"><span id="translatedtitle">The MODerate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) <span class="hlt">reflectance</span> anisotropy and albedo of dormant and snow-covered canopies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Zhuosen</p> <p></p> <p>Data from NASA's MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), in polar orbit on the Terra and <span class="hlt">Aqua</span> platforms, have provided surface bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) and albedo products (MCD43) that have been successfully validated during the growing seasons of various vegetated land surface types. This research, however, focuses on the quality of <span class="hlt">MODIS</span> BRDF/albedo product retrievals during the more difficult periods of vegetation dormancy and snow cover by comparison with ground-based albedo measurements. Cropland, grassland, deciduous and conifer forest, and high latitude tundra (including recently burned) sites are considered. Low illumination angles and persistent cloudiness, as well as lower-quality atmospheric correction and cloud discrimination, limit the number of high quality retrievals that are obtained during snow-covered periods. Forest retrievals are challenging as underlying snow may be obscured by foliage or canopy shadows at high viewing and illumination angles. Neither satellite albedo retrievals nor ground measurements are considered reliable at solar zenith angles greater than 70°, which further complicates retrievals at high latitude locations. Moreover, changes due to snowfall or snowmelt can alter the albedo of a location significantly over a very short timescale. Therefore, the standard 500-m gridded BRDF/albedo products are also compared with results from both the <span class="hlt">MODIS</span> daily Direct Broadcast BRDF/Albedo algorithm and the standard MOD10A daily snow albedo product. Using an integrated validation strategy, analyses of the representativeness of the surface heterogeneity under both dormant and snow-covered situations are performed to decide whether direct comparisons between ground measurements and 500-m satellite observations can be made or whether finer spatial resolution airborne or spaceborne data are required to scale the results at each location. Landsat ETM+ data are used to generate finer scale</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9298E..0GL','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9298E..0GL"><span id="translatedtitle">Multitemporal cross-calibration of GF-1 WFV and Terra <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Li; Shi, Tingting; Han, Qijin; Zhang, Xuewen</p> <p>2014-11-01</p> <p>The Gao Fen-1(GF-1) satellite with WFV sensors onboard was launched on April 26, 2013, as part of Gao Fen earth observing system. The Terra Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) has been operational for more than a decade. With its high accuracy onboard calibration system, the data from <span class="hlt">MODIS</span> has become a critical component of numerous applications. Cross-calibration between the sensors is critical to bring the measurements from different sensors to a common radiometric scale. Because of the differences in the spectral <span class="hlt">reflectance</span> function (SRF), the measured physical quantities can be significantly different while observing the same target. This paper focuses on evaluation the radiometric calibration agreement between GF-1/WFV and Terra/<span class="hlt">MODIS</span> using the near-simultaneous and cloud-free image pairs over Dun huang pseudo-invariant calibration site in the visible and near-infrared spectral range. The SRF differences of the analogous WFV and <span class="hlt">MODIS</span> spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. Assuming that the ground target is spectrally and temporally stable, a typical <span class="hlt">reflectance</span> spectrum over the Dun huang site obtained by in-situ measurements was used to compute spectral band adjustment factors (SBAF) for the cross-calibration. No BRDF correction was applied to reduce the seasonal oscillations since the analysis were restricted to only near-nadir images. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) <span class="hlt">reflectance</span> between the two sensors. WFV band 4 has the presence of the water vapor and oxygen absorption features which is absent from the corresponding <span class="hlt">MODIS</span> band 2 which made the WFV measured TOA <span class="hlt">reflectance</span> lower than the <span class="hlt">MODIS</span>'s. Overall, the average percent differences were consistent to within 7%. The long-term cross-calibration results <span class="hlt">reflected</span> that WFV sensor is stable since launch. Although the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H34A..07M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H34A..07M"><span id="translatedtitle">Detection of Harmful Algal Blooms in the Optically Complex Coastal Waters of the Kuwait Bay using <span class="hlt">Aqua-MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manche, C. J.; Sultan, M.; Uddin, S.; Al-Dousari, A.; Chouinard, K.</p> <p>2013-12-01</p> <p>In the optically complex coastal marine waters of the Kuwait Bay, the propagation of Harmful Algal Blooms (HABs) has become a severe issue over the last decade affecting aquaculture a primary component of the Kuwaiti economy. Although several remote sensing based methods of algal bloom detection exist today, few may accurately detect the concentration and identify the type of HABs in Case II waters. The purpose of this study is: (1) assessment of the method that best detects and identifies algal blooms in general and HABs in particular, in the Kuwait Bay, and (2) identification of the factors controlling the occurrence of HABs. Fluorescence Line Height (FLH), Empirical, Bio-Optical, and Operational Methods as well as Ocean Colour 3 Band Ratio (OC3M), Garver-Siegel-Maritorena Model (GSM), and General Inherent Optical Property (GIOP) Chlorophyll-a (Chl-a) algorithms were applied to Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) images acquired (07/2002 to 07/2012) over the Kuwait Bay and areas as far east as Shatt Al-Arab and as far south as N. 29.284 (Lat.), E. 50.047 (Long.) decimal degrees. In-situ data (bloom days: 50; sampling locations: 64) collected (09/1999 to 07/2011) from the Kuwait Bay was provided by the Kuwait Institute for Scientific Research and was used to test the reliability of the satellite-based inferences. Tasks accomplished and findings reached include: (1) comparison of in situ to estimated OC3M, GSM, and GIOP chlorophyll concentrations over the sampling locations for the time period 2002 to 2009 showed that OC3M outperformed the two other techniques in predicting the observed distribution and in replicating the measured concentration of the in-situ Chl-a data; (2) applying the OC3M algorithm to a total of 4039 scenes and using threshold values of 3, 4, and 5 mg/m3 Chl-a concentrations we inferred 371, 202, and 124 occurrences in the Kuwait Bay that met their respective threshold; (3) applying the operational method we successfully</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012AGUFM.B54C..04D&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012AGUFM.B54C..04D&link_type=ABSTRACT"><span id="translatedtitle">Validating the simulation of optical <span class="hlt">reflectance</span> by a vertically resolved canopy biophysics model with <span class="hlt">MODIS</span> daily observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drewry, D. T.; Duveiller, G.</p> <p>2012-12-01</p> <p>Agricultural modeling and yield forecasting are complicated by seasonal variability in traits controlled by factors such as growth stage, nutrient availability and moisture status. While a new generation of vegetation models incorporate ecophysiological details that allow for accurate estimates of carbon uptake, water use and energy exchange, these increases in process-level detail have resulted in the requirement to estimate a broader set of model parameters. Constraining uncertainties in model estimates of productivity and water use requires periodic updates as the structural and physiological status of the vegetation varies over the growing season. Here we explore the utilization of remote sensing <span class="hlt">reflectance</span> observations in the optical domain collected from the <span class="hlt">MODIS</span> sensors onboard the Terra and <span class="hlt">Aqua</span> satellites for constraining key canopy states and reducing the uncertainty in modeled CO2, water and energy exchange with the atmosphere. At the core of this approach is a vertically discretized model (MLCan) that characterizes the ecophysiological functioning of a plant canopy and its biophysical coupling to the ambient environment at a half-hourly timestep. Above-ground vegetation is partially controlled by a root system model that simulates moisture uptake in a multi-layer soil system. MLCan has been rigorously validated for both C3 and C4 crops against field- and leaf-scale observations of canopy CO2 uptake, evapotranspiration and sensible heat exchange across a wide range of meteorological conditions in both ambient and elevated CO2 environments. A widely utilized radiation transfer model (PROSAIL) that accounts for the effects of leaf-level optical properties and foliage distribution and orientation on canopy <span class="hlt">reflectance</span> is coupled to MLCan. This coupling provides the capability of expanding the spectral resolution of the model to nm-scale over the optical range. The coupled model will provide a system for testing the links between plant canopy biochemical</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010322','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010322"><span id="translatedtitle">Daily <span class="hlt">MODIS</span> 500 m <span class="hlt">Reflectance</span> Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shuai, Yanmin; Schaaf, Crystal; Zhang, Xiaoyang; Strahler, Alan; Roy, David; Morisette, Jeffrey; Wang, Zhuosen; Nightingale, Joanne; Nickeson, Jaime; Richardson, Andrew D.; Xie, Donghui; Wang, Jindi; Li, Xiaowen; Strabala, Kathleen; Davies, James E.</p> <p>2013-01-01</p> <p>Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily <span class="hlt">MODIS</span> 500 m <span class="hlt">reflectance</span> anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily <span class="hlt">MODIS</span> 500 m <span class="hlt">reflectance</span> anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected <span class="hlt">MODIS</span> Nadir BRDF (bidirectional <span class="hlt">reflectance</span> distribution function) adjusted <span class="hlt">reflectance</span> (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4435130','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4435130"><span id="translatedtitle">Evaluation and Intercomparison of <span class="hlt">MODIS</span> and GEOV1 Global Leaf Area Index Products over Four Sites in North China</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping</p> <p>2015-01-01</p> <p>This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011–2013. The Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and Terra <span class="hlt">MODIS</span> LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The <span class="hlt">MODIS</span> products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra <span class="hlt">MODIS</span> (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both <span class="hlt">MODIS</span> and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than <span class="hlt">MODIS</span>. <span class="hlt">MODIS</span> anomalies mainly occurred during summer and likely occurred because of surface <span class="hlt">reflectance</span> uncertainty, shorter temporal resolutions and inconsistency between simulated and <span class="hlt">MODIS</span> surface <span class="hlt">reflectances</span>. This study suggests that further improvements of the <span class="hlt">MODIS</span> LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of <span class="hlt">MODIS</span> observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70178118','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70178118"><span id="translatedtitle">Application-ready expedited <span class="hlt">MODIS</span> data for operational land surface monitoring of vegetation condition</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Brown, Jesslyn; Howard, Daniel M.; Wylie, Bruce K.; Frieze, Aaron; Ji, Lei; Gacke, Carolyn</p> <p>2015-01-01</p> <p>Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) system. Because of near-daily global coverage, <span class="hlt">MODIS</span> data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An “expedited” processing system called “eMODIS” operated by the U.S. Geological Survey provides rapid <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard <span class="hlt">MODIS</span> products. We assessed e<span class="hlt">MODIS</span> quality and consistency by comparing to standard <span class="hlt">MODIS</span> data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard <span class="hlt">MODIS</span> (MOD/MYD09Q1), the e<span class="hlt">MODIS</span> Normalized Difference Vegetation Index (NDVI) maintained a strong, significant relationship to standard <span class="hlt">MODIS</span> NDVI, whether from morning (Terra) or afternoon (<span class="hlt">Aqua</span>) orbits. The <span class="hlt">Aqua</span> e<span class="hlt">MODIS</span> data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in e<span class="hlt">MODIS</span> data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2010/1055/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2010/1055/"><span id="translatedtitle">e<span class="hlt">MODIS</span>: A User-Friendly Data Source</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jenkerson, Calli; Maiersperger, Thomas; Schmidt, Gail</p> <p>2010-01-01</p> <p>The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'e<span class="hlt">MODIS</span>' based on Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). With a more frequent repeat cycle than Landsat and higher spatial resolutions than the Advanced Very High Resolution Spectroradiometer (AVHRR), <span class="hlt">MODIS</span> is well suited for vegetation studies. For operational monitoring, however, the benefits of <span class="hlt">MODIS</span> are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. e<span class="hlt">MODIS</span> responds to a community-specific need for alternatively packaged <span class="hlt">MODIS</span> data, addressing each of these factors for real-time monitoring and historical trend analysis. e<span class="hlt">MODIS</span> processes calibrated radiance data (level-1B) acquired by the <span class="hlt">MODIS</span> sensors on the EOS Terra and <span class="hlt">Aqua</span> satellites by combining <span class="hlt">MODIS</span> Land Science Collection 5 Atmospherically Corrected Surface <span class="hlt">Reflectance</span> production code and USGS EROS <span class="hlt">MODIS</span> Direct Broadcast System (DBS) software to create surface <span class="hlt">reflectance</span> and Normalized Difference Vegetation Index (NDVI) products. e<span class="hlt">MODIS</span> is produced over the continental United States and over Alaska extending into Canada to cover the Yukon River Basin. The 250-meter (m), 500-m, and 1,000-m products are delivered in Geostationary Earth Orbit Tagged Image File Format (Geo- TIFF) and composited in 7-day intervals. e<span class="hlt">MODIS</span> composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see e<span class="hlt">MODIS</span> Product Description below). For e<span class="hlt">MODIS</span> products generated over the continental United States (e<span class="hlt">MODIS</span> CONUS), the Terra (from 2000) and <span class="hlt">Aqua</span> (from 2002) records are available and continue through present time. e<span class="hlt">MODIS</span> CONUS also is generated in an expedited process that delivers a 7-day rolling composite</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33E0223X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33E0223X"><span id="translatedtitle">Status of <span class="hlt">MODIS</span> Instruments and Future Calibration Improvements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, X.; Angal, A.; Wu, A.; Salomonson, V. V.</p> <p>2015-12-01</p> <p><span class="hlt">MODIS</span> is one of the key instruments currently operated on two major missions for the NASA's Earth Observing System (EOS) program: Terra and <span class="hlt">Aqua</span> launched in 1999 and 2002, respectively. Nearly 40 data products have been routinely generated from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> observations and widely distributed to the science community and users worldwide for their studies of the earth's system and changes in its geophysical properties. To date, each <span class="hlt">MODIS</span> instrument operation remains nominal and its on-board calibrators (OBC) continue to function satisfactorily. On a regular basis, <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) calibration is performed by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). For the thermal emissive bands (TEB), an on-board blackbody (BB) provides a scan-by-scan calibration reference. Since launch, extensive calibration and characterization activities have been scheduled and implemented by the <span class="hlt">MODIS</span> Characterization Support Team (MCST) to produce and update calibration look-up tables (LUT). This presentation provides an overview of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument status, their on-orbit operation and calibration activities, and radiometric, spectral, and spatial performance. It describes calibration changes (algorithms and look-up tables) made for the <span class="hlt">MODIS</span> Level 1B (L1B) data collection 6 (C6) and discusses remaining challenging issues and ongoing effort for future improvements. As expected, lessons from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have benefitted and will continue to help the S-NPP and JPSS VIIRS instruments in terms of on-orbit operation strategies and calibration enhancements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9881E..1GL','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9881E..1GL"><span id="translatedtitle">Status of <span class="hlt">MODIS</span> spatial and spectral characterization and performance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Link, Dan; Wang, Zhipeng; Xiong, Xiaoxiong</p> <p>2016-05-01</p> <p>Since launch, both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instruments have continued to operate and make measurements of the earth's top of atmospheric (TOA) radiances and <span class="hlt">reflectance</span>. <span class="hlt">MODIS</span> collects data in 36 spectral bands covering wavelengths from 0.41 to 14.4 μm. These spectral bands and detectors are located on four focal plane assemblies (FPAs). <span class="hlt">MODIS</span> on-board calibrators (OBC) include a spectro-radiometric calibration assembly (SRCA), which was designed to characterize and monitor sensor spatial and spectral performance, such as on-orbit changes in the band-to-band registration (BBR), modulation transfer function (MTF), spectral band center wavelengths (CW) and bandwidths (BW). In this paper, we provide a status update of <span class="hlt">MODIS</span> spatial and spectral characterization and performance, following a brief description of SRCA functions and on-orbit calibration activities. Sensor spatial and spectral performance parameters derived from SRCA measurements are introduced and discussed. Results show that on-orbit spatial performance has been very stable for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instruments. The large BBR shifts in <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, an issue identified pre-launch, have remained the same over its entire mission. On-orbit changes in CW and BW are less than 0.5 nm and 1 nm, respectively, for most VIS/NIR spectral bands of both instruments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1715789K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1715789K"><span id="translatedtitle">The regime of aerosol asymmetry parameter and Angstrom exponent over Europe, Mediterranean and Middle East based on <span class="hlt">MODIS</span> satellite data. Intercomparison of <span class="hlt">MODIS-Aqua</span> C051 and C006 retrievals</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korras-Carraca, Marios Bruno; Hatzianastassiou, Nikolaos; Matsoukas, Christos; Gkikas, Antonis; Papadimas, Christos; Sayers, Andy</p> <p>2015-04-01</p> <p>Atmospheric aerosols, both natural and anthropogenic, can cause climate change through their direct, indirect, and semi-direct effects on the radiative energy budget of the Earth-atmosphere system. In the present work, we study two of the most important optical properties of aerosols, the asymmetry parameter (gaer) and the Angstrom exponent (α). Both gaer and α are related with aerosol size, which is a very important parameter for climate and human health. The study region comprises North Africa, the Arabian peninsula, Europe, and the Mediterranean basin. These areas are of great interest, because of the variety of aerosol types they host, both anthropogenic and natural. Urban, industrial or biomass-burning aerosols are usually fine, while desert dust or sea-salt are basically coarse, making thus possible the establishment of a relationship between the type and the size of aerosols. Using satellite data from the collection 051 of <span class="hlt">MODIS</span> (MODerate resolution Imaging Spectroradiometer, <span class="hlt">Aqua</span>), we investigate the spatio-temporal characteristics of the asymmetry parameter and Angstrom exponent. We generally find significant spatial variability, with larger gaer values over regions dominated by larger size particles, e.g. outside the Atlantic coasts of north-western Africa, where desert-dust outflow is taking place. The gaer values tend to decrease with increasing wavelength, especially over areas dominated by small particulates. The intra-annual variability is found to be small in desert-dust areas, with maximum values during summer, while in all other areas larger values are reported during the cold season and smaller during the warm. Significant intra-annual and inter-annual variability is observed around the Black Sea. However, the inter-annual trends of gaer are found to be generally small. The geographical distributions for α (given for the pair of wavelengths 550-865 nm) affirm the conclusions drawn from the asymmetry parameter as regards the aerosol size over</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A14C..05V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A14C..05V"><span id="translatedtitle">Transitioning <span class="hlt">MODIS</span> to VIIRS observations for Land: Surface <span class="hlt">Reflectance</span> results, Status and Long-term Prospective</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vermote, E.</p> <p>2015-12-01</p> <p>Surface <span class="hlt">reflectance</span> is one of the key products from VIIRS and as with <span class="hlt">MODIS</span>, is used in developing several higher-order land products. The VIIRS Surface <span class="hlt">Reflectance</span> (SR) IP is based on the heritage <span class="hlt">MODIS</span> Collection 5 product (Vermote et al. 2002). The quality and character of surface <span class="hlt">reflectance</span> depends on the accuracy of the VIIRS Cloud Mask (VCM) and aerosol algorithms and of course on the adequate calibration of the sensor. Early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system known as the Interface Data Processing System (IDPS), has been a major focus of work to-date, but is now evolving into the development of a VIIRS suite of Climate Data Records produced by the NASA Land Science Investigator Processing System (SIPS). We will present the calibration performance and the role of the surface <span class="hlt">reflectance</span> in calibration monitoring, the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions), the performance of the aerosol input used in the atmospheric correction with quantitative results of the performance of the SR product over AERONET sites. Based on those elements and further assessment, we will address the readiness of the SR product for the production of higher-order land products such as Vegetation Indices, Albedo and LAI/FPAR, the its application to agricultural monitoring and in particular the integration of VIIRS data into the global agricultural monitoring (GLAM) system developed at UMd. Finally from the lessons learned, we will articulate a set of critical recommendations to ensure consistency and continuity of the JPSS mission with the <span class="hlt">MODIS</span> data record.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001322&hterms=water+universe&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dwater%2Buniverse','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001322&hterms=water+universe&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dwater%2Buniverse"><span id="translatedtitle"><span class="hlt">Aqua</span> CERES First Light</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>NASA's latest Earth Observing System satellite-<span class="hlt">Aqua</span>-is dedicated to advancing our understanding of Earth's water cycle. Launched on May 4, 2002, <span class="hlt">Aqua</span> has successfully completed its checkout period and is fully operational. Using multiple instruments, <span class="hlt">Aqua</span> data and images are crucial toward improving our knowledge of global climate change. The Clouds and the Earth's Radiant Energy System (CERES) instrument is one of six on board the <span class="hlt">Aqua</span> satellite. CERES detects the amount of outgoing heat and <span class="hlt">reflected</span> sunlight leaving the planet. A detailed understanding of how clouds affect the energy balance is essential for better climate change predictions. These <span class="hlt">Aqua</span> images show CERES measurements over the United States from June 22, 2002. Clear ocean regions, shown in dark blue on the left image, <span class="hlt">reflect</span> the least amount of sunlight back to space. Clear land areas, shown in lighter blue, <span class="hlt">reflect</span> more solar energy. Clouds and snow-covered surfaces, shown in white and green, <span class="hlt">reflect</span> the greatest amounts of sunlight back to space. Clear warm regions, shown in yellow over much of the western United States on the right image, emit the most heat. High, cold clouds, shown in blue and white, significantly reduce the amount of heat lost to space. <span class="hlt">Aqua</span> is part of NASA's Earth Science Enterprise, a long-term research effort dedicated to understanding and protecting our home planet. Through the study of Earth, NASA will help to provide sound science to policy and economic decision makers so as to better life here, while developing the technologies needed to explore the universe and search for life beyond our home planet. Click to read details on the launch and deployment of <span class="hlt">Aqua</span>; or read the <span class="hlt">Aqua</span> fact sheet for more information about the mission. Image courtesy CERES Science Team, NASA Langley Research Center</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040031528&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bland%2Bsurface%2Btemperature','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040031528&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bland%2Bsurface%2Btemperature"><span id="translatedtitle">Accessing and Understanding <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Leptoukh, Gregory; Jenkerson, Calli B.; Jodha, Siri</p> <p>2003-01-01</p> <p>The National Aeronautics and Space Administration (NASA) launched the Terra satellite in December 1999, as part of the Earth Science Enterprise promotion of interdisciplinary studies of the integrated Earth system. <span class="hlt">Aqua</span>, the second satellite from the series of EOS constellation, was launched in May 2002. Both satellites carry the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument. <span class="hlt">MODIS</span> data are processed at the Goddard Space Flight Center, Greenbelt, MD, and then archived and distributed by the Distributed Active Archive Centers (DAACs). Data products from the <span class="hlt">MODIS</span> sensors present new challenges to remote sensing scientists due to specialized production level, data format, and map projection. <span class="hlt">MODIS</span> data are distributed as calibrated radiances and as higher level products such as: surface <span class="hlt">reflectance</span>, water-leaving radiances, ocean color and sea surface temperature, land surface kinetic temperature, vegetation indices, leaf area index, land cover, snow cover, sea ice extent, cloud mask, atmospheric profiles, aerosol properties, and many other geophysical parameters. <span class="hlt">MODIS</span> data are stored in HDF- EOS format in both swath format and in several different map projections. This tutorial guides users through data set characteristics as well as search and order interfaces, data unpacking, data subsetting, and potential applications of the data. A CD-ROM with sample data sets, and software tools for working with the data will be provided to the course participants.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1111496C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1111496C"><span id="translatedtitle">Actual evapotranspiration estimation in a Mediterranean mountain region by means of Landsat-5 TM and TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> imagery and Sap Flow measurements in Pinus sylvestris forest stands.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Pons, X.; Llorens, P.</p> <p>2009-04-01</p> <p>Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and in the assessment of environmental stress that affects forest and agricultural ecosystems. An increase of evapotranspiration while precipitation remains constant, or is reduced, could decrease water availability for natural and agricultural systems and human needs. Consequently, water balance methods, as the evapotranspiration modelling, have been widely used to estimate crop and forest water needs, as well as the global change effects. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute evapotranspiration at regional scales in a feasible way. Currently, the 38% of Catalonia (NE of the Iberian Peninsula) is covered by forests, and one of the most important forest species is Scots Pine (Pinus sylvestris) which represents the 18.4% of the area occupied by forests. The aim of this work is to model actual evapotranspiration in Pinus sylvestris forest stands, in a Mediterranean mountain region, using remote sensing data, and compare it with stand-scale sap flow measurements measured in the Vallcebre research area (42° 12' N, 1° 49' E), in the Eastern Pyrenees. To perform this study a set of 30 cloud-free TERRA-<span class="hlt">MODIS</span> images and 10 Landsat-5 TM images of path 198 and rows 31 and 32 from June 2003 to January 2005 have been selected to perform evapotranspiration modelling in Pinus sylvestris forest stands. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected two different types of products which contain the remote sensing data we have used to model daily evapotranspiration, daily LST product and daily calibrated <span class="hlt">reflectances</span> product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015385','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015385"><span id="translatedtitle"><span class="hlt">MODIS</span> On-Orbit Calibration and Lessons Learned</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Jack</p> <p>2012-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is a key instrument for NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> missions. Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for more than 12 and 10 years, respectively, and generated an unprecedented amount of data products for the science and user community over a wide range of applications. <span class="hlt">MODIS</span> was developed with improved design and stringent calibration requirements over its heritage sensors in order . to extend and enhance their long-term data records. Its follow-on instrument, the Visible/Infrared Imager Radiometer Suite (VIIRS), was launched on-board the Suomi National Polar-orbiting Partnership (NPP) spacecraft October 28, 2011. <span class="hlt">MODIS</span> collects data in 36 spectral bands, covering wavelengths from 0.41 to 14.S!Jlll, and at 250m, SOOm, and lkm spatial resolutions (nadir). <span class="hlt">MODIS</span> on-orbit calibration is provided by a set of onboard calibrators (OBC), including a solar diffuser (SO), a solar diffuser stability monitor (SDSM), a blackbody (BB), and a spectroradiometric calibration assembly (SRCA). In addition to the onboard calibrators, regular lunar observations are made by both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> to track their calibration stability in the <span class="hlt">reflective</span> solar region. This tutorial session provides an overview of <span class="hlt">MODIS</span> on-orbit calibration and characterization methodologies. It discusses challenging issues and lessons learned from sensor design, operation, calibration, and inter-comparisons. Examples of instrument on-orbit performance are illustrated with a focus on the improvements made based on various lessons learned. It is expected that <span class="hlt">MODIS</span> experience and lessons will continue to provide valuable information for future earth observing missions/sensors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110020728','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110020728"><span id="translatedtitle"><span class="hlt">MODIS</span> On-orbit Calibration Uncertainty Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chiang, Vincent; Sun, Junqiang; Wu, Aisheng</p> <p>2011-01-01</p> <p><span class="hlt">MODIS</span> has 20 <span class="hlt">reflective</span> solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, <span class="hlt">MODIS</span> was developed with very stringent calibration uncertainty requirements. As a result, <span class="hlt">MODIS</span> was designed and built with a set of on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated. In terms of its calibration traceability, <span class="hlt">MODIS</span> RSB calibration is <span class="hlt">reflectance</span> based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of <span class="hlt">MODIS</span> calibration methodologies and an in-depth analysis of its on-orbit calibration uncertainties. Also discussed in this paper are uncertainty contributions from individual components and differences due to Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument characteristics and on-orbit performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014IJAEO..33..243P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014IJAEO..33..243P"><span id="translatedtitle">Automatic and improved radiometric correction of Landsat imagery using reference values from <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> images</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pons, X.; Pesquer, L.; Cristóbal, J.; González-Guerrero, O.</p> <p>2014-12-01</p> <p>Radiometric correction is a prerequisite for generating high-quality scientific data, making it possible to discriminate between product artefacts and real changes in Earth processes as well as accurately produce land cover maps and detect changes. This work contributes to the automatic generation of surface <span class="hlt">reflectance</span> products for Landsat satellite series. Surface <span class="hlt">reflectances</span> are generated by a new approach developed from a previous simplified radiometric (atmospheric + topographic) correction model. The proposed model keeps the core of the old model (incidence angles and cast-shadows through a digital elevation model [DEM], Earth-Sun distance, etc.) and adds new characteristics to enhance and automatize ground <span class="hlt">reflectance</span> retrieval. The new model includes the following new features: (1) A fitting model based on reference values from pseudoinvariant areas that have been automatically extracted from existing <span class="hlt">reflectance</span> products (Terra <span class="hlt">MODIS</span> MOD09GA) that were selected also automatically by applying quality criteria that include a geostatistical pattern model. This guarantees the consistency of the internal and external series, making it unnecessary to provide extra atmospheric data for the acquisition date and time, dark objects or dense vegetation. (2) A spatial model for atmospheric optical depth that uses detailed DEM and MODTRAN simulations. (3) It is designed so that large time-series of images can be processed automatically to produce consistent Landsat surface <span class="hlt">reflectance</span> time-series. (4) The approach can handle most images, acquired now or in the past, regardless of the processing system, with the exception of those with extremely high cloud coverage. The new methodology has been successfully applied to a series of near 300 images of the same area including MSS, TM and ETM+ imagery as well as to different formats and processing systems (LPGS and NLAPS from the USGS; CEOS from ESA) for different degrees of cloud coverage (up to 60%) and SLC</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1111496C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1111496C&link_type=ABSTRACT"><span id="translatedtitle">Actual evapotranspiration estimation in a Mediterranean mountain region by means of Landsat-5 TM and TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> imagery and Sap Flow measurements in Pinus sylvestris forest stands.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Pons, X.; Llorens, P.</p> <p>2009-04-01</p> <p>Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and in the assessment of environmental stress that affects forest and agricultural ecosystems. An increase of evapotranspiration while precipitation remains constant, or is reduced, could decrease water availability for natural and agricultural systems and human needs. Consequently, water balance methods, as the evapotranspiration modelling, have been widely used to estimate crop and forest water needs, as well as the global change effects. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute evapotranspiration at regional scales in a feasible way. Currently, the 38% of Catalonia (NE of the Iberian Peninsula) is covered by forests, and one of the most important forest species is Scots Pine (Pinus sylvestris) which represents the 18.4% of the area occupied by forests. The aim of this work is to model actual evapotranspiration in Pinus sylvestris forest stands, in a Mediterranean mountain region, using remote sensing data, and compare it with stand-scale sap flow measurements measured in the Vallcebre research area (42° 12' N, 1° 49' E), in the Eastern Pyrenees. To perform this study a set of 30 cloud-free TERRA-<span class="hlt">MODIS</span> images and 10 Landsat-5 TM images of path 198 and rows 31 and 32 from June 2003 to January 2005 have been selected to perform evapotranspiration modelling in Pinus sylvestris forest stands. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected two different types of products which contain the remote sensing data we have used to model daily evapotranspiration, daily LST product and daily calibrated <span class="hlt">reflectances</span> product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRD..117.3202W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRD..117.3202W"><span id="translatedtitle">Critical <span class="hlt">reflectance</span> derived from <span class="hlt">MODIS</span>: Application for the retrieval of aerosol absorption over desert regions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wells, Kelley C.; Martins, J. Vanderlei; Remer, Lorraine A.; Kreidenweis, Sonia M.; Stephens, Graeme L.</p> <p>2012-02-01</p> <p>The determination of aerosol direct radiative forcing over desert regions requires accurate information about the aerosol single-scattering albedo (SSA); however, the brightness of desert surfaces in the visible and near-IR range complicates the retrieval of aerosol optical properties using passive space-based measurements. Here we use the critical <span class="hlt">reflectance</span> method to retrieve spectral aerosol absorption from space over North Africa, a desert region that is predominantly impacted by absorbing dust and biomass burning aerosol. We examine the sensitivity of the critical <span class="hlt">reflectance</span> parameter to aerosol physical and optical properties that are representative of the region, and we find that the critical <span class="hlt">reflectance</span> has low sensitivity to assumptions of aerosol size and refractive index for dust-like particles, except at scattering angles near 180°, which should be avoided with this method. We use our findings to retrieve spectral SSA from critical <span class="hlt">reflectance</span> derived from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) <span class="hlt">reflectances</span> in the vicinity of two Aerosol Robotic Network (AERONET) stations: Tamanrasset, in the Algerian Sahara, and Banizoumbou, in the Sahel. We retrieve lower aerosol SSAs at Banizoumbou, which is often impacted by dust-smoke mixtures, and higher SSAs at Tamanrasset, where pure desert dust is the dominant aerosol. Our results generally fall within the AERONET uncertainty envelopes, although at Banizoumbou we retrieve a spectral dependence different from that of AERONET. On the basis of our analysis, we expect to be able to retrieve SSA from critical <span class="hlt">reflectance</span> for pure dust with an uncertainty of 0.02 and to provide spatial and spectral SSA information that will help reduce current uncertainties in the aerosol radiative forcing over desert regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015244','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015244"><span id="translatedtitle">Using Lunar Observations to Assess Terra <span class="hlt">MODIS</span> Thermal Emissive Bands Calibration</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Chen, Hongda</p> <p>2010-01-01</p> <p><span class="hlt">MODIS</span> collects data in both the <span class="hlt">reflected</span> solar and thermal emissive regions using 36 spectral bands. The center wavelengths of these bands cover the3.7 to 14.24 micron region. In addition to using its on-board calibrators (OBC), which include a full aperture solar diffuser (SD) and a blackbody (BB), lunar observations have been scheduled on a regular basis to support both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-orbit calibration and characterization. This paper provides an overview of <span class="hlt">MODIS</span> lunar observations and their applications for the <span class="hlt">reflective</span> solar bands (RSB) and thermal emissive bands (TEB) with an emphasis on potential calibration improvements of <span class="hlt">MODIS</span> band 21 at 3.96 microns. This spectral band has detectors set with low gains to enable fire detection. Methodologies are proposed and examined on the use of lunar observations for the band 21 calibration. Also presented in this paper are preliminary results derived from Terra <span class="hlt">MODIS</span> lunar observations and remaining challenging issues.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120010372','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120010372"><span id="translatedtitle">Evaluation of Detector-to-Detector and Mirror Side Differences for Terra <span class="hlt">MODIS</span> <span class="hlt">Reflective</span> Solar Bands Using Simultaneous MISR Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wu, Aisheng; Xiong, Xiaoxiong; Angal, A.; Barnes, W.</p> <p>2011-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is one of the five Earth-observing instruments on-board the National Aeronautics and Space Administration (NASA) Earth-Observing System(EOS) Terra spacecraft, launched in December 1999. It has 36 spectral bands with wavelengths ranging from 0.41 to 14.4 mm and collects data at three nadir spatial resolutions: 0.25 km for 2 bands with 40 detectors each, 0.5 km for 5 bands with 20 detectors each and 1 km for the remaining 29 bands with 10 detectors each. <span class="hlt">MODIS</span> bands are located on four separate focal plane assemblies (FPAs) according to their spectral wavelengths and aligned in the cross-track direction. Detectors of each spectral band are aligned in the along-track direction. <span class="hlt">MODIS</span> makes observations using a two-sided paddle-wheel scan mirror. Its on-board calibrators (OBCs) for the <span class="hlt">reflective</span> solar bands (RSBs) include a solar diffuser (SD), a solar diffuser stability monitor (SDSM) and a spectral-radiometric calibration assembly (SRCA). Calibration is performed for each band, detector, sub-sample (for sub-kilometer resolution bands) and mirror side. In this study, a ratio approach is applied to <span class="hlt">MODIS</span> observed Earth scene <span class="hlt">reflectances</span> to track the detector-to-detector and mirror side differences. Simultaneous observed <span class="hlt">reflectances</span> from the Multi-angle Imaging Spectroradiometer (MISR), also onboard the Terra spacecraft, are used with <span class="hlt">MODIS</span> observed <span class="hlt">reflectances</span> in this ratio approach for four closely matched spectral bands. Results show that the detector-to-detector difference between two adjacent detectors within each spectral band is typically less than 0.2% and, depending on the wavelengths, the maximum difference among all detectors varies from 0.5% to 0.8%. The mirror side differences are found to be very small for all bands except for band 3 at 0.44 mm. This is the band with the shortest wavelength among the selected matching bands, showing a time-dependent increase for the mirror side difference. This</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMT.....8.5237J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMT.....8.5237J"><span id="translatedtitle">Adaption of the <span class="hlt">MODIS</span> aerosol retrieval algorithm using airborne spectral surface <span class="hlt">reflectance</span> measurements over urban areas: a case study</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jäkel, E.; Mey, B.; Levy, R.; Gu, X.; Yu, T.; Li, Z.; Althausen, D.; Heese, B.; Wendisch, M.</p> <p>2015-12-01</p> <p><span class="hlt">MODIS</span> (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the <span class="hlt">reflectance</span> characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface <span class="hlt">reflectance</span> in blue and red wavelengths. From airborne measurements of surface <span class="hlt">reflectance</span> over the city of Zhongshan, China, were collected that could replace the assumptions within the <span class="hlt">MODIS</span> retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the <span class="hlt">MODIS</span> data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured <span class="hlt">reflectance</span> from <span class="hlt">MODIS</span>, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the <span class="hlt">MODIS</span> AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model <span class="hlt">reflectances</span> at top of atmosphere for predefined aerosol properties. The <span class="hlt">reflectance</span> data were used as input for the retrieval methods. It</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005757&hterms=Wang&qs=N%3D0%26Ntk%3DAuthor-Name%26Ntx%3Dmode%2Bmatchall%26Ntt%3DWang%252C%2BX','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005757&hterms=Wang&qs=N%3D0%26Ntk%3DAuthor-Name%26Ntx%3Dmode%2Bmatchall%26Ntt%3DWang%252C%2BX"><span id="translatedtitle">Scientific Impact of <span class="hlt">MODIS</span> C5 Calibration Degradation and C6+ Improvements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; Hall, F.; Sellers, P.; Wu, A.; Angal, A.</p> <p>2014-01-01</p> <p>The Collection 6 (C6) <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) <span class="hlt">MODIS</span> Terra and, to lesser extent, in <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> geophysical data sets. Sensor degradation is largest in the blue band (B3) of the <span class="hlt">MODIS</span> sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple <span class="hlt">MODIS</span> C5 products including the dark target algorithm's aerosol optical depth over land and Ångstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface <span class="hlt">reflectance</span> and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad <span class="hlt">MODIS</span> user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6C calibration of the <span class="hlt">MODIS</span> data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of <span class="hlt">MODIS</span> Terra since about 2007, as well as detrending and Terra- <span class="hlt">Aqua</span> cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the <span class="hlt">MODIS</span> ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface <span class="hlt">reflectance</span> (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015444','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015444"><span id="translatedtitle">Impact of Sensor Degradation on the <span class="hlt">MODIS</span> NDVI Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, Dongdong; Morton, Douglas; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert</p> <p>2011-01-01</p> <p>Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, we evaluated the impact of sensor degradation on trend detection using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on the Terra and <span class="hlt">Aqua</span> platforms. For Terra <span class="hlt">MODIS</span>, the impact of blue band (Band 3, 470nm) degradation on simulated surface <span class="hlt">reflectance</span> was most pronounced at near-nadir view angles, leading to a 0.001-0.004/yr decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends <span class="hlt">MODIS</span> NDVI over North America were consistent with simulated results, with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and <span class="hlt">Aqua</span> (6.7%) <span class="hlt">MODIS</span> sensors during 2002-2010. Planned adjustments to Terra <span class="hlt">MODIS</span> calibration for Collection 6 data reprocessing will largely eliminate this negative bias in NDVI trends over vegetation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140009143','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140009143"><span id="translatedtitle">Impact of Sensor Degradation on the <span class="hlt">MODIS</span> NDVI Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert</p> <p>2012-01-01</p> <p>Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on the Terra and <span class="hlt">Aqua</span> platforms. For Terra <span class="hlt">MODIS</span>, the impact of blue band (Band 3, 470 nm) degradation on simulated surface <span class="hlt">reflectance</span> was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in <span class="hlt">MODIS</span> NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and <span class="hlt">Aqua</span> (6.7%) <span class="hlt">MODIS</span> sensors during 2002-2010. Planned adjustments to Terra <span class="hlt">MODIS</span> calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006614','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006614"><span id="translatedtitle">Consistency of CERES Radiances and Fluxes from <span class="hlt">Aqua</span> and Suomi-NPP</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Su, Wenying; Liang, Lusheng; Miller, Walter; Loeb, Norman</p> <p>2015-01-01</p> <p>The Clouds and Earth's Radiant Energy System (CERES) instruments on board Terra, <span class="hlt">Aqua</span>, and Suomi-NPP have been providing data products critical to advancing our understanding of the effects of clouds and aerosols on radiative energy within the Earth-atmosphere system. The CERES instrument consists of a threechannel broadband scanning radiometer. The scanning radiometer measures radiances in shortwave (SW, 0.3-5 micron), window (WN, 8-12 micron), and total (0.3-200 micron) channels. The longwave (LW) component is derived as the difference between total and SW channels. These measured radiances at a given sun-Earthsatellite geometry are converted to outgoing <span class="hlt">reflected</span> solar and emitted thermal TOA radiative fluxes by using CERES scene-type dependent angular distribution models (ADMs). The CERES instruments must remain radiometrically stable and correctly inter-calibrated to accurately capture changes in Earth"s radiation budget from interannual to decadal timescales. This presentation will focus on comparisons between collocated radiance measurements from CERES instruments on <span class="hlt">Aqua</span> and on Suomi-NPP. As we do not have a set of ADMs that is constructed specifically for the CERES instrument on Suomi-NPP, CERES <span class="hlt">Aqua</span> ADMs are used to invert fluxes from radiance measurements on Suomi-NPP. But the CERES <span class="hlt">Aqua</span> footprint size is smaller than the CERES Suomi-NPP footprint size and the scene identifications provided by <span class="hlt">MODIS</span> and VIIRS can also be different from each other. Will using <span class="hlt">Aqua</span> ADMs for Suomi-NPP flux inversion increase the flux uncertainty? We will examine the deseasonalized flux anomaly time series using <span class="hlt">Aqua</span> data alone and using combined <span class="hlt">Aqua</span> and Suomi-NPP data. We will also present a simulation study to assess the Suomi-NPP flux uncertainty from using <span class="hlt">Aqua</span> ADMs for the flux inversion.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B43C0570C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B43C0570C"><span id="translatedtitle">Generating and Evaluation Leaf Area Index (LAI) from <span class="hlt">MODIS</span> MultiAngle Implementation of Atmospheric Correction (MAIAC) Surface <span class="hlt">Reflectance</span> Dataset</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, C.; Park, T.; Yan, K.; Lyapustin, A.; Wang, Y.; CHOI, S.; Yang, B.; Knyazikhin, Y.; Myneni, R. B.</p> <p>2015-12-01</p> <p>This study generates and evaluates prototype Leaf Area Index (LAI) product based on MODerate resolution Imaging Spectroradiometer's (<span class="hlt">MODIS</span>) Bidirectional <span class="hlt">Reflectance</span> Factor (BRF, commonly known as surface <span class="hlt">reflectance</span>) which is a product of MultiAngle Implementation of Atmospheric Correction (MAIAC) package. LAI is a key parameter of vegetation in characterizing interactions of energy and mass between the Earth's surface and atmosphere. On the other hand, MAIAC BRF is retrieved from a new atmospheric correction algorithm, which has higher spatial resolution and is believed to have more reliable cloud/aerosol detection technique than standard <span class="hlt">MODIS</span> BRF product. Two main objectives of this study are: 1). Maintaining the radiative transfer theory based LAI algorithm's look up table (LUT) unchanged, to compare LAI product retrieved from different versions of BRF products (<span class="hlt">MODIS</span> collection 5, collection 6 and MAIAC); 2). To adjust the LUT to resolve LAI's possible systematic discrepancies resulting from atmospheric correction methods within the input BRF other than our LAI algorithm. Before the LUT adjusting, comparing to standard <span class="hlt">MODIS</span> products shows that MAIAC LAI product will overestimate among herbaceous biome types which have low LAI values, while underestimate among woody biome types which have relatively higher values. Based on the theory of radiative transfer of canopy spectral invariants, two biome and MAIAC specific configurable parameters (Single Scattering Albedo and Uncertainty) in the LUT are adjusted to minimize the inconsistency due to input BRFs. Experiments shows that our new result: 1). has good agreement with field measured data (e.g. DIRECT); 2) is consistent with standard <span class="hlt">MODIS</span> LAI product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120010660','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120010660"><span id="translatedtitle">Critical <span class="hlt">Reflectance</span> Derived from <span class="hlt">MODIS</span>: Application for the Retrieval of Aerosol Absorption over Desert Regions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wells, Kelley C.; Martins, J. Vanderlei; Remer, Lorraine A.; Kreidenweis, Sonia M.; Stephens, Graeme L.</p> <p>2012-01-01</p> <p>Aerosols are tiny suspended particles in the atmosphere that scatter and absorb sunlight. Smoke particles are aerosols, as are sea salt, particulate pollution and airborne dust. When you look down at the earth from space sometimes you can see vast palls of whitish smoke or brownish dust being transported by winds. The reason that you can see these aerosols is because they are <span class="hlt">reflecting</span> incoming sunlight back to the view in space. The reason for the difference in color between the different types of aerosol is that the particles arc also absorbing sunlight at different wavelengths. Dust appears brownish or reddish because it absorbs light in the blue wavelengths and scatters more reddish light to space, Knowing how much light is scattered versus how much is absorbed, and knowin that as a function of wavelength is essential to being able to quantify the role aerosols play in the energy balance of the earth and in climate change. It is not easy measuring the absorption properties of aerosols when they are suspended in the atmosphere. People have been doing this one substance at a time in the laboratory, but substances mix when they are in the atmosphere and the net absorption effect of all the particles in a column of air is a goal of remote sensing that has not yet been completely successful. In this paper we use a technique based on observing the point at which aerosols change from brightening the surface beneath to darkening it. If aerosols brighten a surface. they must scatter more light to space. If they darken the surface. they must be absorbing more. That cross over point is called the critical <span class="hlt">reflectance</span> and in this paper we show that critical <span class="hlt">reflectance</span> is a monotonic function of the intrinsic absorption properties of the particles. This parameter we call the single scattering albedo. We apply the technique to <span class="hlt">MODIS</span> imagery over the Sahara and Sahel regions to retrieve the single scattering albedo in seven wavelengths, compare these retrievals to ground</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23038327','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23038327"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span>-derived bidirectional <span class="hlt">reflectivity</span> retrieval algorithm in mid-infrared channel with field measurements.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tang, Bo-Hui; Wu, Hua-; Li, Zhao-Liang; Nerry, Françoise</p> <p>2012-07-30</p> <p>This work addressed the validation of the <span class="hlt">MODIS</span>-derived bidirectional <span class="hlt">reflectivity</span> retrieval algorithm in mid-infrared (MIR) channel, proposed by Tang and Li [Int. J. Remote Sens. 29, 4907 (2008)], with ground-measured data, which were collected from a field campaign that took place in June 2004 at the ONERA (Office National d'Etudes et de Recherches Aérospatiales) center of Fauga-Mauzac, on the PIRRENE (Programme Interdisciplinaire de Recherche sur la Radiométrie en Environnement Extérieur) experiment site [Opt. Express 15, 12464 (2007)]. The leaving-surface spectral radiances measured by a BOMEM (MR250 Series) Fourier transform interferometer were used to calculate the ground brightness temperatures with the combination of the inversion of the Planck function and the spectral response functions of <span class="hlt">MODIS</span> channels 22 and 23, and then to estimate the ground brightness temperature without the contribution of the solar direct beam and the bidirectional <span class="hlt">reflectivity</span> by using Tang and Li's proposed algorithm. On the other hand, the simultaneously measured atmospheric profiles were used to obtain the atmospheric parameters and then to calculate the ground brightness temperature without the contribution of the solar direct beam, based on the atmospheric radiative transfer equation in the MIR region. Comparison of those two kinds of brightness temperature obtained by two different methods indicated that the Root Mean Square Error (RMSE) between the brightness temperatures estimated respectively using Tang and Li's algorithm and the atmospheric radiative transfer equation is 1.94 K. In addition, comparison of the hemispherical-directional <span class="hlt">reflectances</span> derived by Tang and Li's algorithm with those obtained from the field measurements showed that the RMSE is 0.011, which indicates that Tang and Li's algorithm is feasible to retrieve the bidirectional <span class="hlt">reflectivity</span> in MIR channel from <span class="hlt">MODIS</span> data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C43A0367C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C43A0367C"><span id="translatedtitle">Towards an Aassimilation of <span class="hlt">MODIS</span> VIS/NIR <span class="hlt">reflectance</span> into the detailed snow model SURFEX/ISBA-Crocus</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Charrois, L.; Cosme, E.; Dumont, M.; Lafaysse, M.; Morin, S.; Libois, Q.; Picard, G.; Arnaud, L.</p> <p>2014-12-01</p> <p>SURFEX/ISBA-Crocus is a physically based multi-layer snowpack model used for numerous scientific and operational applications such as avalanche risk forecast. Although some snowpack models simulations usually performed reasonably well, differences with real snowpack still exist and may be due to various origins such as weather forcing input. Yet, no snow observations are assimilated into the snow model SURFEX/ISBA-Crocus so that the simulation error is accumulated over the winter season. Some efforts will be done to assimilate data from visible and near-infrared imagers into the snowpack model to improve the snowpack simulations. The new optical scheme of SURFEX/ISBA-Crocus, called TARTES, allows the use of <span class="hlt">reflectance</span> as diagnostic variables of the model. These <span class="hlt">reflectance</span> are sensitive to snow properties such as specific surface area (SSA) and impurity content. They are measured by the <span class="hlt">MODIS</span> spectroradiometer and can thus be used in an assimilation framework to account for the high spatial and temporal variability of the snow cover in mountainous areas. Prior to assimilation, we used ensemble methods to find the best assimilation scheme to be implemented. The distribution of model errors is investigated together with the relationship between simulated <span class="hlt">reflectance</span> and model prognostic variables (density, SSA, …). First tests of <span class="hlt">reflectance</span> assimilation were then carried out using a particle filter and <span class="hlt">MODIS</span> measurements at Col du Lautaret (French Alps). The impact of the assimilation has been evaluated in terms of simulated snow properties.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.6273Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.6273Z"><span id="translatedtitle">Intercalibration of CERES, <span class="hlt">MODIS</span>, and MISR <span class="hlt">reflected</span> solar radiation and its application to albedo trends</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhan, Yizhe; Davies, Roger</p> <p>2016-06-01</p> <p>Measurements on the Terra satellite by the Cloud and the Earth's Radiant Energy System (CERES), the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), and the Multiangle Imaging Spectroradiometer (MISR), between 2001 and 2015 over the polar regions, are analyzed in order to investigate the intercalibration differences between these instruments. Direct comparisons of colocated near-nadir radiances from CERES, <span class="hlt">MODIS</span>, and MISR show relative agreement within 2.4% decade-1. By comparison with the CERES shortwave broadband, <span class="hlt">MODIS</span> Collection 6 is getting brighter, by 1.0 ± 0.7% decade-1 in the red band and 1.4 ± 0.7% decade-1 in the near infrared. MISR's red and near-infrared bands, however, show darkening trends of -1.0 ± 0.6% decade-1 and -1.1 ± 0.6% decade-1, respectively. The CERES/<span class="hlt">MODIS</span> or CERES/MISR visible and near IR radiance ratio is shown to have a significant negative correlation with precipitable water content over the Antarctic Plateau. The intercalibration results successfully correct the differential top-of-atmosphere trends in zonal albedos between CERES and MISR.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020083259','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020083259"><span id="translatedtitle">Relationship Between Surface <span class="hlt">Reflectance</span> in the Visible and Mid-IR used in <span class="hlt">MODIS</span> Aerosol Algorithm-Theory</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram J.; Gobron, Nadine; Pinty, Bernard; Widlowski, Jean-Luc; Verstraete, Michel M.; Lau, William K. M. (Technical Monitor)</p> <p>2002-01-01</p> <p>Data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument that flies in polar orbit on the Terra platform, are used to derive the aerosol optical thickness and properties over land and ocean. The relationships between visible <span class="hlt">reflectance</span> (at blue, rho(sub blue), and red, rho(sub red)) and mid-infrared (at 2.1 microns, rho(sub 2.1)) are used in the <span class="hlt">MODIS</span> aerosol retrieval algorithm to derive global distribution of aerosols over the land. These relations have been established from a series of measurements indicating that rho(sub blue) is approximately 0.5 rho(sub red) is approximately 0.25 rho(sub 2.1). Here we use a model to describe the transfer of radiation through a vegetation canopy composed of randomly oriented leaves to assess the theoretical foundations for these relationships. Calculations for a wide range of leaf area indices and vegetation fractions show that rho(sub blue) is consistently about 1/4 of rho(sub 2.1) as used by <span class="hlt">MODIS</span> for the whole range of analyzed cases, except for very dark soils, such as those found in burn scars. For its part, the ratio rho(sub red)/rho(sub 2.1) varies from less than the empirically derived value of 1/2 for dense and dark vegetation, to more than 1/2 for bright mixture of soil and vegetation. This is in agreement with measurements over uniform dense vegetation, but not with measurements over mixed dark scenes. In the later case the discrepancy is probably mitigated by shadows due to uneven canopy and terrain on a large scale. It is concluded that the value of this ratio should ideally be made dependent on the land cover type in the operational processing of <span class="hlt">MODIS</span> data, especially over dense forests.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005180&hterms=orbit&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dorbit','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005180&hterms=orbit&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dorbit"><span id="translatedtitle">On-Orbit Performance of <span class="hlt">MODIS</span> Solar Diffuser Stability Monitor</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Angal, Amit; Choi, Taeyoung; Sun, Jungiang; Johnson, Eric</p> <p>2014-01-01</p> <p><span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) calibration is provided by an on-board solar diffuser (SD). On-orbit changes in the SD bi-directional <span class="hlt">reflectance</span> factor (BRF) are tracked by a solar diffuser stability monitor (SDSM). The SDSM consists of a solar integration sphere (SIS) with nine detectors covering wavelengths from 0.41 to 0.94 microns. It functions as a ratioing radiometer, making alternate observations of the sunlight through a fixed attenuation screen and the sunlight diffusely <span class="hlt">reflected</span> from the SD during each scheduled SD/SDSM calibration event. Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> SD/SDSM systems have been operated regularly to support the RSB on-orbit calibration. This paper provides an overview of <span class="hlt">MODIS</span> SDSM design functions, its operation and calibration strategies, and on-orbit performance. Changes in SDSM detector responses over time and their potential impact on tracking SD on-orbit degradation are examined. Also presented in this paper are lessons learned from <span class="hlt">MODIS</span> SD/SDSM calibration system and improvements made to the VIIRS SD/SDSM system, including preliminary comparisons of <span class="hlt">MODIS</span> and VIIRS SDSM on-orbit performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150023337','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150023337"><span id="translatedtitle"><span class="hlt">MODIS</span> and VIIRS Lunar Observations and Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Wang, Zhipeng; Sun, Junqiang; Angal, Amit Avinash; Fulbright, Jon; Butler, James</p> <p>2013-01-01</p> <p>Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for more than 13 and 11 years since their launch in 1999 and 2002, respectively. The VIIRS instrument on-board the S-NPP launched in 2011 has also operated for nearly 2 years. Both <span class="hlt">MODIS</span> and VIIRS make observations in the <span class="hlt">reflective</span> solar and thermal emissive regions and their on-orbit calibration and characterization are provided by a set of on-board calibrators (OBC). In addition, lunar observations have been made on a regular basis to support sensor on-orbit calibration. This paper provides a brief overview of <span class="hlt">MODIS</span> and VIIRS instrument on-orbit calibration and characterization activities. It describes the approaches and strategies developed to schedule and perform on-orbit lunar observations. Specific applications of <span class="hlt">MODIS</span> and VIIRS lunar observations discussed in this paper include radiometric calibration stability monitoring and performance assessment of sensor spatial characterization. Results derived from lunar observations, such as sensor response (or gain) trending and band-to-band registration, are compared with that derived from sensor OBC. The methodologies and applications presented in this paper can also be applied to other earth observing sensors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100020136','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100020136"><span id="translatedtitle">Remote Sensing of the Absorption Coefficients and Chlorophyll a Concentration in the U.S. Southern Middle Atlantic Bight from SeaWiFS and <span class="hlt">MODIS-Aqua</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pan, Xiaoju; Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.</p> <p>2008-01-01</p> <p>At present, satellite remote sensing of coastal water quality and constituent concentration is subject to large errors as compared to the capability of satellite sensors in oceanic waters. In this study, field measurements collected on a series of cruises within U.S. southern Middle Atlantic Bight (SMAB) were applied to improve retrievals of satellite ocean color products in order to examine the factors that regulate the bio-optical properties within the continental shelf waters of the SMAB. The first objective was to develop improvements in satellite retrievals of absorption coefficients of phytoplankton (a(sub ph)), colored dissolved organic matter (CDOM) (a(sub g)), non-pigmented particles (a(sub d)), and non-pigmented particles plus CDOM (a(sub dg)), and chlorophyll a concentration ([Chl_a]). Several algorithms were compared to derive constituent absorption coefficients from remote sensing <span class="hlt">reflectance</span> (R(sub rs)) ratios. The validation match-ups showed that the mean absolute percent differences (MAPD) were typically less than 35%, although higher errors were found for a(sub d) retrievals. Seasonal and spatial variability of satellite-derived absorption coefficients and [Chl_a] was apparent and consistent with field data. CDOM is a major contributor to the bio-optical properties of the SMAB, accounting for 35-70% of total light absorption by particles plus CDOM at 443 nm, as compared to 30-45% for phytoplankton and 0-20% for non-pigmented particles. The overestimation of [Chl_a] from the operational satellite algorithms may be attributed to the strong CDOM absorption in this region. River discharge is important in controlling the bio-optical environment, but cannot explain all of the regional and seasonal variability of biogeochemical constituents in the SMAB.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713537G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713537G"><span id="translatedtitle">Intercomparison of <span class="hlt">MODIS-Aqua</span> C051 and C006 Level 3 Deep Blue AOD and Ångström exponent retrievals over the Sahara desert and the Arabian Peninsula during the period 2002-2014</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gkikas, Antonis; Basart, Sara; Korras-Carraca, Marios; Papadimas, Christos; Hatzianastassiou, Nikos; Sayer, Andrew; Hsu, Christina; Baldasano, Jose Maria</p> <p>2015-04-01</p> <p>Dust loads emitted from the arid regions of Northern Africa and the Arabian Peninsula account for the major portion of the global dust aerosol burden. Depending on prevailing atmospheric circulation they can be transported far away from their source areas. Considering the key role of dust aerosols to weather and climate a better description of their spatial and temporal variability it is an issue of great importance. The main target of the present study is to describe aerosols' regime over Northern Africa and Arabian Peninsula using Deep Blue aerosol optical depth (AOD550nm) and Ångström exponent (α412-470nm) measurements. Given the applied changes to the retrieval algorithm, emphasis is also given to the inter-comparison between the data from Collections 051 and 006. The analysis is performed using <span class="hlt">MODIS-Aqua</span> daily Level 3 data at 1°x1° spatial resolution over the period 2002-2014. The study region extends from 20°W to 60°E and from 0° to 40°N. The obtained long-term geographical distributions reveal many similarities between C051 and C006 AOD retrievals. They both indicate a zone of high AODs along the parallel of 15°N, extending from the western coasts of Africa to Chad where the maximum values (~1.3) are recorded. In the Arabian Peninsula, the maximum AODs (up to 0.6) are found in Iraq. On the contrary, more apparent differences between the two collections are found for α412-470nm. It is evident a reduction of C006 retrievals, which is more pronounced across the Sahara desert. In C006, the α412-470nm values over the deserts of Northern Africa and Middle East mostly vary from 0 to 0.6 while higher values (up to 1.5) are observed in sub-sahel regions, west coasts of Saudi Arabia and Iran. During the study period, in both collections, AOD has decreased by up to 93% in N. Africa (northern parts of Algeria) while it has increased by up to 70% in the Middle East (northern parts of Iraq). Reversed tendencies are found for the α412-470nm retrievals. For</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030102194','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030102194"><span id="translatedtitle">The <span class="hlt">MODIS</span> Aerosol Algorithm, Products and Validation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Mattoo, S.; Chu, D. A.; Martins, J. V.; Li, R.-R.; Ichoku, C.; Levy, R. C.; Kleidman, R. G.</p> <p>2003-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard both NASA's Terra and <span class="hlt">Aqua</span> satellites is making near global daily observations of the earth in a wide spectral range. These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode and several derived parameters including <span class="hlt">reflected</span> spectral solar flux at top of atmosphere. Over ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 microns to 2.13 microns. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral aerosol flux, mass concentration and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of AERONET data gleaned from 133 AERONET stations. 8000 <span class="hlt">MODIS</span> aerosol retrievals colocated with AERONET measurements confirm that one-standard deviation of <span class="hlt">MODIS</span> optical thickness retrievals fall within the predicted uncertainty of delta tauapproximately equal to plus or minus 0.03 plus or minus 0.05 tau over ocean and delta tay equal to plus or minus 0.05 plus or minus 0.15 tau over land. 271 <span class="hlt">MODIS</span> aerosol retrievals co-located with AERONET inversions at island and coastal sites suggest that one-standard deviation of <span class="hlt">MODIS</span> effective radius retrievals falls within delta r_eff approximately equal to 0.11 microns. The accuracy of the <span class="hlt">MODIS</span> retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRG..121..855P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRG..121..855P"><span id="translatedtitle">Retrieval of seasonal dynamics of forest understory <span class="hlt">reflectance</span> from semiarid to boreal forests using <span class="hlt">MODIS</span> BRDF data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pisek, Jan; Chen, Jing M.; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael E.; Karnieli, Arnon; Sprinstin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi</p> <p>2016-03-01</p> <p>Spatial and temporal patterns of forest background (understory) <span class="hlt">reflectance</span> are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional <span class="hlt">reflectance</span> distribution function (<span class="hlt">MODIS</span> BRDF)/albedo data. We compared satellite-based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N-31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..52..243R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..52..243R"><span id="translatedtitle">Monitoring water turbidity and surface suspended sediment concentration of the Bagre Reservoir (Burkina Faso) using <span class="hlt">MODIS</span> and field <span class="hlt">reflectance</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Robert, Elodie; Grippa, Manuela; Kergoat, Laurent; Pinet, Sylvain; Gal, Laetitia; Cochonneau, Gérard; Martinez, Jean-Michel</p> <p>2016-10-01</p> <p>Monitoring turbidity and Surface Suspended Sediment Concentration (SSSC) of inland waters is essential to address several important issues: erosion, sediment transport and deposition throughout watersheds, reservoir siltation, water pollution, human health risks, etc. This is especially important in regions with limited conventional monitoring capacities such as West Africa. In this study, we explore the use of Moderate Resolution Imaging Spectroradiometer data (<span class="hlt">MODIS</span>, MOD09Q1 and MYD09Q1 products, red (R) and near infrared (NIR) bands) to monitor turbidity and SSSC for the Bagre Reservoir in Burkina Faso. High values ​​of these parameters associated with high spatial and temporal variability potentially challenge the methodologies developed so far for less turbid waters. Field measurements (turbidity, SSSC, radiometry) are used to evaluate different radiometric indices. The NIR/R ratio is found to be the most suited to retrieve SSSC and turbidity for both in-situ spectoradiometer measurements and satellite <span class="hlt">reflectance</span> from <span class="hlt">MODIS</span>. The spatio temporal variability of <span class="hlt">MODIS</span> NIR/R together with rainfall estimated by the Tropical Rainforest Measuring Mission (TRMM) and altimetry data from Jason-2 is analyzed over the Bagre Reservoir for the 2000-2015 period. It is found that rain events of the early rainy season (February-March) through mid-rainy season (August) are decisive in triggering turbidity increase. Sediment transport is observed in the reservoir from upstream to downstream between June and September. Furthermore, a significant increase of 19% in turbidity values is observed between 2000 and 2015, mainly for the July to December period. It is especially well marked for August, with the central and downstream areas showing the largest increase. The most probable hypothesis to explain this evolution is a change in land use, and particularly an increase in the amount of bare soils, which enhances particle transport by runoff.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9639E..11A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9639E..11A"><span id="translatedtitle">Cross-calibration of the <span class="hlt">reflective</span> solar bands of Terra <span class="hlt">MODIS</span> and Landsat 7 Enhanced Thematic Mapper plus over PICS using different approaches</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Angal, Amit; Brinkmann, Jake; Mishra, Nischal; Link, Daniel; Xiong, Xiaoxiong J.; Helder, Dennis</p> <p>2015-10-01</p> <p>Both Terra <span class="hlt">MODIS</span> and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) have been successfully operating for over 15 years to collect valuable measurements of the earth's land, ocean, and atmosphere. The land-viewing bands of both sensors are widely used in several scientific products such as surface <span class="hlt">reflectance</span>, normalized difference vegetation index, enhanced vegetation index etc. A synergistic use of the multi-temporal measurements from both sensors can greatly benefit the science community. Previous effort from the <span class="hlt">MODIS</span> Characterization Support Team (MCST) was focused on comparing the top-of-atmosphere <span class="hlt">reflectance</span> of the two sensors over Libya 4 desert target. Uncertainties caused by the site/atmospheric BRDF, spectral response mismatch, and atmospheric water-vapor were also characterized. In parallel, an absolute calibration approach based on empirical observation was also developed for the Libya 4 site by the South Dakota State University's (SDSU) Image Processing Lab. Observations from Terra <span class="hlt">MODIS</span> and Earth Observing One (EO-1) Hyperion were used to model the Landsat ETM+ TOA <span class="hlt">reflectance</span>. Recently, there has been an update to the <span class="hlt">MODIS</span> calibration algorithm, which has resulted in the newly reprocessed Collection 6 Level 1B calibrated products. Similarly, a calibration update to some ETM+ bands has also resulted in long-term improvements of its calibration accuracy. With these updates, calibration differences between the spectrally matching bands of Terra <span class="hlt">MODIS</span> and L7 ETM+ over the Libya 4 site are evaluated using both approaches.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3892887','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3892887"><span id="translatedtitle">Comparability of Red/Near-Infrared <span class="hlt">Reflectance</span> and NDVI Based on the Spectral Response Function between <span class="hlt">MODIS</span> and 30 Other Satellite Sensors Using Rice Canopy Spectra</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing</p> <p>2013-01-01</p> <p>Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The <span class="hlt">reflectance</span> and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR <span class="hlt">reflectances</span> and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy <span class="hlt">reflectances</span> were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific <span class="hlt">reflectances</span> in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR <span class="hlt">reflectances</span>. The results showed that as compared to the Terra <span class="hlt">MODIS</span>, the mean relative percentage difference (RPD) ranged from −12.67% to 36.30% for the red <span class="hlt">reflectance</span>, −8.52% to −0.23% for the NIR <span class="hlt">reflectance</span>, and −9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra <span class="hlt">MODIS</span> ranged from 1.28% to 36.30% for the red <span class="hlt">reflectance</span>, 0.84% to 8.71% for the NIR <span class="hlt">reflectance</span>, and 0.59% to 9.32% for the NDVI. The lowest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for Landsat5 TM for the red <span class="hlt">reflectance</span>, CBERS02B CCD for the NIR <span class="hlt">reflectance</span> and Landsat4 TM for the NDVI. In addition, the largest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for IKONOS for the red <span class="hlt">reflectance</span>, AVHRR1 onboard NOAA8 for the NIR <span class="hlt">reflectance</span> and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24287529','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24287529"><span id="translatedtitle">Comparability of red/near-infrared <span class="hlt">reflectance</span> and NDVI based on the spectral response function between <span class="hlt">MODIS</span> and 30 other satellite sensors using rice canopy spectra.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing</p> <p>2013-11-26</p> <p>Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The <span class="hlt">reflectance</span> and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR <span class="hlt">reflectances</span> and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy <span class="hlt">reflectances</span> were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific <span class="hlt">reflectances</span> in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR <span class="hlt">reflectances</span>. The results showed that as compared to the Terra <span class="hlt">MODIS</span>, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red <span class="hlt">reflectance</span>, -8.52% to -0.23% for the NIR <span class="hlt">reflectance</span>, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra <span class="hlt">MODIS</span> ranged from 1.28% to 36.30% for the red <span class="hlt">reflectance</span>, 0.84% to 8.71% for the NIR <span class="hlt">reflectance</span>, and 0.59% to 9.32% for the NDVI. The lowest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for Landsat5 TM for the red <span class="hlt">reflectance</span>, CBERS02B CCD for the NIR <span class="hlt">reflectance</span> and Landsat4 TM for the NDVI. In addition, the largest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for IKONOS for the red <span class="hlt">reflectance</span>, AVHRR1 onboard NOAA8 for the NIR <span class="hlt">reflectance</span> and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110006350','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110006350"><span id="translatedtitle">Overview of NASA Earth Observing Systems Terra and <span class="hlt">Aqua</span> Moderate Resolution Imaging Spectroradiometer Instrument Calibration Algorithms and On-Orbit Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Wenny, Brian N.; Barnes, William L.</p> <p>2009-01-01</p> <p>Since launch, the Terra and <span class="hlt">Aqua</span> moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) instruments have successfully operated on-orbit for more than 9 and 6.5 years, respectively. Iv1ODIS, a key instrument for the NASA's Earth Observing System (EOS) missions, was designed to make continuous observations for studies of Earth's land, ocean, and atmospheric properties and to extend existing data records from heritage earth-observing sensors. In addition to frequent global coverage, <span class="hlt">MODIS</span> observations are made in 36 spectral bands, covering both solar <span class="hlt">reflective</span> and thermal emissive spectral regions. Nearly 40 data products are routinely generated from <span class="hlt">MODIS</span>' observations and publicly distributed for a broad range of applications. Both instruments have produced an unprecedented amount of data in support of the science community. As a general reference for understanding sensor operation and calibration, and thus science data quality, we ;provide an overview of the <span class="hlt">MODIS</span> instruments and their pre-launch calibration and characterization, and describe their on-orbit calibration algorithms and performance. On-orbit results from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> radiometric, spectral, and "spatial calibration are discussed. Currently, both instruments, including their on-board calibration devices, are healthy and are expected to continue operation for several }rears to come.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015744','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015744"><span id="translatedtitle">Evaluating the Assumptions of Surface <span class="hlt">Reflectance</span> and Aerosol Type Selection Within the <span class="hlt">MODIS</span> Aerosol Retrieval Over Land: The Problem of Dust Type Selection</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mielonen, T.; Levy, R. C.; Aaltonen, V.; Komppula, M.; de Leeuw, G.; Huttunen, J.; Lihavainen, H.; Kolmonen, P.; Lehtinen, K. E. J.; Arola, A.</p> <p>2011-01-01</p> <p>Aerosol Optical Depth (AOD) and Angstrom exponent (AE) values derived with the <span class="hlt">MODIS</span> retrieval algorithm over land (Collection 5) are compared with ground based sun photometer measurements at eleven sites spanning the globe. Although, in general, total AOD compares well at these sites (R2 values generally over 0.8), there are cases (from 2 to 67% of the measurements depending on the site) where <span class="hlt">MODIS</span> clearly retrieves the wrong spectral dependence, and hence, an unrealistic AE value. Some of these poor AE retrievals are due to the aerosol signal being too small (total AOD<0.3) but in other cases the AOD should have been high enough to derive accurate AE. However, in these cases, <span class="hlt">MODIS</span> indicates AE values close to 0.6 and zero fine model weighting (FMW), i.e. dust model provides the best fitting to the <span class="hlt">MODIS</span> observed <span class="hlt">reflectance</span>. Yet, according to evidence from the collocated sun photometer measurements and back-trajectory analyses, there should be no dust present. This indicates that the assumptions about aerosol model and surface properties made by the <span class="hlt">MODIS</span> algorithm may have been incorrect. Here we focus on problems related to parameterization of the land-surface optical properties in the algorithm, in particular the relationship between the surface <span class="hlt">reflectance</span> at 660 and 2130 nm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070031724&hterms=chapter&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dchapter','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070031724&hterms=chapter&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dchapter"><span id="translatedtitle">Introduction to <span class="hlt">MODIS</span> Cloud Products. Chapter 5</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baum, Bryan A.; Platnick, Steven</p> <p>2006-01-01</p> <p>The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) imagers on the Terra and <span class="hlt">Aqua</span> Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar <span class="hlt">reflectance</span> and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental Satellite (GOES), <span class="hlt">MODIS</span> provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core <span class="hlt">MODIS</span> operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the <span class="hlt">MODIS</span> atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing satellite-based cloud climatologies</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70010012','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70010012"><span id="translatedtitle"><span class="hlt">MODIS</span> and SeaWIFS on-orbit lunar calibration</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Sun, Jielun; Eplee, R.E.; Xiong, X.; Stone, T.; Meister, G.; McClain, C.R.</p> <p>2008-01-01</p> <p>The Moon plays an important role in the radiometric stability monitoring of the NASA Earth Observing System's (EOS) remote sensors. The <span class="hlt">MODIS</span> and SeaWIFS are two of the key instruments for NASA's EOS missions. The <span class="hlt">MODIS</span> Protoflight Model (PFM) on-board the Terra spacecraft and the <span class="hlt">MODIS</span> Flight Model 1 (FM1) on-board the <span class="hlt">Aqua</span> spacecraft were launched on December 18, 1999 and May 4, 2002, respectively. They view the Moon through the Space View (SV) port approximately once a month to monitor the long-term radiometric stability of their <span class="hlt">Reflective</span> Solar Bands (RSB). SeaWIFS was launched on-board the OrbView-2 spacecraft on August 1, 1997. The SeaWiFS lunar calibrations are obtained once a month at a nominal phase angle of 7??. The lunar irradiance observed by these instruments depends on the viewing geometry. The USGS photometric model of the Moon (the ROLO model) has been developed to provide the geometric corrections for the lunar observations. For <span class="hlt">MODIS</span>, the lunar view responses with corrections for the viewing geometry are used to track the gain change for its <span class="hlt">reflective</span> solar bands (RSB). They trend the system response degradation at the Angle Of Incidence (AOI) of sensor's SV port. With both the lunar observation and the on-board Solar Diffuser (SD) calibration, it is shown that the <span class="hlt">MODIS</span> system response degradation is wavelength, mirror side, and AOI dependent. Time-dependent Response Versus Scan angle (RVS) Look-Up Tables (LUT) are applied in <span class="hlt">MODIS</span> RSB calibration and lunar observations play a key role in RVS derivation. The corrections provided by the RVS in the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data from the 412 nm band are as large as 16% and 13%, respectively. For SeaWIFS lunar calibrations, the spacecraft is pitched across the Moon so that the instrument views the Moon near nadir through the same optical path as it views the Earth. The SeaWiFS system gain changes for its eight bands are calibrated using the geometrically-corrected lunar observations. The radiometric</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.5138P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.5138P"><span id="translatedtitle">Retrieval of seasonal dynamics of forest understory <span class="hlt">reflectance</span> from semi-arid to boreal forests using <span class="hlt">MODIS</span> BRDF data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pisek, Jan; Chen, Jing; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael; Karnieli, Arnon; Sprintsin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi</p> <p>2016-04-01</p> <p>Ground vegetation (understory) provides an essential contribution to the whole-stand <span class="hlt">reflectance</span> signal in many boreal, sub-boreal, and temperate forests. Accurate knowledge about forest understory <span class="hlt">reflectance</span> is urgently needed in various forest <span class="hlt">reflectance</span> modelling efforts. However, systematic collections of understory <span class="hlt">reflectance</span> data covering different sites and ecosystems are almost missing. Measurement of understory <span class="hlt">reflectance</span> is a real challenge because of an extremely high variability of irradiance at the forest floor, weak signal in some parts of the spectrum, spectral separability issues of over- and understory and its variable nature. Understory can consist of several sub-layers (regenerated tree, shrub, grasses or dwarf shrub, mosses, lichens, litter, bare soil), it has spatially-temporally variable species composition and ground coverage. Additional challenges are introduced by patchiness of ground vegetation, ground surface roughness, and understory-overstory relations. Due to this variability, remote sensing might be the only means to provide consistent data at spatially relevant scales. In this presentation, we report on retrieving seasonal courses of understory Normalized Difference Vegetation Index (NDVI) from multi-angular <span class="hlt">MODIS</span> BRDF/Albedo data. We compared satellite-based seasonal courses of understory NDVI against an extended collection of different types of forest sites with available in-situ understory <span class="hlt">reflectance</span> measurements. These sites are distributed along a wide latitudinal gradient on the Northern hemisphere: a sparse and dense black spruce forests in Alaska and Canada, a northern European boreal forest in Finland, hemiboreal needleleaf and deciduous stands in Estonia, a mixed temperate forest in Switzerland, a cool temperate deciduous broadleaf forest in Korea, and a semi-arid pine plantation in Israel. Our results indicated the retrieval method performs well particularly over open forests of different types. We also demonstrated</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005181&hterms=orbit&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dorbit','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005181&hterms=orbit&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dorbit"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> and VIIRS Solar Diffuser On-Orbit Degradation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Fulbright, Jon; Angal, Amit; Wang, Zhipeng; Geng, Xu; Butler, Jim</p> <p>2015-01-01</p> <p>Both <span class="hlt">MODIS</span> and VIIRS instruments use a solar diffuser (SD) for their <span class="hlt">reflective</span> solar bands (RSB) on-orbit calibration. On-orbit changes in SD bi-directional <span class="hlt">reflectance</span> factor (BRF) are tracked by a solar diffuser stability monitor (SDSM) using its alternate measurements of the sunlight <span class="hlt">reflected</span> off the SD panel and direct sunlight through a fixed attenuation screen. The SDSM calibration data are collected by a number of filtered detectors, covering wavelengths from 0.41 to 0.94 micrometers. In this paper we describe briefly the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and S-NPP VIIRS SDSM on-orbit operation and calibration activities and strategies, provide an overall assessment of their SDSM on-orbit performance, including wavelength-dependent changes in the SDSM detector responses and changes in their SD BRF, and discuss remaining challenging issues and their potential impact on RSB calibration quality. Due to different launch dates, operating configurations, and calibration frequencies, the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and S-NPP VIIRS SD have experienced different amount of SD degradation. However, in general the shorter the wavelength, the larger is the SD on-orbit degradation. On the other hand, the larger changes in SDSM detector responses are observed at longer wavelengths in the near infrared (NIR).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010SPIE.7807E..0GD','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010SPIE.7807E..0GD"><span id="translatedtitle">Space environment's effect on <span class="hlt">MODIS</span> calibration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dodd, J. L.; Wenny, B. N.; Chiang, K.; Xiong, X.</p> <p>2010-09-01</p> <p>The MODerate resolution Imaging Spectroradiometer flies on board the Earth Observing System (EOS) satellites Terra and <span class="hlt">Aqua</span> in a sun-synchronous orbit that crosses the equator at 10:30 AM and 2:30 PM, respectively, at a low earth orbit (LEO) altitude of 705 km. Terra was launched on December 18,1999 and <span class="hlt">Aqua</span> was launched on May 4, 2002. As the <span class="hlt">MODIS</span> instruments on board these satellites continue to operate beyond the design lifetime of six years, the cumulative effect of the space environment on <span class="hlt">MODIS</span> and its calibration is of increasing importance. There are several aspects of the space environment that impact both the top of atmosphere (TOA) calibration and, therefore, the final science products of <span class="hlt">MODIS</span>. The south Atlantic anomaly (SAA), spacecraft drag, extreme radiative and thermal environment, and the presence of orbital debris have the potential to significantly impact both <span class="hlt">MODIS</span> and the spacecraft, either directly or indirectly, possibly resulting in data loss. Efforts from the Terra and <span class="hlt">Aqua</span> Flight Operations Teams (FOT), the <span class="hlt">MODIS</span> Instrument Operations Team (IOT), and the <span class="hlt">MODIS</span> Characterization Support Team (MCST) prevent or minimize external impact on the TOA calibrated data. This paper discusses specific effects of the space environment on <span class="hlt">MODIS</span> and how they are minimized.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/544116','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/544116"><span id="translatedtitle">The <span class="hlt">MODIS</span> 2.1-{micro}m channel -- correlation with visible <span class="hlt">reflectance</span> for use in remote sensing of aerosol</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Kaufman, Y.J.; Wald, A.E.; Remer, L.A.; Li, R.R.; Gao, B.C.; Flynn, L.</p> <p>1997-09-01</p> <p>A new technique for remote sensing of aerosol over the land and for atmospheric correction of Earth imagery is developed. It is based on detection of dark surface targets in the blue and red channels, as in previous methods, but uses the 2.1-{micro}m channel, instead of the 3.75 {micro}m for their detection. A 2.1-{micro}m channel is present on ADEOS OCTS and GLI, and planned on EOS-<span class="hlt">MODIS</span> and EOSP, and a similar 2.2-{micro}m channel is present on Landsat TM. The advantage of the 2.1-{micro}m channel over the 3.75-{micro}m channel is that it is not affected by emitted radiation. The 2.1-{micro}m channel is transparent to most aerosol types (except dust) and therefore can be used to detect dark surface targets. Correlation between the surface <span class="hlt">reflection</span> in the blue (0.49 {micro}m), red (0.66 {micro}m), and 2.1 {micro}m is established using atmospherically corrected Landsat TM and AVIRIS aircraft images collected over the Eastern United States, Maine, and California and spectral data obtained from the ground and light aircraft near San Diego, CA.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000033817','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000033817"><span id="translatedtitle">Sensitivity of Cirrus Bidirectional <span class="hlt">Reflectance</span> at <span class="hlt">MODIS</span> Bands to Vertical Inhomogeneity of Ice Crystal Habits and Size Distribution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, P.; Gao, B.-C.; Baum, B. A.; Wiscombe, W.; Hu, Y.; Nasiri, S. L.; Soulen, P. F.; Heymsfield, A. J.; McFarquhar, G. M.; Miloshevich, L. M.</p> <p>2000-01-01</p> <p>A common assumption in satellite imager-based cirrus retrieval algorithms is that the radiative properties of a cirrus cloud may be represented by those associated with a specific ice crystal shape (or habit) and a single particle size distribution. However, observations of cirrus clouds have shown that the shapes and sizes of ice crystals may vary substantially with height within the clouds. In this study we investigate the sensitivity of the top-of-atmosphere bidirectional <span class="hlt">reflectances</span> at two <span class="hlt">MODIS</span> bands centered at 0.65 micron and 2.11 micron to the cirrus models assumed to be either a single homogeneous layer or three distinct but contiguous, layers. First, we define the single- and three-layer cirrus cloud models with respect to ice crystal habit and size distribution on the basis of in situ replicator data acquired during the First ISCCP Regional Experiment (FIRE-II), held in Kansas during the fall of 1991. Subsequently, fundamental light scattering and radiative transfer theory is employed to determine the single scattering and the bulk radiative properties of the cirrus cloud. Regarding the radiative transfer computations, we present a discrete form of the adding/doubling principle by introducing a direct transmission function, which is computationally straightforward and efficient an improvement over previous methods. For the 0.65 micron band, at which absorption by ice is negligible, there is little difference between the bidirectional <span class="hlt">reflectances</span> calculated for the one- and three-layer cirrus models, suggesting that the vertical inhomogeneity effect is relatively unimportant. At the 2.11 micron band, the bidirectional <span class="hlt">reflectances</span> computed for both optically thin (tau = 1) and thick (tau = 10) cirrus clouds show significant differences between the results for the one- and three-layer models. The <span class="hlt">reflectances</span> computed for the three-layer cirrus model are substantially larger than those computed for the single-layer cirrus. Finally, we find that cloud</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030112964&hterms=lighthouse&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dlighthouse','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030112964&hterms=lighthouse&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dlighthouse"><span id="translatedtitle">Towards Improved <span class="hlt">MODIS</span> Aerosol Retrieval over the US East Coast Region: Re-examining the Aerosol Model and Surface Assumptions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Levy, R. C.; Remer, L. A.; Kaufman, Y. J.; Holben, B. N.</p> <p>2002-01-01</p> <p>The MODerate resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) aboard the Terra and recently the <span class="hlt">Aqua</span> platform, produces a set of aerosol products over both ocean and land regions. Previous validation efforts have shown that from a global perspective, aerosol optical depth (AOD) is successfully retrieved from <span class="hlt">MODIS</span>. Even over coastal regions, the over- land and over-ocean retrievals are consistent with each other, and well matched with ground-based sunphotometer measurements (such as AERONET). However, the East Coast of the United States is one region where there is consistently a discrepancy between land and ocean retrievals. Over the ocean, <span class="hlt">MODIS</span> AODs are consistent with coastal sunphotometer measurements, but over land, AODs are consistently over- estimated. In this study we use field data from the Chesapeake Lighthouse and Aircraft Measurements for Satellites experiment (CLAMS), (held during summer 2001) to determine the aerosol properties at a number of sites. Using the 6-S radiative transfer package, we compute simulated satellite radiances and compare them with observed <span class="hlt">MODIS</span> radiances. We believe that the AOD over-estimation is not likely due to an incorrect choice of the urban/industrial aerosol models. Using 6-S to do an atmospheric correction for a very low AOD case, we show rather, that the discrepancies are likely a result of incorrect assumptions about the surface <span class="hlt">reflectance</span> properties. Understanding and improving <span class="hlt">MODIS</span> retrievals over the East Coast will not only improve the global quality of <span class="hlt">MODIS</span>, but also would enable the use of <span class="hlt">MODIS</span> as a tool for monitoring regional aerosol events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15559823','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15559823"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span> aerosol retrievals and evaluation of potential cloud contamination in East Asia.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Xia, Xiang-Ao; Chen, Hong-Bin; Wang, Pu-Cai</p> <p>2004-01-01</p> <p><span class="hlt">MODIS</span> aerosol retrievals onboard Terra/<span class="hlt">Aqua</span> and ground truth data obtained from AERONET (Aerosol Robtic Network) solar direct radiance measurements are collocated to evaluate the quality of the former in East Asia. AERONET stations in East Asia are separated into two groups according to their locations and the preliminary validation results for each station. The validation results showed that the accuracy of <span class="hlt">MODIS</span> aerosol retrievals in East Asia is a little worse than that obtained in other regions such as Eastern U.S., Western Europe, Brazil and so on. The primary reason is due to the improper aerosol model used in <span class="hlt">MODIS</span> aerosol retrieval algorithm, so it is of significance to characterize aerosol properties properly according to long-term ground-based remote sensing or other relevant in situ observations in order to improve <span class="hlt">MODIS</span> retrievals in East Asia. Cloud contamination is proved to be one of large errors, which is demonstrated by the significant relation between <span class="hlt">MODIS</span> aerosol retrievals versus cloud fraction, as well as notable improvement of linear relation between satellite and ground aerosol data after potential cloud contamination screened. Hence, it is suggested that more stringent clear sky condition be set in use of <span class="hlt">MODIS</span> aerosol data. It should be pointed out that the improvement might be offset by other error sources in some cases because of complex relation between different errors. Large seasonal variation of surface <span class="hlt">reflection</span> and uncertainties associated with it result in large intercepts and random error in <span class="hlt">MODIS</span> aerosol retrievals in northern inland of East Asia. It remains to be a big problem to retrieve aerosols accurately in inland characterized by relatively larger surface <span class="hlt">reflection</span> than the requirement in <span class="hlt">MODIS</span> aerosol retrieval algorithm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A33M0338G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A33M0338G"><span id="translatedtitle">Operationalizing a Research Sensor: <span class="hlt">MODIS</span> to VIIRS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grant, K. D.; Miller, S. W.; Puschell, J.</p> <p>2012-12-01</p> <p>The National Oceanic and Atmospheric Administration (NOAA) and NASA are jointly acquiring the next-generation civilian environmental satellite system: the Joint Polar Satellite System (JPSS). JPSS will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA. The JPSS satellite will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The primary sensor for the JPSS mission is the Visible/Infrared Imager Radiometer Suite (VIIRS) developed by Raytheon Space and Airborne Systems (SAS). The ground processing system for the JPSS mission is known as the Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS) which are both developed by Raytheon Intelligence and Information Systems (IIS). The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by Raytheon SAS for the NASA Earth Observing System (EOS) as a research instrument to capture data in 36 spectral bands, ranging in wavelength from 0.4 μm to 14.4 μm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). <span class="hlt">MODIS</span> data provides unprecedented insight into large-scale Earth system science questions related to cloud and aerosol characteristics, surface emissivity and processes occurring in the oceans, on land, and in the lower atmosphere. <span class="hlt">MODIS</span> has flown on the EOS Terra satellite since 1999 and on the EOS <span class="hlt">Aqua</span> satellite since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of <span class="hlt">MODIS</span>-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to <span class="hlt">MODIS</span> for the next-generation polar-orbiting environmental satellites, the Visible/Infrared Imager</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUSM.A21A..09A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUSM.A21A..09A"><span id="translatedtitle"><span class="hlt">MODIS</span> Radiances for Earth System Science Studies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ahmad, S. P.; Salomonson, V. V.; Barnes, W. L.; Xiong, X.; Leptoukh, G. G.; Serafino, G. N.</p> <p>2002-05-01</p> <p><span class="hlt">MODIS</span>, a major NASA's Earth Observing System (EOS) instrument, was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) for global monitoring of the atmosphere, the terrestrial ecosystems and oceans, to develop better understanding of the 'Total Earth System', and to study the effects of natural and human-induced changes on the global environment. <span class="hlt">MODIS</span> with its 2330 km viewing swath width provides almost daily global coverage. It acquires data in 36 high spectral resolution bands between 0.415 and 14.235 micron with spatial resolutions of 250 m (2 bands), 500 m (5 bands), and 1000 m (29 bands). This year a similar instrument will be flown on the EOS-<span class="hlt">Aqua</span> satellite (1:30 pm equator crossing time). This will enable us to study diurnal variation of the rapidly varying systems. The radiance data measured by <span class="hlt">MODIS</span> at high spatial resolution with some new channels (never used before for remote sensing from space) provides improved and valuable information about the physical structure of the Earth system, such as vertical distribution of temperature and humidity, cloud and aerosol characteristics, sources and sinks of trace gases, surface emissivity, land and sea surface temperature, land cover and primary productivity, snow cover and sea ice concentration, glacier and polar ice sheets, ocean currents, ocean color, and phytoplankton. Almost all key climate and environmental parameters are available as standard <span class="hlt">MODIS</span> products and are derived from <span class="hlt">MODIS</span> high spatial resolution radiances. However, these radiometrically corrected and geolocated high spatial resolution radiance data (referred as Level 1B product) are much in demand by the science user community. These radiances are needed to enhance existing algorithms, to test new algorithms for the retrieval of existing or new parameters, and for developing simulation datasets for characterization of new sensors. <span class="hlt">MODIS</span> radiance counts, calibrated radiance/<span class="hlt">reflectance</span>, geolocation</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030020719&hterms=Remote+Viewing&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DRemote%2BViewing','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030020719&hterms=Remote+Viewing&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DRemote%2BViewing"><span id="translatedtitle">Remote Sensing of Cloud, Aerosol, and Land Properties from <span class="hlt">MODIS</span>: Applications to the East Asia Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Moody, Eric G.</p> <p>2002-01-01</p> <p><span class="hlt">MODIS</span> is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999 and the <span class="hlt">Aqua</span> satellite in May 2002. <span class="hlt">MODIS</span> scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using <span class="hlt">MODIS</span> data, focusing primarily on (i) the <span class="hlt">MODIS</span> cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral <span class="hlt">reflectance</span>. The physical principles behind the determination of each of these products will be described, together with an example of their application using <span class="hlt">MODIS</span> observations to the east Asian region. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 min (Level-3 products).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2008/3061/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2008/3061/"><span id="translatedtitle">Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Overview</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>,</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is an instrument that collects remotely sensed data used by scientists for monitoring, modeling, and assessing the effects of natural processes and human actions on the Earth's surface. The continual calibration of the <span class="hlt">MODIS</span> instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make <span class="hlt">MODIS</span> images a valuable time series (2000-present) of geophysical and biophysical land-surface measurements. Carried on two National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellites, <span class="hlt">MODIS</span> acquires morning (EOS-Terra) and afternoon (EOS-<span class="hlt">Aqua</span>) views almost daily. Terra data acquisitions began in February 2000 and <span class="hlt">Aqua</span> data acquisitions began in July 2002. Land data are generated only as higher-level products, removing the burden of common types of data processing from the user community. <span class="hlt">MODIS</span>-based products describing ecological dynamics, radiation budget, and land cover are projected onto a sinusoidal mapping grid and distributed as 10- by 10-degree tiles at 250-, 500-, or 1,000-meter spatial resolution. Some products are also created on a 0.05-degree geographic grid to support climate modeling studies. All <span class="hlt">MODIS</span> products are distributed in the Hierarchical Data Format-Earth Observing System (HDF-EOS) file format and are available through file transfer protocol (FTP) or on digital video disc (DVD) media. Versions 4 and 5 of <span class="hlt">MODIS</span> land data products are currently available and represent 'validated' collections defined in stages of accuracy that are based on the number of field sites and time periods for which the products have been validated. Version 5 collections incorporate the longest time series of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007087','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007087"><span id="translatedtitle">Trends in <span class="hlt">MODIS</span> Geolocation Error Analysis</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wolfe, R. E.; Nishihama, Masahiro</p> <p>2009-01-01</p> <p>Data from the two <span class="hlt">MODIS</span> instruments have been accurately geolocated (Earth located) to enable retrieval of global geophysical parameters. The authors describe the approach used to geolocate with sub-pixel accuracy over nine years of data from M0DIS on NASA's E0S Terra spacecraft and seven years of data from <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> spacecraft. The approach uses a geometric model of the <span class="hlt">MODIS</span> instruments, accurate navigation (orbit and attitude) data and an accurate Earth terrain model to compute the location of each <span class="hlt">MODIS</span> pixel. The error analysis approach automatically matches <span class="hlt">MODIS</span> imagery with a global set of over 1,000 ground control points from the finer-resolution Landsat satellite to measure static biases and trends in the MO0lS geometric model parameters. Both within orbit and yearly thermally induced cyclic variations in the pointing have been found as well as a general long-term trend.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.H32B..04U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.H32B..04U"><span id="translatedtitle">The <span class="hlt">MODIS</span> Vegetation Canopy Water Content product</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ustin, S. L.; Riano, D.; Trombetti, M.</p> <p>2008-12-01</p> <p>Vegetation water stress drives wildfire behavior and risk, having important implications for biogeochemical cycling in natural ecosystems, agriculture, and forestry. Water stress limits plant transpiration and carbon gain. The regulation of photosynthesis creates close linkages between the carbon, water, and energy cycles and through metabolism to the nitrogen cycle. We generated systematic weekly CWC estimated for the USA from 2000-2006. <span class="hlt">MODIS</span> measures the sunlit <span class="hlt">reflectance</span> of the vegetation in the visible, near-infrared, and shortwave infrared. Radiative transfer models, such as PROSPECT-SAILH, determine how sunlight interacts with plant and soil materials. These models can be applied over a range of scales and ecosystem types. Artificial Neural Networks (ANN) were used to optimize the inversion of these models to determine vegetation water content. We carried out multi-scale validation of the product using field data, airborne and satellite cross-calibration. An Algorithm Theoretical Basis Document (ATBD) of the product is under evaluation by NASA. The CWC product inputs are 1) The <span class="hlt">MODIS</span> Terra/<span class="hlt">Aqua</span> surface <span class="hlt">reflectance</span> product (MOD09A1/MYD09A1) 2) The <span class="hlt">MODIS</span> land cover map product (MOD12Q1) reclassified to grassland, shrub-land and forest canopies; 3) An ANN trained with PROSPECT-SAILH; 4) A calibration file for each land cover type. The output is an ENVI file with the CWC values. The code is written in Matlab environment and is being adapted to read not only the 8 day <span class="hlt">MODIS</span> composites, but also daily surface <span class="hlt">reflectance</span> data. We plan to incorporate the cloud and snow mask and generate as output a geotiff file. Vegetation water content estimates will help predicting linkages between biogeochemical cycles, which will enable further understanding of feedbacks to atmospheric concentrations of greenhouse gases. It will also serve to estimate primary productivity of the biosphere; monitor/assess natural vegetation health related to drought, pollution or diseases</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009SPIE.7452E..0MX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009SPIE.7452E..0MX"><span id="translatedtitle">On-orbit operation and performance of <span class="hlt">MODIS</span> blackbody</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, X.; Chang, T.; Barnes, W.</p> <p>2009-08-01</p> <p><span class="hlt">MODIS</span> collects data in 36 spectral bands, including 20 <span class="hlt">reflective</span> solar bands (RSB) and 16 thermal emissive bands (TEB). The TEB on-orbit calibration is performed on a scan-by-scan basis using a quadratic algorithm that relates the detector response with the calibration radiance from the sensor on-board blackbody (BB). The calibration radiance is accurately determined each scan from the BB temperature measured using a set of 12 thermistors. The BB thermistors were calibrated pre-launch with traceability to the NIST temperature standard. Unlike many heritage sensors, the <span class="hlt">MODIS</span> BB can be operated at a constant temperature or with the temperature continuously varying between instrument ambient (about 270K) and 315K. In this paper, we provide an overview of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-board BB operations, functions, and on-orbit performance. We also examine the impact of key calibration parameters, such as BB emissivity and temperature (stability and gradient) determined from its thermistors, on the TEB calibration and Level 1 (L1B) data product uncertainty.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110006383','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110006383"><span id="translatedtitle">On-Orbit Operation and Performance of <span class="hlt">MODIS</span> Blackbody</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Chang, T.; Barnes, W.</p> <p>2009-01-01</p> <p><span class="hlt">MODIS</span> collects data in 36 spectral bands, including 20 <span class="hlt">reflective</span> solar bands (RSB) and 16 thermal emissive bands (TES). The TEB on-orbit calibration is performed on a scan-by-scan basis using a quadratic algorithm that relates the detector response with the calibration radiance from the sensor on-board blackbody (BB). The calibration radiance is accurately determined each scan from the BB temperature measured using a set of 12 thermistors. The BB thermistors were calibrated pre-launch with traceability to the NIST temperature standard. Unlike many heritage sensors, the <span class="hlt">MODIS</span> BB can be operated at a constant temperature or with the temperature continuously varying between instrument ambient (about 270K) and 315K. In this paper, we provide an overview of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-board BB operations, functions, and on-orbit performance. We also examine the impact of key calibration parameters, such as BB emissivity and temperature (stability and gradient) determined from its thermistors, on the TEB calibration and Level I (LIB) data product uncertainty.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060047447','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060047447"><span id="translatedtitle">Status of the <span class="hlt">MODIS</span> Level 1B Algorithms and Calibration Tables</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X; Salomonson, V V; Kuyper, J; Tan, L; Chiang, K; Sun, J; Barnes, W L</p> <p>2005-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellites, launched in December 1999 and May 2002, respectively. The <span class="hlt">MODIS</span> Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) <span class="hlt">reflectance</span> factors for the sensor's <span class="hlt">reflective</span> solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the <span class="hlt">MODIS</span> L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the <span class="hlt">MODIS</span> collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.4783C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.4783C"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> RSB detector uniformity using deep convective clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen</p> <p>2016-05-01</p> <p>For satellite sensor, the striping observed in images is typically associated with the relative multiple detector gain difference derived from the calibration. A method using deep convective cloud (DCC) measurements to assess the difference among detectors after calibration is proposed and demonstrated for select <span class="hlt">reflective</span> solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Each detector of <span class="hlt">MODIS</span> RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra <span class="hlt">MODIS</span> Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most <span class="hlt">Aqua</span> bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for <span class="hlt">MODIS</span> band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to <span class="hlt">reflectance</span> images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160007849&hterms=cloud&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dcloud','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160007849&hterms=cloud&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dcloud"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> RSB Detector Uniformity Using Deep Convective Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen</p> <p>2016-01-01</p> <p>For satellite sensor, the striping observed in images is typically associated with the relative multiple detector gain difference derived from the calibration. A method using deep convective cloud (DCC) measurements to assess the difference among detectors after calibration is proposed and demonstrated for select <span class="hlt">reflective</span> solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Each detector of <span class="hlt">MODIS</span> RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra <span class="hlt">MODIS</span> Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most <span class="hlt">Aqua</span> bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for <span class="hlt">MODIS</span> band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to <span class="hlt">reflectance</span> images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21068859','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21068859"><span id="translatedtitle">Point-spread function of the ocean color bands of the Moderate Resolution Imaging Spectroradiometer on <span class="hlt">Aqua</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Meister, Gerhard; McClain, Charles R</p> <p>2010-11-10</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the <span class="hlt">Aqua</span> platform has nine spectral bands with center wavelengths from 412 to 870 nm that are used to produce the standard ocean color data products. Ocean scenes usually contain high contrast due to the presence of bright clouds over dark water. About half of the <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> ocean pixels are flagged as spatial stray light contaminated. The <span class="hlt">MODIS</span> has been characterized for stray light effects prelaunch. In this paper, we derive point-spread functions for the <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> ocean bands based on prelaunch line-spread function measurements. The stray light contamination of ocean scenes is evaluated based on artificial test scenes and on-orbit data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100020840','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100020840"><span id="translatedtitle"><span class="hlt">MODIS</span> On-Board Blackbody Function and Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiaoxiong, Xiong; Wenny, Brian N.; Wu, Aisheng; Barnes, William</p> <p>2009-01-01</p> <p>Two <span class="hlt">MODIS</span> instruments are currently in orbit, making continuous global observations in visible to long-wave infrared wavelengths. Compared to heritage sensors, <span class="hlt">MODIS</span> was built with an advanced set of on-board calibrators, providing sensor radiometric, spectral, and spatial calibration and characterization during on-orbit operation. For the thermal emissive bands (TEB) with wavelengths from 3.7 m to 14.4 m, a v-grooved blackbody (BB) is used as the primary calibration source. The BB temperature is accurately measured each scan (1.47s) using a set of 12 temperature sensors traceable to NIST temperature standards. The onboard BB is nominally operated at a fixed temperature, 290K for Terra <span class="hlt">MODIS</span> and 285K for <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, to compute the TEB linear calibration coefficients. Periodically, its temperature is varied from 270K (instrument ambient) to 315K in order to evaluate and update the nonlinear calibration coefficients. This paper describes <span class="hlt">MODIS</span> on-board BB functions with emphasis on on-orbit operation and performance. It examines the BB temperature uncertainties under different operational conditions and their impact on TEB calibration and data product quality. The temperature uniformity of the BB is also evaluated using TEB detector responses at different operating temperatures. On-orbit results demonstrate excellent short-term and long-term stability for both the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-board BB. The on-orbit BB temperature uncertainty is estimated to be 10mK for Terra <span class="hlt">MODIS</span> at 290K and 5mK for <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> at 285K, thus meeting the TEB design specifications. In addition, there has been no measurable BB temperature drift over the entire mission of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.U41B0013G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.U41B0013G"><span id="translatedtitle"><span class="hlt">Aqua</span> Education and Public Outreach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Graham, S. M.; Parkinson, C. L.; Chambers, L. H.; Ray, S. E.</p> <p>2011-12-01</p> <p>NASA's <span class="hlt">Aqua</span> satellite was launched on May 4, 2002, with six instruments designed to collect data about the Earth's atmosphere, biosphere, hydrosphere, and cryosphere. Since the late 1990s, the <span class="hlt">Aqua</span> mission has involved considerable education and public outreach (EPO) activities, including printed products, formal education, an engineering competition, webcasts, and high-profile multimedia efforts. The printed products include <span class="hlt">Aqua</span> and instrument brochures, an <span class="hlt">Aqua</span> lithograph, <span class="hlt">Aqua</span> trading cards, NASA Fact Sheets on <span class="hlt">Aqua</span>, the water cycle, and weather forecasting, and an <span class="hlt">Aqua</span> science writers' guide. On-going formal education efforts include the Students' Cloud Observations On-Line (S'COOL) Project, the MY NASA DATA Project, the Earth System Science Education Alliance, and, in partnership with university professors, undergraduate student research modules. Each of these projects incorporates <span class="hlt">Aqua</span> data into its inquiry-based framework. Additionally, high school and undergraduate students have participated in summer internship programs. An earlier formal education activity was the <span class="hlt">Aqua</span> Engineering Competition, which was a high school program sponsored by the NASA Goddard Space Flight Center, Morgan State University, and the Baltimore Museum of Industry. The competition began with the posting of a Round 1 <span class="hlt">Aqua</span>-related engineering problem in December 2002 and concluded in April 2003 with a final round of competition among the five finalist teams. The <span class="hlt">Aqua</span> EPO efforts have also included a wide range of multimedia products. Prior to launch, the <span class="hlt">Aqua</span> team worked closely with the Special Projects Initiative (SPI) Office to produce a series of live webcasts on <span class="hlt">Aqua</span> science and the Cool Science website <span class="hlt">aqua</span>.nasa.gov/coolscience, which displays short video clips of <span class="hlt">Aqua</span> scientists and engineers explaining the many aspects of the <span class="hlt">Aqua</span> mission. These video clips, the <span class="hlt">Aqua</span> website, and numerous presentations have benefited from dynamic visualizations showing the <span class="hlt">Aqua</span> launch</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080023286','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080023286"><span id="translatedtitle"><span class="hlt">MODIS</span> Land Data Products: Generation, Quality Assurance and Validation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Masuoka, Edward; Wolfe, Robert; Morisette, Jeffery; Sinno, Scott; Teague, Michael; Saleous, Nazmi; Devadiga, Sadashiva; Justice, Christopher; Nickeson, Jaime</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) on-board NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> Satellites are key instruments for providing data on global land, atmosphere, and ocean dynamics. Derived <span class="hlt">MODIS</span> land, atmosphere and ocean products are central to NASA's mission to monitor and understand the Earth system. NASA has developed and generated on a systematic basis a suite of <span class="hlt">MODIS</span> products starting with the first Terra <span class="hlt">MODIS</span> data sensed February 22, 2000 and continuing with the first <span class="hlt">MODIS-Aqua</span> data sensed July 2, 2002. The <span class="hlt">MODIS</span> Land products are divided into three product suites: radiation budget products, ecosystem products, and land cover characterization products. The production and distribution of the <span class="hlt">MODIS</span> Land products are described, from initial software delivery by the <span class="hlt">MODIS</span> Land Science Team, to operational product generation and quality assurance, delivery to EOS archival and distribution centers, and product accuracy assessment and validation. Progress and lessons learned since the first <span class="hlt">MODIS</span> data were in early 2000 are described.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AMT.....9.3193S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AMT.....9.3193S"><span id="translatedtitle">Comparison of <span class="hlt">MODIS</span> and VIIRS cloud properties with ARM ground-based observations over Finland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sporre, Moa K.; O'Connor, Ewan J.; Håkansson, Nina; Thoss, Anke; Swietlicki, Erik; Petäjä, Tuukka</p> <p>2016-07-01</p> <p>Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments aboard the satellites Terra and <span class="hlt">Aqua</span> and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols - Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). <span class="hlt">MODIS</span> collection 6 overestimated LWP by on average 13 g m-2 (11 %). Interestingly, LWP for <span class="hlt">MODIS</span> collection 5.1 is slightly overestimated by <span class="hlt">Aqua</span> (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the <span class="hlt">reflectance</span> bands of the <span class="hlt">MODIS</span> instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70173626','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70173626"><span id="translatedtitle">High-frequency remote monitoring of large lakes with <span class="hlt">MODIS</span> 500 m imagery</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.</p> <p>2012-01-01</p> <p>Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30 m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16 days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on <span class="hlt">Aqua</span>/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using <span class="hlt">MODIS</span> 500 m data and compared <span class="hlt">MODIS</span> utility to Landsat-based methods. <span class="hlt">MODIS</span> images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface <span class="hlt">reflectance</span>. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, <span class="hlt">reflecting</span> seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of <span class="hlt">MODIS</span> data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to <span class="hlt">reflect</span> seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040171173&hterms=research+methodology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dresearch%2Bmethodology','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040171173&hterms=research+methodology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dresearch%2Bmethodology"><span id="translatedtitle"><span class="hlt">MODIS</span> In-flight Calibration Methodologies</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Barnes, W.</p> <p>2004-01-01</p> <p><span class="hlt">MODIS</span> is a key instrument for the NASA's Earth Observing System (EOS) currently operating on the Terra spacecraft launched in December 1999 and <span class="hlt">Aqua</span> spacecraft launched in May 2002. It is a cross-track scanning radiometer, making measurements over a wide field of view in 36 spectral bands with wavelengths from 0.41 to 14.5 micrometers and providing calibrated data products for science and research communities in their studies of the Earth s system of land, oceans, and atmosphere. A complete suite of on-board calibrators (OBC) have been designed for the instruments in-flight calibration and characterization, including a solar diffuser (SD) and solar diffuser stability monitor (SDSM) system for the radiometric calibration of the 20 <span class="hlt">reflective</span> solar bands (RSB), a blackbody (BB) for the radiometric calibration of the 16 thermal emissive bands (TEB), and a spectro-radiometric calibration assembly (SRCA) for the spatial (all bands) and spectral (RSB only) characterization. This paper discusses <span class="hlt">MODIS</span> in-flight Cali bration methodologies of using its on-board calibrators. Challenging issues and examples of tracking and correcting instrument on-orbit response changes are presented, including SD degradation (20% at 412nm, 12% at 466nm, and 7% at 530nm over four and a half years) and response versus scan angle changes (10%, 4%, and 1% differences between beginning of the scan and end of the scan at 412nm, 466nm, and 530nm) in the VIS spectral region. Current instrument performance and lessons learned are also provided.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC54C..06K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC54C..06K"><span id="translatedtitle">Fifteen Years of Earth Observations from <span class="hlt">MODIS</span>: What Has Been Accomplished?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>King, M. D.; Running, S. W.; Platnick, S. E.; Franz, B. A.</p> <p>2014-12-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and <span class="hlt">Aqua</span> spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for <span class="hlt">Aqua</span>. Among the remote sensing algorithms developed and applied to this sensor for nearly 15 years of Earth observations are spectral and spatial distribution of albedo and surface <span class="hlt">reflectance</span>, snow and sea ice mapping, land cover and vegetation index, fire products, including burn scars, cloud amount, cloud and aerosol optical properties, sea surface temperature, and ocean color. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, biogeochemistry studies, and fundamental atmospheric research. A sampling of what has been accomplished and the breadth of new, often unanticipated, applications will be highlighted and discussed. Many of the <span class="hlt">MODIS</span> products have already been adopted by agencies concerned with natural resource and environmental management.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AMT.....6.2989L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AMT.....6.2989L"><span id="translatedtitle">The Collection 6 <span class="hlt">MODIS</span> aerosol products over land and ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Mattoo, S.; Munchak, L. A.; Remer, L. A.; Sayer, A. M.; Patadia, F.; Hsu, N. C.</p> <p>2013-11-01</p> <p>The twin Moderate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors have been flying on Terra since 2000 and <span class="hlt">Aqua</span> since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from <span class="hlt">MODIS</span>-observed spectral <span class="hlt">reflectance</span>. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface <span class="hlt">reflectance</span>, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and <span class="hlt">Aqua</span> differently. For <span class="hlt">Aqua</span>, all changes will result in reduced</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070034809&hterms=HTML&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DHTML','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070034809&hterms=HTML&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DHTML"><span id="translatedtitle">Generating a Long-Term Land Data Record from the AVHRR and <span class="hlt">MODIS</span> Instruments</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pedelty, Jeffrey; Devadiga, Sadashiva; Masuoka, Edward; Brown, Molly; Pinzon, Jorge; Tucker, Compton; Vermote, Eric; Prince, Stephen; Nagol, Jyotheshwar; Justice, Christopher; Roy, David; Ju, Junchang; Schaaf, Crystal; Liu, Jicheng; Privette, Jeffrey; Pincheiro, Ana</p> <p>2007-01-01</p> <p>The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and <span class="hlt">MODIS</span> instruments for land climate studies. The project will create daily surface <span class="hlt">reflectance</span> and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for <span class="hlt">MODIS</span> products from EOS Terra and <span class="hlt">Aqua</span>. Higher order products such as burned area, land surface temperature, albedo, bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA satellites by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in <span class="hlt">MODIS</span> processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface <span class="hlt">reflectance</span> product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for <span class="hlt">MODIS</span> land product quality assessment. The land surface <span class="hlt">reflectance</span> products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110007300&hterms=ecosystem+marine&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystem%2Bmarine','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110007300&hterms=ecosystem+marine&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystem%2Bmarine"><span id="translatedtitle">Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, <span class="hlt">MODIS</span>, and MISR</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.</p> <p>2010-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Airborne Simulator (MAS) and <span class="hlt">MODIS</span>/Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional <span class="hlt">reflectance</span> and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process <span class="hlt">MODIS</span> Cloud data from the <span class="hlt">Aqua</span> and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on <span class="hlt">MODIS</span>, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from <span class="hlt">MODIS</span> on the Terra spacecraft. Finally, this <span class="hlt">MODIS</span>-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007875','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007875"><span id="translatedtitle">Validation of the <span class="hlt">MODIS</span> "Clear-Sky" Surface Temperature of the Greenland Ice Sheet</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Koenig, L. S.; DiGirolamo, N. E.; Comiso, J.; Shuman, C. A.</p> <p>2011-01-01</p> <p>Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and <span class="hlt">Aqua</span> satellites. We use the <span class="hlt">MODIS</span> ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and <span class="hlt">Aqua</span> IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and <span class="hlt">Reflection</span> Radiometer. In this work, we focus on 1) and 2) above. Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and <span class="hlt">Aqua</span> satellites</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70032007','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70032007"><span id="translatedtitle">Detection rates of the <span class="hlt">MODIS</span> active fire product in the United States</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hawbaker, T.J.; Radeloff, V.C.; Syphard, A.D.; Zhu, Z.; Stewart, S.I.</p> <p>2008-01-01</p> <p><span class="hlt">MODIS</span> active fire data offer new information about global fire patterns. However, uncertainties in detection rates can render satellite-derived fire statistics difficult to interpret. We evaluated the <span class="hlt">MODIS</span> 1??km daily active fire product to quantify detection rates for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> sensors, examined how cloud cover and fire size affected detection rates, and estimated how detection rates varied across the United States. <span class="hlt">MODIS</span> active fire detections were compared to 361 reference fires (??? 18??ha) that had been delineated using pre- and post-fire Landsat imagery. Reference fires were considered detected if at least one <span class="hlt">MODIS</span> active fire pixel occurred within 1??km of the edge of the fire. When active fire data from both <span class="hlt">Aqua</span> and Terra were combined, 82% of all reference fires were found, but detection rates were less for <span class="hlt">Aqua</span> and Terra individually (73% and 66% respectively). Fires not detected generally had more cloudy days, but not when the <span class="hlt">Aqua</span> data were considered exclusively. <span class="hlt">MODIS</span> detection rates decreased with fire size, and the size at which 50% of all fires were detected was 105??ha when combining <span class="hlt">Aqua</span> and Terra (195??ha for <span class="hlt">Aqua</span> and 334??ha for Terra alone). Across the United States, detection rates were greatest in the West, lower in the Great Plains, and lowest in the East. The <span class="hlt">MODIS</span> active fire product captures large fires in the U.S. well, but may under-represent fires in areas with frequent cloud cover or rapidly burning, small, and low-intensity fires. We recommend that users of the <span class="hlt">MODIS</span> active fire data perform individual validations to ensure that all relevant fires are included. ?? 2008 Elsevier Inc. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PhDT........43M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PhDT........43M"><span id="translatedtitle">Estimation of suspended particulate matter concentration in the Mississippi Sound using <span class="hlt">MODIS</span> imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Merritt, Danielle</p> <p></p> <p>The discharge of sediment-laden rivers into the Mississippi Sound increases the turbidity of coastal waters. The concentration of suspended particulates is an important parameter in the analysis of coastal water quality factors. The spatiotemporal resolution associated with satellite sensors makes remote sensing an ideal tool to monitor suspended particulate concentrations. Accordingly, the presented research evaluated the validity of published algorithms that relate remote sensing <span class="hlt">reflectance</span> (Rrs) with suspended particulate matter for the Mississippi Sound. Additionally, regression analysis was used to correlate in situ SPM concentrations with coincident observations of visible and nearinfrared band <span class="hlt">reflectance</span> collected by the <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> sensor in order to develop a predictive model for SPM. The most robust algorithm yielded an RMSE of 15.53% (n = 86) in the determination of SPM concentrations. The application of this algorithm allows for the rapid assessment of water quality issues related to elevated SPM concentrations in the Mississippi Sound.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130014411','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130014411"><span id="translatedtitle">A Full Snow Season in Yellowstone: A Database of Restored <span class="hlt">Aqua</span> Band 6</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gladkova, Irina; Grossberg, Michael; Bonev, George; Romanov, Peter; Riggs, George; Hall, Dorothy</p> <p>2013-01-01</p> <p>The algorithms for estimating snow extent for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) optimally use the 1.6- m channel which is unavailable for <span class="hlt">MODIS</span> on <span class="hlt">Aqua</span> due to detector damage. As a test bed to demonstrate that <span class="hlt">Aqua</span> band 6 can be restored, we chose the area surrounding Yellowstone and Grand Teton national parks. In such rugged and difficult-to-access terrain, satellite images are particularly important for providing an estimation of snow-cover extent. For the full 2010-2011 snow season covering the Yellowstone region, we have used quantitative image restoration to create a database of restored <span class="hlt">Aqua</span> band 6. The database includes restored radiances, normalized vegetation index, normalized snow index, thermal data, and band-6-based snow-map products. The restored <span class="hlt">Aqua</span>-band-6 data have also been regridded and combined with Terra data to produce a snow-cover map that utilizes both Terra and <span class="hlt">Aqua</span> snow maps. Using this database, we show that the restored <span class="hlt">Aqua</span>-band-6-based snow-cover extent has a comparable performance with respect to ground stations to the one based on Terra. The result of a restored band 6 from <span class="hlt">Aqua</span> is that we have an additional band-6 image of the Yellowstone region each day. This image can be used to mitigate cloud occlusion, using the same algorithms used for band 6 on Terra. We show an application of this database of restored band-6 images to illustrate the value of creating a cloud gap filling using the National Aeronautics and Space Administration s operational cloud masks and data from both <span class="hlt">Aqua</span> and Terra.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030108344&hterms=water+africa&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dwater%2Bafrica','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030108344&hterms=water+africa&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dwater%2Bafrica"><span id="translatedtitle">A Technique for Remote Sensing of Suspended Sediments and Shallow Coastal Waters Using <span class="hlt">MODIS</span> Visible and Near-IR Channels</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Li, Rong-Rong; Kaufman, Yoram J.</p> <p>2002-01-01</p> <p>We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (<span class="hlt">MODIS</span>). The <span class="hlt">MODIS</span> instruments on board the NASA Terra and <span class="hlt">Aqua</span> Spacecrafts are equipped with one set of narrow channels located in a wide 0.4 - 2.5 micron spectral range. These channels were designed primarily for remote sensing of the land surface and atmosphere. We have found that the set of land and cloud channels are also quite useful for remote sensing of the bright coastal waters. We have developed an empirical algorithm, which uses the narrow <span class="hlt">MODIS</span> channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom <span class="hlt">reflections</span>. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 micron that does not allow illumination of sediments in the water or a shallow ocean floor. <span class="hlt">MODIS</span> data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20050156603&hterms=Science+DirecT&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DScience%2BDirecT','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20050156603&hterms=Science+DirecT&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DScience%2BDirecT"><span id="translatedtitle"><span class="hlt">MODIS</span> Direct Broadcast and Remote Sensing Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tsay, Si-Chee</p> <p>2004-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and <span class="hlt">Aqua</span> spacecraft on May 4, 2002. <span class="hlt">MODIS</span> scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the <span class="hlt">MODIS</span> measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/<span class="hlt">Aqua-MODIS</span> Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using <span class="hlt">MODIS</span> data, focusing primarily on the <span class="hlt">MODIS</span> cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171375','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171375"><span id="translatedtitle">Cloud Inhomogeneity from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cahalan, Robert F.</p> <p>2004-01-01</p> <p>Two full months (July 2003 and January 2004) of <span class="hlt">MODIS</span> Atmosphere Level-3 data from the Terra and <span class="hlt">Aqua</span> satellites are analyzed in order to characterize the horizontal variability of cloud optical thickness and water path at global scales. Various options to derive cloud variability parameters are discussed. The climatology of cloud inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two cloud phases, and separately over land and ocean. We find that cloud inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid clouds, weaker for local morning than local afternoon, about the same for liquid and ice clouds on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that <span class="hlt">MODIS</span> is capable of revealing significant fluctuations in cloud horizontal inhomogenity and stress the need to model their global radiative effect in future studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150001339','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150001339"><span id="translatedtitle">An Approach for the Long-Term 30-m Land Surface Snow-Free Albedo Retrieval from Historic Landsat Surface <span class="hlt">Reflectance</span> and <span class="hlt">MODIS</span>-based A Priori Anisotropy Knowledge</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.; He, Tao</p> <p>2014-01-01</p> <p>Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from <span class="hlt">MODIS</span>, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a "<span class="hlt">MODIS</span>-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with <span class="hlt">MODIS</span> Bidirectional <span class="hlt">Reflectance</span> Distribution Function (BRDF) information. Here we present a "pre-<span class="hlt">MODIS</span> era" approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT <span class="hlt">reflects</span> a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from <span class="hlt">MODIS</span> observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir <span class="hlt">reflectance</span> ratios as a bridge between the Landsat and <span class="hlt">MODIS</span> scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes.We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070017413&hterms=production+evaluation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dproduction%2Bevaluation','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070017413&hterms=production+evaluation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dproduction%2Bevaluation"><span id="translatedtitle">Evaluation of AIRS, <span class="hlt">MODIS</span>, and HIRS 11 Micron Brightness Temperature Difference Changes from 2002 through 2006</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Broberg, Steven E.; Aumann, Hartmut H.; Gregorich, David T.; Xiong, X.</p> <p>2006-01-01</p> <p>In an effort to validate the accuracy and stability of AIRS data at low scene temperatures (200-250 K range), we evaluated brightness temperatures at 11 microns with <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> band 31 and HIRS/3 channel 8 for Antarctic granules between September 2002 and May 2006. We found excellent agreement with <span class="hlt">MODIS</span> (at the 0.2 K level) over the full emperature range in data from early in the <span class="hlt">Aqua</span> mission. However, in more recent data, starting in April 2005, we found a scene temperature dependence in <span class="hlt">MODIS</span>-AIRS brightness temperature differences, with a discrepancy of 1- 1.5 K at 200 K. The comparison between AIRS and HIRS/3 (channel 8) on NOAA 16 for the same time period yields excellent agreement. The cause and time dependence of the disagreement with <span class="hlt">MODIS</span> is under evaluation, but the change was coincident with a change in the <span class="hlt">MODIS</span> production software from collection 4 to 5.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B33C0193L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B33C0193L"><span id="translatedtitle">Mapping Crop Cycles in China Using <span class="hlt">MODIS</span>-EVI Time Series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, L.; Friedl, M. A.; Xin, Q.; Gray, J. M.; Pan, Y.; Frolking, S. E.</p> <p>2014-12-01</p> <p>As the Earth's population continues to grow and demand for food increases, multiple cropping is an effective way to increase crop production. Cropping intensity, which we define here as the number of cropping cycles per year, is an important dimension of land use that is strongly influences water demand and agricultural production. Satellite data provide global land cover maps with indispensable information regarding areal extent of global croplands and its distribution. However, the land use information such as cropping intensity is not routinely provided by global land cover products from instruments such as <span class="hlt">MODIS</span>, because mapping this information from remote sensing is challenging. We present a straight forward but efficient algorithm for automated mapping of agricultural intensity over large geographic regions using 8-day <span class="hlt">MODIS</span> EVI time series data derived from Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> products. The proposed algorithm first applies an adaptive Savitzky-Golay filter to smooth Enhanced Vegetation Index (EVI) time series derived from <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> data, and then uses an iterative moving-window methodology to identify cropping cycles from the smoothed EVI time series. Comparison of results from our algorithm with national survey data at both the provincial and prefectural level in China show that the algorithm provides estimates of gross sown area that agree well with inventory data. Accuracy assessment using data generated by expert classification of randomly selected pixel samples indicates an overall accuracy of 91.0% for three agricultural intensity classes. More generally, the algorithm shows significant potential to automatically estimate reliable cropping intensity information in support of large-scale studies of agricultural land use and land cover dynamics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1112835C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1112835C"><span id="translatedtitle">Regional scale net radiation estimation by means of Landsat and TERRA/<span class="hlt">AQUA</span> imagery and GIS modeling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Ninyerola, M.; Pons, X.; Llorens, P.; Poyatos, R.</p> <p>2009-04-01</p> <p>Net radiation (Rn) is one of the most important variables for the estimation of surface energy budget and is used for various applications including agricultural meteorology, climate monitoring and weather prediction. Moreover, net radiation is an essential input variable for potential as well as actual evapotranspiration modeling. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute net radiation at regional scales in a feasible way. In this study we present a regional scale estimation of the daily Rn on clear days, (Catalonia, NE of the Iberian Peninsula), using a set of 22 Landsat images (17 Landsat-5 TM and 5 Landsat-7 ETM+) and 171 TERRA/<span class="hlt">AQUA</span> images <span class="hlt">MODIS</span> from 2000 to 2007 period. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected three different types of products which contain the remote sensing data we have used to model daily Rn: daily LST product, daily calibrated <span class="hlt">reflectances</span> product and daily atmospheric water vapour product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital Elevation Model, obtaining an RMS less than 30 m. Radiometric correction of Landsat non-thermal bands has been done following the methodology proposed by Pons and Solé (1994), which allows to reduce the number of undesired artifacts that are due to the effects of the atmosphere or to the differential illumination which is, in turn, due to the time of the day, the location in the Earth and the relief (zones being more illuminated than others, shadows, etc). Atmospheric correction of Landsat thermal band has been carried out by means of a single-channel algorithm improvement developed by Cristóbal et al. (2009) and the land surface emissivity computed by means of the methodology proposed by Sobrino and Raissouni (2000). Rn has been estimated through the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008715','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008715"><span id="translatedtitle">The Operational <span class="hlt">MODIS</span> Cloud Optical and Microphysical Property Product: Overview of the Collection 6 Algorithm and Preliminary Results</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas</p> <p>2012-01-01</p> <p>Operational Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) are currently being reprocessed along with other <span class="hlt">MODIS</span> Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar <span class="hlt">reflectance</span> techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud <span class="hlt">reflectance</span> and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from <span class="hlt">MODIS</span> Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the <span class="hlt">MODIS</span> L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030032934','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030032934"><span id="translatedtitle"><span class="hlt">MODIS</span> Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most <span class="hlt">MODIS</span> data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. <span class="hlt">MODIS</span> Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). <span class="hlt">MODIS</span> data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the <span class="hlt">MODIS</span> Science Teams. <span class="hlt">MODIS</span>/Terra Level 1, and all <span class="hlt">MODIS</span>/Terra 11 micron SST products are announced as validated. At the time of this publication, the <span class="hlt">MODIS</span> Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of <span class="hlt">MODIS</span>/Terra Ocean products. <span class="hlt">MODIS/Aqua</span> Level 1 and cloud mask products are released with provisional maturity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160005113','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160005113"><span id="translatedtitle">EOS <span class="hlt">Aqua</span> Mission Status at Earth Science Constellation MOWG Meeting @ LASP April 13, 2016</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Guit, William J.</p> <p>2016-01-01</p> <p>This presentation <span class="hlt">reflects</span> the EOS <span class="hlt">Aqua</span> mission status, spacecraft subsystem summary, recent and planned activities, inclination adjust maneuvers, propellant usage and lifetime estimate, orbital maintenance maneuvers, conjunction assessment high interest events, ground track error, spacecraft orbital parameters trends and predictions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023024','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023024"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span> Aerosol Optical Depth Retrievals over a Tropical Urban Site, Pune, India</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>More, Sanjay; Kuman, P. Pradeep; Gupta, Pawan; Devara, P. C. S.; Aher, G. R.</p> <p>2011-01-01</p> <p>In the present paper, <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span>; level 2, collection 5) derived aerosoloptical depths (AODs) are compared with the ground-based measurements obtained from AERONET (level 2.0) and Microtops - II sun-photometer over a tropical urban station, Pune (18 deg 32'N; 73 deg 49'E, 559 m amsl). This is the first ever systematic validation of the <span class="hlt">MODIS</span> aerosol products over Pune. Analysis of the data indicates that the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> AOD retrievals at 550 nm have good correlations with the AERONET and Microtops - II sun-photometer AOD measurements. During winter the linear regression correlation coefficients for <span class="hlt">MODIS</span> products against AERONET measurements are 0.79 for Terra and 0.62 for <span class="hlt">Aqua</span>; however for premonsoon, the corresponding coefficients are 0.78 and 0.74. Similarly, the linear regression correlation coefficients for Microtops measurements against <span class="hlt">MODIS</span> products are 0.72 and 0.93 for Terra and <span class="hlt">Aqua</span> data respectively during winter and are 0.78 and 0.75 during pre-monsoon. On yearly basis in 2008-2009, correlation coefficients for <span class="hlt">MODIS</span> products against AERONET measurements are 0.80 and 0.78 for Terra and <span class="hlt">Aqua</span> respectively while the corresponding coefficients are 0.70 and 0.73 during 2009-2010. The regressed intercepts with <span class="hlt">MODIS</span> vs. AERONET are 0.09 for Terra and 0.05 for <span class="hlt">Aqua</span> during winter whereas their values are 0.04 and 0.07 during pre-monsoon. However, <span class="hlt">MODIS</span> AODs are found to underestimate during winter and overestimate during pre-monsoon with respect to AERONET and Microtops measurements having slopes 0.63 (Terra) and 0.74 (<span class="hlt">Aqua</span>) during winter and 0.97 (Terra) and 0.94 (<span class="hlt">Aqua</span>) during pre-monsoon. Wavelength dependency of Single Scattering Albedo (SSA) shows presence of absorbing and scattering aerosol particles. For winter, SSA decreases with wavelength with the values 0.86 +/- 0.03 at 440 nm and 0.82 +/- 0.04 at 1020nm. In pre-monsoon, it increases with wavelength (SSA is 0.87 +/- 0.02 at 440nm; and 0.88 +/-0.04 at 1020 nm).</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/1045215','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/1045215"><span id="translatedtitle">A SOAP Web Service for accessing <span class="hlt">MODIS</span> land product subsets</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>SanthanaVannan, Suresh K; Cook, Robert B; Pan, Jerry Yun; Wilson, Bruce E</p> <p>2011-01-01</p> <p>Remote sensing data from satellites have provided valuable information on the state of the earth for several decades. Since March 2000, the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor on board NASA s Terra and <span class="hlt">Aqua</span> satellites have been providing estimates of several land parameters useful in understanding earth system processes at global, continental, and regional scales. However, the HDF-EOS file format, specialized software needed to process the HDF-EOS files, data volume, and the high spatial and temporal resolution of <span class="hlt">MODIS</span> data make it difficult for users wanting to extract small but valuable amounts of information from the <span class="hlt">MODIS</span> record. To overcome this usability issue, the NASA-funded Distributed Active Archive Center (DAAC) for Biogeochemical Dynamics at Oak Ridge National Laboratory (ORNL) developed a Web service that provides subsets of <span class="hlt">MODIS</span> land products using Simple Object Access Protocol (SOAP). The ORNL DAAC <span class="hlt">MODIS</span> subsetting Web service is a unique way of serving satellite data that exploits a fairly established and popular Internet protocol to allow users access to massive amounts of remote sensing data. The Web service provides <span class="hlt">MODIS</span> land product subsets up to 201 x 201 km in a non-proprietary comma delimited text file format. Users can programmatically query the Web service to extract <span class="hlt">MODIS</span> land parameters for real time data integration into models, decision support tools or connect to workflow software. Information regarding the <span class="hlt">MODIS</span> SOAP subsetting Web service is available on the World Wide Web (WWW) at http://daac.ornl.gov/modiswebservice.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130013087','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130013087"><span id="translatedtitle"><span class="hlt">Aqua</span> 10 Years After Launch</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2013-01-01</p> <p>A little over ten years ago, in the early morning hours of May 4, 2002, crowds of spectators stood anxiously watching as the Delta II rocket carrying NASA's <span class="hlt">Aqua</span> spacecraft lifted off from its launch pad at Vandenberg Air Force Base in California at 2:55 a.m. The rocket quickly went through a low-lying cloud cover, after which the main portion of the rocket fell to the waters below and the rockets second stage proceeded to carry <span class="hlt">Aqua</span> south across the Pacific, onward over Antarctica, and north to Africa, where the spacecraft separated from the rocket 59.5 minutes after launch. Then, 12.5 minutes later, the solar array unfurled over Europe, and <span class="hlt">Aqua</span> was on its way in the first of what by now have become over 50,000 successful orbits of the Earth.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980236657','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980236657"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1996-01-01</p> <p>Our first activity is based on delivery of code to Bob Evans (University of Miami) for integration and eventual delivery to the <span class="hlt">MODIS</span> Science Data Support Team. As we noted in our previous semi-annual report, coding required the development and analysis of an end-to-end model of fluorescence line height (FLH) errors and sensitivity. This model is described in a paper in press in Remote Sensing of the Environment. Once the code was delivered to Miami, we continue to use this error analysis to evaluate proposed changes in <span class="hlt">MODIS</span> sensor specifications and performance. Simply evaluating such changes on a band by band basis may obscure the true impacts of changes in sensor performance that are manifested in the complete algorithm. This is especially true with FLH that is sensitive to band placement and width. The error model will be used by Howard Gordon (Miami) to evaluate the effects of absorbing aerosols on the FLH algorithm performance. Presently, FLH relies only on simple corrections for atmospheric effects (viewing geometry, Rayleigh scattering) without correcting for aerosols. Our analysis suggests that aerosols should have a small impact relative to changes in the quantum yield of fluorescence in phytoplankton. However, the effect of absorbing aerosol is a new process and will be evaluated by Gordon.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811679M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811679M"><span id="translatedtitle">Global land surface albedo maps from <span class="hlt">MODIS</span> using the Google Earth Engine</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mitraka, Zina; Benas, Nikolaos; Gorelick, Noel; Chrysoulakis, Nektarios</p> <p>2016-04-01</p> <p>The land surface albedo (LSA) is a critical physical variable, which influences the Earth's climate by affecting the energy budget and distribution in the Earth-atmosphere system. Its role is highly significant in both global and local scales; hence, LSA measurements provide a quantitative means for better constraining global and regional scale climate modelling efforts. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor, on board NASA's Terra and <span class="hlt">Aqua</span> platforms, provides the parameters needed for the computation of LSA on an 8-day temporal scale and a variety of spatial scales (ranging between 0.5 - 5 km). This dataset was used here for the LSA estimation and its changes over the study area at 0.5 km spatial resolution. More specifically, the <span class="hlt">MODIS</span> albedo product was used, which includes both the directional-hemispherical surface <span class="hlt">reflectance</span> (black-sky albedo) and the bi-hemispherical surface <span class="hlt">reflectance</span> (white-sky albedo). The LSA was estimated for the whole globe on an 8-day basis for the whole time period covered by <span class="hlt">MODIS</span> acquisitions (i.e. 2000 until today). To estimate LSA from black-sky and white-sky albedos, the fraction of the diffused radiation is needed, a function of the Aerosol Optical Thickness (AOT). Required AOT information was acquired from the <span class="hlt">MODIS</span> AOT product at 1̊ × 1̊ spatial resolution. Since LSA also depends on solar zenith angle (SZA), 8-day mean LSA values were computed as averages of corresponding LSA values for representative SZAs covering the 24-hour day. The estimated LSA was analysed in terms of both spatial and seasonal characteristics, while LSA changes during the period examined were assessed. All computation were performed using the Google Earth Engine (GEE). The GEE provided access to all the <span class="hlt">MODIS</span> products needed for the analysis without the need of searching or downloading. Moreover, the combination of <span class="hlt">MODIS</span> products in both temporal and spatial terms was fast and effecting using the GEE API (Application</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120002030','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120002030"><span id="translatedtitle">Analysis of Co-Located <span class="hlt">MODIS</span> and CALIPSO Observations Near Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Varnai, Tamas; Marshak, Alexander</p> <p>2011-01-01</p> <p>The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the <span class="hlt">Aqua</span> satellite's <span class="hlt">MODIS</span> instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the <span class="hlt">reflection</span> of its pulses. In contrast, <span class="hlt">MODIS</span> takes images of <span class="hlt">reflected</span> sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that <span class="hlt">MODIS</span> can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between <span class="hlt">MODIS</span> and CALIOP observations have only a minor impact. The study also finds that <span class="hlt">MODIS</span> data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when <span class="hlt">MODIS</span> cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113219L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113219L"><span id="translatedtitle">Quantifying intra and inter-annual variation of <span class="hlt">MODIS</span> derived leaf area index time-series 2000-2008</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lanorte, A.; de Santis, F.; Lasaponara, R.</p> <p>2009-04-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is a key instrument aboard NASA's Terra and <span class="hlt">Aqua</span> satellites. Terra <span class="hlt">MODIS</span> and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> image the entire Earth's surface every one to two days and provide vital information for global-change research. <span class="hlt">MODIS</span> derived leaf area index (LAI) is an important parameter for describing vegetation canopy structure in the terrestrial ecosystem on the global, continental, and regional scales. In this study we analyse intra and inter-annual variation of <span class="hlt">MODIS</span> derived leaf area index time-series 2000-2008 data for Mediterranean ecosystems of Southern Italy. The objective is to explore seasonal trends in the phenology of southern Italy woodlands and shrublands and inter-annual long-term variations related to plant's photosynthesis process or growth status.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015418','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015418"><span id="translatedtitle">Evaluation and Windspeed Dependence of <span class="hlt">MODIS</span> Aerosol Retrievals Over Open Ocean</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kleidman, Richard G.; Smirnov, Alexander; Levy, Robert C.; Mattoo, Shana; Tanre, Didier</p> <p>2011-01-01</p> <p>The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the <span class="hlt">MODIS</span> aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing <span class="hlt">MODIS</span> Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that <span class="hlt">MODIS</span> is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and <span class="hlt">Aqua</span>, respectively. Angstrom Exponent comparisons show a high correlation between <span class="hlt">MODIS</span> retrievals and shipboard measurements (R= 0.85 Terra, 0.83 <span class="hlt">Aqua</span>), although the <span class="hlt">MODIS</span> aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and <span class="hlt">Aqua</span> ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that <span class="hlt">Aqua</span> agreement with AERONET is marginally better. However we cannot claim based on the current study that the better <span class="hlt">Aqua</span> comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and <span class="hlt">Aqua</span> retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A41D0150L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A41D0150L"><span id="translatedtitle">Comparison of Deep Blue and Land Surface <span class="hlt">Reflectance</span> in the San Joaquin Valley</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lehmuth, S.; Agrawal, P.; Fisher, D.; Nguyen, A.; Roberts, K.; Strawa, A. W.; Johnson, L. F.; Skiles, J. W.</p> <p>2009-12-01</p> <p>lation standards for the past several years. While previous studies show strong correlations between the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) derived Aerosol Optical Thickness (AOT) and surface PM measurements on the East Coast of the United States, weak correlations have been found on the West Coast. Specific causes for this discrepancy have not been identified. The Deep Blue algorithm was created in order to correct AOT calculations over arid, non-vegetated regions. Although slight improvements were seen, numbers over California remained problematic. This study aims to understand the poor correlation on the West Coast, specifically in the SJV, by targeting surface <span class="hlt">reflectance</span> as a factor for the inaccuracy. This was done by comparing land surface <span class="hlt">reflectances</span> derived from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> to ground <span class="hlt">reflectance</span> measurements for the region, in order to examine their correlation. Presumably, an undesirable effect on AOT calculations would occur if these surface <span class="hlt">reflectance</span> values are imprecise. Results show that there is little correlation between the data sets. <span class="hlt">MODIS</span> Land Surface <span class="hlt">Reflectance</span> matched closest to the mixed ground measurements. In all products, the red band (0.620 - 0.670 μm) values vary more than the blue band (0.459 - 0.479 μm) values. Most data fall in a horizontal linear trend line, not the expected 1:1 line.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980219482','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980219482"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1998-01-01</p> <p>The objectives of the last six months were: (1) Revise the algorithms for the Fluorescence Line Height (FLH) and Chlorophyll Fluorescence Efficiency (CFE) products, especially the data quality flags; (2) Revise the MOCEAN validation plan; (3) Deploy and recover bio-optical instrumentation at the Hawaii Ocean Time-series (HOT) site as part of the Joint Global Ocean Flux Study (JGOFS); (4) Prepare for field work in the Antarctic Polar Frontal Zone as part of JGOFS; (5) Submit manuscript on bio-optical time scales as estimated from Lagrangian drifters; (6) Conduct chemostat experiments on fluorescence; (7) Interface with the Global Imager (GLI) science team; and (8) Continue development of advanced data system browser. We are responsible for the delivery of two at-launch products for AM-1: Fluorescence line height (FLH) and chlorophyll fluorescence efficiency (CFE). We also considered revising the input chlorophyll, which is used to determine the degree of binning. We have refined the quality flags for the Version 2 algorithms. We have acquired and installed a Silicon Graphics Origin 200. We are working with the University of Miami team to develop documentation that will describe how the <span class="hlt">MODIS</span> ocean components are linked together.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040008406','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040008406"><span id="translatedtitle">A Study of Uncertainties for <span class="hlt">MODIS</span> Cloud Retrievals of Optical Thickness and Effective Radius</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Pincus, Robert</p> <p>2002-01-01</p> <p>The investigation spanned four linked components as summarized in section III, each relating to some aspect of uncertainty assessment in the retrieval of cloud optical and microphysical properties using solar <span class="hlt">reflectance</span> algorithms such as the <span class="hlt">MODIS</span> operational cloud product (product IDS MOD06, MDY06 for Terra and <span class="hlt">Aqua</span>, respectively). As discussed, three of these components have been fully completed (items (l), (2), and (3) while item (4) has been partially completed. These efforts have resulted in peer-reviewed publications and/or information delivered to the <span class="hlt">MODIS</span> P.I. (M. D. King) for inclusion in the cloud product Quality Assessment (QA) output, a portion of the product output used, in part, for retrieval error assignments. This final report begins with a synopsis of the proposed investigation (section III) followed by a summary of work performed up through the last report including updates (section IV). Section V describes new activities. Publications from the efforts are listed in section VI. Figures (available in powerpoint format) are found in section VII.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070017429','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070017429"><span id="translatedtitle">The Plane-parallel Albedo Bias of Liquid Clouds from <span class="hlt">MODIS</span> Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cahalan, Robert F.; Platnick, Steven</p> <p>2007-01-01</p> <p>In our most advanced modeling tools for climate change prediction, namely General Circulation Models (GCMs), the schemes used to calculate the budget of solar and thermal radiation commonly assume that clouds are horizontally homogeneous at scales as large as a few hundred kilometers. However, this assumption, used for convenience, computational speed, and lack of knowledge on cloud small scale variability, leads to erroneous estimates of the radiation budget. This paper provides a global picture of the solar radiation errors at scales of approximately 100 km due to warm (liquid phase) clouds only. To achieve this, we use cloud retrievals from the instrument <span class="hlt">MODIS</span> on the Terra and <span class="hlt">Aqua</span> satellites, along with atmospheric and surface information, as input into a GCM-style radiative transfer algorithm. Since the <span class="hlt">MODIS</span> product contains information on cloud variability below 100 km we can run the radiation algorithm both for the variable and the (assumed) homogeneous clouds. The difference between these calculations for <span class="hlt">reflected</span> or transmitted solar radiation constitutes the bias that GCMs would commit if they were able to perfectly predict the properties of warm clouds, but then assumed they were homogeneous for radiation calculations. We find that the global average of this bias is approx.2-3 times larger in terms of energy than the additional amount of thermal energy that would be trapped if we were to double carbon dioxide from current concentrations. We should therefore make a greater effort to predict horizontal cloud variability in GCMs and account for its effects in radiation calculations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=294400','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=294400"><span id="translatedtitle">Comparison of different <span class="hlt">MODIS</span> data product collections over an agricultural area</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Standard data products from NASA's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) were available at launch (Collection 3) and have undergone two revisions (Collections 4 and 5) during the continuing Terra and <span class="hlt">Aqua</span> missions. In 2000, a research project was conducted in large fields of corn an...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B14D..04H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B14D..04H"><span id="translatedtitle">Potentials and limitations for scaling plant photosynthesis across northern latitudes using <span class="hlt">MODIS</span> (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hilker, T.; Hall, F.; Coops, N.; Lyapustin, A.; Tucker, C. J.</p> <p>2013-12-01</p> <p>Our ability to quantify terrestrial climate feedbacks will depend on a comprehensive understanding of the carbon, water and energy balance over land. Models of photosynthesis have long been challenged by the complexity of the biophysical mechanisms driving gross primary productivity (GPP) and the large number of factors contributing to or limiting photosynthesis at a given time. Currently, neither enzyme kinetics, nor radiation limited models allow sufficiently accurate estimates of GPP and as a result, large uncertainties remain with respect to future carbon uptake and climate scenarios. One possible way to address these issues is to combine photosynthesis models with satellite observations to obtain spatially explicit and temporally continuous estimates of photosynthesis by means of data assimilation. Remote sensing observations can be used to infer GPP as the product of photosynthetically active radiation (PAR) [Wm-2], the fraction of it being absorbed by the green vegetation elements (fPAR) and the efficiency ɛ (g CMJ-1) with which plants can use this absorbed radiation energy to produce biomass. In previous work, we have developed a physically-based approach to use multi-angle observations of the photochemical <span class="hlt">reflectance</span> index, a narrow band index linked to the xanthophyll cycle of vegetation to robustly infer GPP across vegetation types. The technique eliminates extraneous effects of PRI by comparing <span class="hlt">reflectance</span> of the identical canopy from different view angles and estimating differences in photosynthetic down-regulation as a function of canopy shading. Broader application has so far been limited by the availability of multi-angle satellite data. <span class="hlt">MODIS</span> observations are acquired at different angles but these acquisitions are obtained across track. In high northern latitudes, there is a high frequency of satellite passes due to the near polar orbits of the Terra and <span class="hlt">Aqua</span> spacecrafts. This will allow us to combine <span class="hlt">MODIS</span> observation from both platforms from at</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20100034941&hterms=index+path&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dindex%2Bpath','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20100034941&hterms=index+path&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dindex%2Bpath"><span id="translatedtitle">Estimate of the Impact of Absorbing Aerosol Over Cloud on the <span class="hlt">MODIS</span> Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wilcox, Eric M.; Harshvardhan; Platnick, Steven</p> <p>2009-01-01</p> <p>Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA <span class="hlt">Aqua</span> satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the <span class="hlt">MODIS</span> retrieval over oceans, cloud <span class="hlt">reflectance</span> in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the <span class="hlt">MODIS</span> tau retrieval may result from reductions in the 0.86-micrometer <span class="hlt">reflectance</span>, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. <span class="hlt">MODIS</span> LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and <span class="hlt">MODIS</span> LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus <span class="hlt">MODIS</span>) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean <span class="hlt">MODIS</span> LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20100017716&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dspectrometer%2Bresolution','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20100017716&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dspectrometer%2Bresolution"><span id="translatedtitle">Advanced Remote-Sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with <span class="hlt">MODIS</span> Spatial Resolution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pagano, Thomas S.; Chahine, Moustafa T.; Aumann, Hartmut H.; OCallaghan, Fred</p> <p>2006-01-01</p> <p>The Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) will measure a wide range of earth quantities fundamental to the study of global climate change. It will build upon the success of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the Atmospheric Infrared Sounder (AIRS) instruments currently flying on the EOS <span class="hlt">Aqua</span> Spacecraft. Both instruments are facility instruments for NASA providing data to thousands of scientists investigating land, ocean and atmospheric Earth System processes. ARIES will meet all the requirements of AIRS and <span class="hlt">MODIS</span> in a single compact instrument, while providing the next-generation capability of improved spatial resolution for AIRS and improved spectral resolution for <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/22098723','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/22098723"><span id="translatedtitle">In <span class="hlt">aqua</span> vivo EPID dosimetry</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Wendling, Markus; McDermott, Leah N.; Mans, Anton; Olaciregui-Ruiz, Igor; Pecharroman-Gallego, Raul; Sonke, Jan-Jakob; Stroom, Joep; Herk, Marcel J.; Mijnheer, Ben van</p> <p>2012-01-15</p> <p>Purpose: At the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital in vivo dosimetry using an electronic portal imaging device (EPID) has been implemented for almost all high-energy photon treatments of cancer with curative intent. Lung cancer treatments were initially excluded, because the original back-projection dose-reconstruction algorithm uses water-based scatter-correction kernels and therefore does not account for tissue inhomogeneities accurately. The aim of this study was to test a new method, in <span class="hlt">aqua</span> vivo EPID dosimetry, for fast dose verification of lung cancer irradiations during actual patient treatment. Methods: The key feature of our method is the dose reconstruction in the patient from EPID images, obtained during the actual treatment, whereby the images have been converted to a situation as if the patient consisted entirely of water; hence, the method is termed in <span class="hlt">aqua</span> vivo. This is done by multiplying the measured in vivo EPID image with the ratio of two digitally reconstructed transmission images for the unit-density and inhomogeneous tissue situation. For dose verification, a comparison is made with the calculated dose distribution with the inhomogeneity correction switched off. IMRT treatment verification is performed for each beam in 2D using a 2D {gamma} evaluation, while for the verification of volumetric-modulated arc therapy (VMAT) treatments in 3D a 3D {gamma} evaluation is applied using the same parameters (3%, 3 mm). The method was tested using two inhomogeneous phantoms simulating a tumor in lung and measuring its sensitivity for patient positioning errors. Subsequently five IMRT and five VMAT clinical lung cancer treatments were investigated, using both the conventional back-projection algorithm and the in <span class="hlt">aqua</span> vivo method. The verification results of the in <span class="hlt">aqua</span> vivo method were statistically analyzed for 751 lung cancer patients treated with IMRT and 50 lung cancer patients treated with VMAT. Results: The improvements by</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSM.B41B..05D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSM.B41B..05D"><span id="translatedtitle">Mapping the Distribution of Cloud Forests Using <span class="hlt">MODIS</span> Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Douglas, M. W.; Mejia, J.; Murillo, J.; Orozco, R.</p> <p>2007-05-01</p> <p>Tropical cloud forests - those forests that are frequently immersed in clouds or otherwise very humid, are extremely difficult to map from the ground, and are not easily distinguished in satellite imagery from other forest types, but they have a very different flora and fauna than lowland rainforest. Cloud forests, although found in many parts of the tropics, have a very restricted vertical extent and thus are also restricted horizontally. As a result, they are subject to both human disturbance (coffee growing for example) and the effects of possible climate change. Motivated by a desire to seek meteorological explanations for the distribution of cloud forests, we have begun to map cloudiness using <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> visible imagery. This imagery, at ~1030 LT and 1330 LT, is an approximation for mid-day cloudiness. In tropical regions the amount of mid-day cloudiness strongly controls the shortwave radiation and thus the potential for evaporation (and aridity). We have mapped cloudiness using a simple algorithm that distinguishes between the cloud-free background brightness and the generally more <span class="hlt">reflective</span> clouds to separate clouds from the underlying background. A major advantage of <span class="hlt">MODIS</span> imagery over many other sources of satellite imagery is its high spatial resolution (~250m). This, coupled with precisely navigated images, means that detailed maps of cloudiness can be produced. The cloudiness maps can then be related to the underlying topography to further refine the location of the cloud forests. An advantage of this technique is that we are mapping the potential cloud forest, based on cloudiness, rather than the actual cloud forest, which are commonly based on forest estimates from satellite and digital elevation data. We do not derive precipitation, only estimates of daytime cloudiness. Although only a few years of <span class="hlt">MODIS</span> imagery has been used in our studies, we will show that this is sufficient to describe the climatology of cloudiness with acceptable</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030096002','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030096002"><span id="translatedtitle">Sea Ice Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.</p> <p>2003-01-01</p> <p>Global sea ice products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board both the Terra and <span class="hlt">Aqua</span> satellites. Daily sea ice extent and ice-surface temperature (IST) products are available at 1- and 4-km resolution. Validation activities have been undertaken to assess the accuracy of the <span class="hlt">MODIS</span> IST product at the South Pole station in Antarctica and in the Arctic Ocean using near-surface air-temperature data from a meteorological station and drifting buoys. Results from the study areas show that under clear skies, the <span class="hlt">MODIS</span> ISTs are very close to those of the near-surface air temperatures with a bias of -1.1 and -1.2 K, and an uncertainty of 1.6 and 1.7 K, respectively. It is shown that the uncertainties would be reduced if the actual temperature of the ice surface were reported instead of the near-surface air temperature. It is not possible to get an accurate IST from <span class="hlt">MODIS</span> in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and the <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> satellite, it may be possible to develop a relationship between <span class="hlt">MODIS</span>-derived IST and ice temperature derived from the AMSR-E. Since the AMSR-E measurements are generally unaffected by cloud cover, they may be used to complement the <span class="hlt">MODIS</span> IST measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980219481','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980219481"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1998-01-01</p> <p>The objective of the last six months were: (1) Continue analysis of Hawaii Ocean Time-series (HOT) bio-optical mooring data, and Southern Ocean bio-optical drifter data; (2) Complete development of documentation of MOCEAN algorithms and software for use by MOCEAN team and GLI team; (3) Deploy instrumentation during JGOFS cruises in the Southern Ocean; (4) Participate in test cruise for Fast Repetition Rate (FRR) fluorometer; (5) Continue chemostat experiments on the relationship of fluorescence quantum yield to environmental factors; and (6) Continue to develop and expand browser-based information system for in situ bio-optical data. We are continuing to analyze bio-optical data collected at the Hawaii Ocean Time Series mooring as well as data from bio-optical drifters that were deployed in the Southern Ocean. A draft manuscript has now been prepared and is being revised. A second manuscript is also in preparation that explores the vector wind fields derived from NSCAT measurements. The HOT bio-optical mooring was recovered in December 1997. After retrieving the data, the sensor package was serviced and redeployed. We have begun preliminary analysis of these data, but we have only had the data for 3 weeks. However, all of the data were recovered, and there were no obvious anomalies. We will add second sensor package to the mooring when it is serviced next spring. In addition, Ricardo Letelier is funded as part of the SeaWiFS calibration/validation effort (through a subcontract from the University of Hawaii, Dr. John Porter), and he will be collecting bio-optical and fluorescence data as part of the HOT activity. This will provide additional in situ measurements for <span class="hlt">MODIS</span> validation. As noted in the previous quarterly report, we have been analyzing data from three bio-optical drifters that were deployed in the Southern Ocean in September 1996. We presented results on chlorophyll and drifter speed. For the 1998 Ocean Sciences meeting, a paper will be presented on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A41C0078M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A41C0078M"><span id="translatedtitle">Assessing <span class="hlt">MODIS</span> Macrophysical Cloud Property Uncertainties</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maddux, B. C.; Ackerman, S. A.; Frey, R.; Holz, R.</p> <p>2013-12-01</p> <p>Cloud, being multifarious and ephemeral, is difficult to observe and quantify in a systematic way. Even basic terminology used to describe cloud observations is fraught with ambiguity in the scientific literature. Any observational technique, method, or platform will contain inherent and unavoidable measurement uncertainties. Quantifying these uncertainties in cloud observations is a complex task that requires an understanding of all aspects of the measurement. We will use cloud observations obtained from the Moderate Resolution Imaging Spectroradiameter(<span class="hlt">MODIS</span>) to obtain metrics of the uncertainty of its cloud observations. Our uncertainty analyses will contain two main components, 1) an attempt to create a bias or uncertainty with respect to active measurements from CALIPSO and 2) a relative uncertainty within the <span class="hlt">MODIS</span> cloud climatologies themselves. Our method will link uncertainty to the physical observation and its environmental/scene characteristics. Our aim is to create statistical uncertainties that are based on the cloud observational values, satellite view geometry, surface type, etc, for cloud amount and cloud top pressure. The <span class="hlt">MODIS</span> instruments on the NASA Terra and <span class="hlt">Aqua</span> satellites provide observations over a broad spectral range (36 bands between 0.415 and 14.235 micron) and high spatial resolution (250 m for two bands, 500 m for five bands, 1000 m for 29 bands), which the <span class="hlt">MODIS</span> cloud mask algorithm (MOD35) utilizes to provide clear/cloud determinations over a wide array of surface types, solar illuminations and view geometries. For this study we use the standard <span class="hlt">MODIS</span> products, MOD03, MOD06 and MOD35, all of which were obtained from the NASA Level 1 and Atmosphere Archive and Distribution System.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007354','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007354"><span id="translatedtitle">Comparison of the <span class="hlt">MODIS</span> Collection 5 Multilayer Cloud Detection Product with CALIPSO</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Wind, Gala; King, Michael D.; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.</p> <p>2010-01-01</p> <p>CALIPSO, launched in June 2006, provides global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the <span class="hlt">Aqua</span> spacecraft and other A-Train platforms. The most recent processing effort for the <span class="hlt">MODIS</span> Atmosphere Team, referred to as the Collection 5 scream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the <span class="hlt">MODIS</span> cloud optical and microphysical product retrieval, which are generated at a 1 km resolution. Using pixel-level collocations of <span class="hlt">MODIS</span> <span class="hlt">Aqua</span>, CALIOP, we investigate the global performance of multilayer cloud detection algorithms (and thermodynamic phase).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B41D0439O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B41D0439O"><span id="translatedtitle">Landsat and <span class="hlt">MODIS</span> Fusion for Disturbance Analysis in New Zealand</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Owsley, B.; de Beurs, K.; Julian, J.</p> <p>2013-12-01</p> <p>Land management is a key driver of land change in many parts of the world. Activities such as livestock farming and timber production can have a dramatic impact on the environment and are often guided by local and regional policies. Evaluation of these impacts is particularly important in a country like New Zealand, where since 1991 political boundaries have largely coincided with environmental boundaries (catchments). In this study we look at the entire north island of New Zealand and identify disturbance trends at high spatial and temporal resolution using widely available remote sensing data, with the eventual goal of analyzing the effect of land management practices on local ecosystems. Existing remote sensing capabilities are limited in the type of analysis they allow. Free access to the entire Landsat archive provides a valuable resource for analyzing land change across large areas and extended time periods. Landsat images, at 30m spatial resolution, provide a useful tool for monitoring small changes in land cover; however, the 16-day temporal cycle, which is often lengthened considerably by cloud cover, limits the observation of short term changes that can result from disturbance events. The revisit cycle of the <span class="hlt">MODIS</span> sensors aboard Terra and <span class="hlt">Aqua</span> provides a surface <span class="hlt">reflectance</span> dataset at much higher temporal resolution, yet at 500m spatial resolution, it lacks the detail necessary to accurately track small changes in the landscape. A combination of the two products offers researchers the ideal tool for disturbance analysis. Here we utilize both Landsat TM/ETM surface <span class="hlt">reflectance</span> data and <span class="hlt">MODIS</span> Nadir BRDF-adjusted <span class="hlt">reflectance</span> (NBAR) covering the north island of New Zealand (13 Landsat path/rows) for the period 2000-2012. We calculate a disturbance index for both datasets based on normalized values of the Tasseled Cap transformation and then create a fused 8-day, 30m disturbance time series. We then investigate the time series to assess the subtle changes in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5012132','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5012132"><span id="translatedtitle">Frequency and causes of failed <span class="hlt">MODIS</span> cloud property retrievals for liquid phase clouds over global oceans</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.</p> <p>2015-01-01</p> <p>Abstract Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud <span class="hlt">reflectances</span> onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed cloud <span class="hlt">reflectances</span>. In this study, the frequency and potential causes of failed <span class="hlt">MODIS</span> retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm <span class="hlt">MODIS</span> channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar <span class="hlt">reflectivity</span> observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study. PMID:27656330</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5012132','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5012132"><span id="translatedtitle">Frequency and causes of failed <span class="hlt">MODIS</span> cloud property retrievals for liquid phase clouds over global oceans</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.</p> <p>2015-01-01</p> <p>Abstract Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud <span class="hlt">reflectances</span> onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed cloud <span class="hlt">reflectances</span>. In this study, the frequency and potential causes of failed <span class="hlt">MODIS</span> retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm <span class="hlt">MODIS</span> channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar <span class="hlt">reflectivity</span> observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015HESS...19.2337G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015HESS...19.2337G"><span id="translatedtitle">A snow cover climatology for the Pyrenees from <span class="hlt">MODIS</span> snow products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gascoin, S.; Hagolle, O.; Huc, M.; Jarlan, L.; Dejoux, J.-F.; Szczypta, C.; Marti, R.; Sanchez, R.</p> <p>2015-05-01</p> <p>The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The <span class="hlt">MODIS</span> daily snow products (Terra/MOD10A1 and <span class="hlt">Aqua</span>/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the <span class="hlt">MODIS</span> snow products in the Pyrenees. First, we compare the <span class="hlt">MODIS</span> products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively, for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, <span class="hlt">reflecting</span> the hysteresis in the relationship between the depth of the snowpack (or SWE) and its extent within a <span class="hlt">MODIS</span> pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that <span class="hlt">MODIS</span> snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50% of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=306261','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=306261"><span id="translatedtitle">Irrigation modeling with <span class="hlt">Aqua</span>Crop</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p><span class="hlt">Aqua</span>Crop is a crop water productivity model developed by the Land and Water Division of UN-FAO. It simulates yield response to water of herbaceous crops, and is suited to address conditions where water is a key limiting factor in crop production. <span class="hlt">Aqua</span>Crop attempts to balance accuracy, simplicity, an...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009270','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009270"><span id="translatedtitle"><span class="hlt">Aqua</span>'s First 10 Years: An Overview</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2012-01-01</p> <p>NASA's <span class="hlt">Aqua</span> spacecraft was launched at 2:55 a.m. on May 4, 2002, from Vandenberg Air Force Base in California, into a near-polar, sun-synchronous orbit at an altitude of 705 km. <span class="hlt">Aqua</span> carries six Earth-observing instruments to collect data on water in all its forms (liquid, vapor, and solid) and on a wide variety of additional Earth system variables (Parkinson 2003). The design lifetime for <span class="hlt">Aqua</span>'s prime mission was 6 years, and <span class="hlt">Aqua</span> is now well into its extended mission, approaching 10 years of successful operations. The <span class="hlt">Aqua</span> data have been used for hundreds of scientific studies and continue to be used for scientific discovery and numerous practical applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A21C0138M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A21C0138M"><span id="translatedtitle">Development of an Algorithm for <span class="hlt">MODIS</span> and VIIRS Cloud Optical Property Data Record Continuity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meyer, K.; Platnick, S. E.; Ackerman, S. A.; Heidinger, A. K.; Holz, R.; Wind, G.; Amarasinghe, N.; Marchant, B.</p> <p>2015-12-01</p> <p>The launch of Suomi NPP in the fall of 2011 began the next generation of U.S. operational polar orbiting environmental observations. Similar to <span class="hlt">MODIS</span>, the VIIRS imager provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> platform. However, unlike <span class="hlt">MODIS</span>, VIIRS lacks key water vapor and CO2 absorbing channels used by the <span class="hlt">MODIS</span> cloud algorithms for high cloud detection and cloud-top property retrievals. In addition, there is a significant change in the spectral location of the 2.1μm shortwave-infrared channel used by <span class="hlt">MODIS</span> for cloud optical/microphysical retrievals. Given the instrument differences between <span class="hlt">MODIS</span> EOS and VIIRS S-NPP/JPSS, we discuss our adopted method for merging the 15+ year <span class="hlt">MODIS</span> observational record with VIIRS in order to generate cloud optical property data record continuity across the observing systems. The optical property retrieval code uses heritage algorithms that produce the existing <span class="hlt">MODIS</span> cloud optical and microphysical properties product (MOD06). As explained in other presentations submitted to this session, the NOAA AWG/CLAVR-x cloud-top property algorithm and a common <span class="hlt">MODIS</span>-VIIRS cloud mask feed into the optical property algorithm to account for the different channel sets of the two imagers. Data granule and aggregated examples for the current version of the algorithm will be shown.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AtmEn.144..345L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AtmEn.144..345L"><span id="translatedtitle">Evaluation of <span class="hlt">MODIS</span> columnar aerosol retrievals using AERONET in semi-arid Nevada and California, U.S.A., during the summer of 2012</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Loría-Salazar, S. Marcela; Holmes, Heather A.; Patrick Arnott, W.; Barnard, James C.; Moosmüller, Hans</p> <p>2016-11-01</p> <p>Satellite characterization of local aerosol pollution is desirable because of the potential for broad spatial coverage, enabling transport studies of pollution from major sources, such as biomass burning events. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging over land because the underlying surface albedo may be heterogeneous in space and time. Ground-based sunphotometer measurements of AOD are unaffected by surface albedo and are crucial in enabling evaluation, testing, and further development of satellite instruments and retrieval algorithms. Columnar aerosol optical properties from ground-based sunphotometers (Cimel CE-318) as part of AERONET and <span class="hlt">MODIS</span> aerosol retrievals from <span class="hlt">Aqua</span> and Terra satellites were compared over semi-arid California and Nevada during the summer season of 2012. Sunphotometer measurements were used as a 'ground truth' to evaluate the current state of satellite retrievals in this spatiotemporal domain. Satellite retrieved (<span class="hlt">MODIS</span> Collection 6) AOD showed the presence of wildfires in northern California during August. During the study period, the dark-target (DT) retrieval algorithm appears to overestimate AERONET AOD by an average factor of 3.85 in the entire study domain. AOD from the deep-blue (DB) algorithm overestimates AERONET AOD by an average factor of 1.64. Low AOD correlation was also found between AERONET, DT, and DB retrievals. Smoke from fires strengthened the aerosol signal, but <span class="hlt">MODIS</span> versus AERONET AOD correlation hardly increased during fire events (r2∼0.1-0.2 during non-fire periods and r2∼0-0.31 during fire periods). Furthermore, aerosol from fires increased the normalized mean bias (NMB) of <span class="hlt">MODIS</span> retrievals of AOD (NMB∼23%-154% for non-fire periods and NMB∼77%-196% for fire periods). Ångström Extinction Exponent (AEE) from DB for both Terra and <span class="hlt">Aqua</span> did not correlate with AERONET observations. High surface <span class="hlt">reflectance</span> and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110010238','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110010238"><span id="translatedtitle">Ten Years of Cloud Properties from <span class="hlt">MODIS</span>: Global Statistics and Use in Climate Model Evaluation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven E.</p> <p>2011-01-01</p> <p>The NASA Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), launched onboard the Terra and <span class="hlt">Aqua</span> spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example <span class="hlt">MODIS</span> Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 <span class="hlt">MODIS</span> atmosphere team product (product names MOD08 and MYD08 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the <span class="hlt">MODIS</span> cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a <span class="hlt">MODIS</span> cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817822L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817822L"><span id="translatedtitle">New methods for reducing cloud obscuration based on combination products of <span class="hlt">MODIS</span> and AMSR2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Muyi; Pan, Yaozhong; Zhu, Xiufang; Yin, Heyang</p> <p>2016-04-01</p> <p>As one of the main sources for water availability in semi-arid mountain regions, snow melt provides runoff and water supply for the downstream population and is of great importance for both human and environmental systems. For this reason, snow data such as snow cover (SCA) and snow depth (SD) is especially important. Snow cover has been mapped using many remote sensors in the visible, near-infrared, thermal, and microwave wavelengths. Since 1966, optical remote sensors such as AVHRR, Landsat and <span class="hlt">MODIS</span> have obtained critically important data for observing the earth's snow cover. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) employed by Terra and <span class="hlt">Aqua</span> satellites provides spatially snow covered data with 500 m and daily temporal resolution. However the utility of the <span class="hlt">MODIS</span> snow-cover products is limited by cloud cover which causes gaps in the daily snow-cover map products. In this paper, we developed a new method in order to reduce cloud obscuration. This method includes four parts: A) Combining various <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> products; B) Temporal and spatial filtering; C) Zonal snowline approach and D) Combining the product deriving from the above three parts and the AMSR2 passive microwave snow depth product (with a spatial resolution of 10 km). In part D, the consistency of two different data (optical remote sensing data with spatial resolution of 500 m and passive microwave remote sensing data with a spatial resolution of 10 km) was evaluated. This study was carried out for Qinghai Province located in northwestern part of China during 1st, October, 2013 to 31st, March, 2015. In order to evaluate the performance of the proposed methodology, 14 <span class="hlt">MODIS</span> snow cover product tiles (with cloud coverage less than 10%) were selected as possible "ground truth" data and cloud mask was generated for each tile randomly. The results show successful performances arising from the methods applied, which resulted in all cloud coverage being removed. The overall accuracy of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980219479','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980219479"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1997-01-01</p> <p>We are responsible for the delivery of two at-launch products for AM-1: Fluorescence line height (FLH) and chlorophyll fluorescence efficiency (CFE). In our last report we had planned to combine the two separate algorithms into a single piece of code. However, after discussions with Bob Evans, it was decided that it was best to leave the two algorithms separate. They have been integrated into the MOCEAN processing system, and given their low computational requirements, it easier to keep them separate. In addition, there remain questions concerning the specific chlorophyll product that will be used for the CFE calculation. Presently, the CFE algorithm relies on the chlorophyll product produced by Ken Carder. This product is based on a <span class="hlt">reflectance</span> model, and is theoretically different than the chlorophyll product being provided by Dennis Clark (NOAA). These two products will be compared systematically in the coming months. If we decide to switch to the Clark product, then it will be simpler to modify the CFE algorithm if it remains separate from the FLH algorithm. Our focus for the next six months is to refine the quality flags that were delivered as part of the algorithm last summer. A description of these flags was provided to Evans for the MOCEAN processing system. A summary was included in the revised ATBD. Some of the flags depend on flags produced by the input products so coordination will be required.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.A11D0170J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.A11D0170J"><span id="translatedtitle">Regional Urban Aerosol Retrieval With <span class="hlt">MODIS</span>: High-Resolution Algorithm Application and Extension of Look-up Tables</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jerg, M. P.; Oo, M. M.; Gross, B. M.; Moshary, F.; Ahmed, S. A.</p> <p>2008-12-01</p> <p>Aerosols play an important role for the global climate by modulating the Earth's energy budget. Air quality and related health issues for humans are also tightly linked with concentration, composition, and size of aerosol particles. Satellite remote sensing with the <span class="hlt">MODIS</span> sensor on NASA's <span class="hlt">Aqua</span> and Terra platforms is one means to investigate aerosols globally. However, due to the global scope of the operational mission only globally based aerosol models can be employed in the look-up table approach of the retrieval algorithm. The relatively coarse resolution of 10x10km also largely prevents the detection of small scale structures in the aerosol optical depth (AOD) on a regional level. Consequently, the operational <span class="hlt">MODIS</span> aerosol algorithm over land has been specifically adapted to the New York City area. First, the operational look-up table was extended based on local aerosol climatology obtained using five years of AERONET measurements at the City College of New York site. These models were then used to create appropriate LUT using the 6S radiative transfer model. Second, regional surface <span class="hlt">reflectance</span> ratio parameterizations which better characterize the urban surface properties were implemented in the algorithm. These two modifications ultimately allow the retrieval algorithm to be applied at the actual sensor resolution of 500x500m. This presentation focuses on estimating the errors that are inherent in the operational processing compared to a regionally refined processing scheme. In particular, we remove artificial hot spots in the aerosol retrieval and are able to extract realistic high resolution aerosol structure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080013490','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080013490"><span id="translatedtitle">Earth System Science Research Using Datra and Products from Terra, <span class="hlt">Aqua</span>, and ACRIM Satellites</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hutchison, Keith D.</p> <p>2007-01-01</p> <p>The report describes the research conducted at CSR to extend <span class="hlt">MODIS</span> data and products to the applications required by users in the State of Texas. This research presented in this report was completed during the timeframe of August 2004 - December 31, 2007. However, since annual reports were filed in December 2005 and 2006, results obtained during calendar year 2007 are emphasized in the report. The stated goals of the project were to complete the fundamental research needed to create two types of new, Level 3 products for the air quality community in Texas from data collected by NASA s EOS Terra and <span class="hlt">Aqua</span> missions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9881E..1XM','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9881E..1XM"><span id="translatedtitle"><span class="hlt">MODIS</span> on-orbit thermal emissive bands lifetime performance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Madhavan, Sriharsha; Wu, Aisheng; Chen, Na; Xiong, Xiaoxiong</p> <p>2016-05-01</p> <p>MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), a leading heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and <span class="hlt">Aqua</span> (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-<span class="hlt">MODIS</span> currently functional beyond 15 years and the A-<span class="hlt">MODIS</span> operating beyond 13 years respectively. The <span class="hlt">MODIS</span> sensor characteristics include a spectral coverage from 0.41 μm - 14.4 μm, of which wavelengths ranging from 3.7 μm - 14. 4 μm cover the thermal infrared region also referred to as the Thermal Emissive Bands (TEBs). The TEBs is calibrated using a v-grooved BlackBody (BB) whose temperature measurements are traceable to the National Institute of Standards and Technology temperature scales. The TEBs calibration based on the onboard BB is extremely important for its high radiometric fidelity. In this paper, we provide a complete characterization of the lifetime instrument performance of both <span class="hlt">MODIS</span> instruments in terms of the sensor gain, the Noise Equivalent difference Temperature, key instrument telemetry such as the BB lifetime trends, the instrument temperature trends, the Cold Focal Plane telemetry and finally, the total assessed calibration uncertainty of the TEBs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171197','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171197"><span id="translatedtitle"><span class="hlt">MODIS</span> Snow and Sea Ice Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.</p> <p>2004-01-01</p> <p>In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Terra and <span class="hlt">Aqua</span> snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080002214&hterms=eve&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Deve','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080002214&hterms=eve&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Deve"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span>-Derived Visible and Near-IR Aerosol Optical Properties and their Spatial Variability in the Presence of Mineral Dust</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Redemann, J.; Zhang, Q.; Schmid, B.; Russell, P. B.; Livingston, J. M.; Jonsson, H.; Remer, L. A.</p> <p>2006-01-01</p> <p>Mineral dust aerosol is among the most difficult aerosol species to measure quantitatively from space. In this paper, we evaluate <span class="hlt">MODIS</span> retrievals of spectral aerosol optical depth (AOD) from the visible to the near-IR off the US West Coast using measurements taken by the NASA Ames Airborne Tracking Sunphotometer, AATS-14, during the EVE (Extended-<span class="hlt">MODIS</span>-lambda Validation Experiment, 2004) campaign in April of 2004. In EVE, a total of 35 and 49 coincident over-ocean suborbital measurements at the nominal level-2 retrieval scale of 10 km x 10 km were collected for Terra and <span class="hlt">Aqua</span>, respectively. For <span class="hlt">MODIS</span>-Terra about 80% of the AOD retrievals are within the estimated uncertainty, DELTA tau = plus or minus 0.03 plus or minus 0.05 tau; this is true for both the visible (here defined to include 466-855 nm) and near-IR (here defined to include 1243-2119 nm) retrievals. For <span class="hlt">MODIS-Aqua</span> about 45% of the AOD retrievals are within DELTA tau = plus or minus 0.03 plus or minus 0.05 tau; the fraction of near-IR retrievals that fall within this uncertainty range is about 27%. We found an rms difference of 0.71 between the sunphotometer snd <span class="hlt">MODIS-Aqua</span> estimates of the visible (553-855 nm) Angstrom exponent, while the <span class="hlt">MODIS</span>-Terra visible Angstrom exponents show an rms difference of only 0.29 when compared to AATS. The cause of the differences in performance between <span class="hlt">MODIS</span>-Terra and <span class="hlt">MODIS-Aqua</span> could be instrument calibration and needs to be explored further. The spatial variability of AOD between retrieval boxes as derived by <span class="hlt">MODIS</span> is generally larger than that indicated by the sunphotometer data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.U41B0019F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.U41B0019F"><span id="translatedtitle">The Unique Capabilities of the <span class="hlt">Aqua</span> Sensors to Characterize the Planetary Boundary Layer</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fishbein, E.; Behrangi, A.; Fetzer, E.; Kahn, B. H.; Schreier, M. M.; Teixeira, J.; Yue, Q.</p> <p>2011-12-01</p> <p>Boundary layer clouds are poorly represented in climate models and remain one of the largest uncertainties in climate projects. The A-train sensors, primarily <span class="hlt">MODIS</span>, AMSR and AIRS on <span class="hlt">Aqua</span>, the Cloudsat CPR and the Calipso CALIOP provide a unique and comprehensive characterization of the hydrological state of the cloudy boundary layer. <span class="hlt">MODIS</span> near IR provides total water vapor above the boundary layer clouds, AMSR total water vapor through the cloud to the surface, and CPR and CALIOP, the height of the clouds. This presentation summarizes characterization of boundary layer water vapor in the transition from stratocumulus to trade cumulus along the GEWEX Cloud System Study (GCSS) Pacific Cross-Section Intercomparison (GPCI) transect.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A51E..02H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A51E..02H"><span id="translatedtitle">Recent Progress on Deep Blue Aerosol Algorithm as Applied to <span class="hlt">Modis</span>, Seawifs, and Viirs, and Their Intercomparisons with Ground Based and Other Satellite Measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hsu, N. C.; Bettenhausen, C.; Sayer, A. M.; Tsay, S.</p> <p>2011-12-01</p> <p>The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/<span class="hlt">MODIS</span> in 1999, and <span class="hlt">Aqua/MODIS</span> in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/<span class="hlt">MODIS</span> aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these SeaWiFS/<span class="hlt">MODIS</span> aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-<span class="hlt">reflecting</span> surfaces into SeaWiFS/<span class="hlt">MODIS</span> as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/<span class="hlt">MODIS</span> retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol loadings</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011581','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011581"><span id="translatedtitle">Recent Progress on Deep Blue Aerosol Algorithm as Applied TO <span class="hlt">MODIS</span>, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina; Bettenhausen, Corey; Sawyer, Andrew; Tsay, Si-Chee</p> <p>2012-01-01</p> <p>The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/<span class="hlt">MODIS</span> in 1999, and <span class="hlt">Aqua/MODIS</span> in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/<span class="hlt">MODIS</span> aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / <span class="hlt">MODIS</span> aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-<span class="hlt">reflecting</span> surfaces into Sea WiFS / <span class="hlt">MODIS</span> as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/<span class="hlt">MODIS</span> retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eosweb.larc.nasa.gov/project/ceres/es4_aqua-xtrk_ed3_table','SCIGOV-ASDC'); return false;" href="https://eosweb.larc.nasa.gov/project/ceres/es4_aqua-xtrk_ed3_table"><span id="translatedtitle">ES4 <span class="hlt">Aqua</span>-Xtrk Ed3</span></a></p> <p><a target="_blank" href="http://eosweb.larc.nasa.gov/">Atmospheric Science Data Center </a></p> <p></p> <p>2016-10-12</p> <p>... Temporal Resolution:  Monthly, Daily, Monthly Hourly File Format:  HDF Tools:  ... for Terra and <span class="hlt">Aqua</span>; Edition2 for TRMM) are approved for science publications.  Additional Info:  a SCAR-B ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1510810P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1510810P"><span id="translatedtitle">Sensitivity of cloud retrieval statistics to algorithm choices: Lessons learned from <span class="hlt">MODIS</span> product development</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Platnick, Steven; Ackerman, Steven; King, Michael; Zhang, Zhibo; Wind, Galina</p> <p>2013-04-01</p> <p>Cloud detection algorithms search for measurement signatures that differentiate a cloud-contaminated or "not-clear" pixel from the clear-sky background. These signatures can be spectral, textural or temporal in nature. The magnitude of the difference between the cloud and the background must exceed a threshold value for the pixel to be classified having a not-clear FOV. All detection algorithms employ multiple tests ranging across some portion of the solar <span class="hlt">reflectance</span> and/or infrared spectrum. However, a cloud is not a single, uniform object, but rather has a distribution of optical thickness and morphology. As a result, problems can arise when the distributions of cloud and clear-sky background characteristics overlap, making some test results indeterminate and/or leading to some amount of detection misclassification. Further, imager cloud retrieval statistics are highly sensitive to how a pixel identified as not-clear by a cloud mask is determined to be useful for cloud-top and optical retrievals based on 1-D radiative models. This presentation provides an overview of the different 'choices' algorithm developers make in cloud detection algorithms and the impact on regional and global cloud amounts and fractional coverage, cloud type and property distributions. Lessons learned over the course of the <span class="hlt">MODIS</span> cloud product development history are discussed. As an example, we will focus on the 1km <span class="hlt">MODIS</span> Collection 5 cloud optical retrieval algorithm (product MOD06/MYD06 for Terra and <span class="hlt">Aqua</span>, respectively) which removed pixels associated with cloud edges as defined by immediate adjacency to clear FOV <span class="hlt">MODIS</span> cloud mask (MOD35/MYD35) pixels as well as ocean pixels with partly cloudy elements in the 250m <span class="hlt">MODIS</span> cloud mask - part of the so-called Clear Sky Restoral algorithm. The Collection 6 algorithm attempts retrievals for these two types of partly cloudy pixel populations, but allows a user to isolate or filter out the populations. Retrieval sensitivities for these</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AGUFM.A31K..08M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AGUFM.A31K..08M&link_type=ABSTRACT"><span id="translatedtitle">Bias Correction of high resolution <span class="hlt">MODIS</span> Aerosol Optical Depth in urban areas using the Dragon AERONET Network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malakar, N. K.; Atia, A.; Gross, B.; Moshary, F.; Ahmed, S. A.; Lary, D. J.</p> <p>2013-12-01</p> <p>Aerosol optical depth (AOD) is widely used parameter used to quantify aerosol abundance. Satellite retrievals of aerosols over land is fundamentally more complex than aerosol retrieval over oceans. Due to wide coverage and the extensive validation the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), on board the Terra and <span class="hlt">Aqua</span> satellites is the workhorse instrument used to retrieve AOD from space. However, satellite algorithms of AOD are extremely complex and depends strongly on sun/view geometry, spectral surface albedo, aerosol model assumptions and surface heterogeneity. This issue becomes even more severe when considering the new <span class="hlt">MODIS</span> 3 km aerosol retrieval products within version 6. To assess satellite retrievals of these high resolution 3 km products, we use the summer 2011 Dragon AERONET data to assess accuracy as well as major retrieval bias that can occur in <span class="hlt">MODIS</span> measurements. In this study, we explore in detail the factors that can drive these biases statistically. As discussed above, our considers multiple conditions such as surface <span class="hlt">reflectivity</span> at various wavelengths, solar and sensor zenith angles, the solar and sensor azimuth, scattering angles as well as meteorological factors and aerosol type (angstrom coefficient) etc which are used inputs are used to train neural network in regression mode to compensate for biases against the Dragon AERONET AOD values. In particular, we confirm the results of previous studies where the land cover (urban fraction) appears to be a strong factor in AOD bias and develop a NN estimator which includes land cover directly. The algorithm will be tested not only in the Baltimore/Washington area but assessed in the general North East US where urban biases in the NYC area have been previously identified.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140005684','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140005684"><span id="translatedtitle">The <span class="hlt">Aqua</span>-Planet Experiment (APE): CONTROL SST Simulation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blackburn, Michael; Williamson, David L.; Nakajima, Kensuke; Ohfuchi, Wataru; Takahashi, Yoshiyuki O.; Hayashi, Yoshi-Yuki; Nakamura, Hisashi; Ishiwatari, Masaki; Mcgregor, John L.; Borth, Hartmut; Wirth, Volkmar; Frank, Helmut; Bechtold, Peter; Wedi, Nils P.; Tomita, Hirofumi; Satoh, Masaki; Zhao, Ming; Held, Isaac M.; Suarez, Max J.; Lee, Myong-In; Watanabe, Masahiro; Kimoto, Masahide; Liu, Yimin; Wang, Zaizhi; Molod, Andrea M.; Rajendran, Kavirajan; Kotoh, Akio; Stratton, Rachel</p> <p>2013-01-01</p> <p>Climate simulations by 16 atmospheric general circulation models (AGCMs) are compared on an <span class="hlt">aqua</span>-planet, a water-covered Earth with prescribed sea surface temperature varying only in latitude. The idealised configuration is designed to expose differences in the circulation simulated by different models. Basic features of the <span class="hlt">aqua</span>-planet climate are characterised by comparison with Earth. The models display a wide range of behaviour. The balanced component of the tropospheric mean flow, and mid-latitude eddy covariances subject to budget constraints, vary relatively little among the models. In contrast, differences in damping in the dynamical core strongly influence transient eddy amplitudes. Historical uncertainty in modelled lower stratospheric temperatures persists in APE.Aspects of the circulation generated more directly by interactions between the resolved fluid dynamics and parameterized moist processes vary greatly. The tropical Hadley circulation forms either a single or double inter-tropical convergence zone (ITCZ) at the equator, with large variations in mean precipitation. The equatorial wave spectrum shows a wide range of precipitation intensity and propagation characteristics. Kelvin mode-like eastward propagation with remarkably constant phase speed dominates in most models. Westward propagation, less dispersive than the equatorial Rossby modes, dominates in a few models or occurs within an eastward propagating envelope in others. The mean structure of the ITCZ is related to precipitation variability, consistent with previous studies.The <span class="hlt">aqua</span>-planet global energy balance is unknown but the models produce a surprisingly large range of top of atmosphere global net flux, dominated by differences in shortwave <span class="hlt">reflection</span> by clouds. A number of newly developed models, not optimised for Earth climate, contribute to this. Possible reasons for differences in the optimised models are discussed.The <span class="hlt">aqua</span>-planet configuration is intended as one component of an</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011127','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011127"><span id="translatedtitle"><span class="hlt">MODIS</span> Science Algorithms and Data Systems Lessons Learned</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wolfe, Robert E.; Ridgway, Bill L.; Patt, Fred S.; Masuoka, Edward J.</p> <p>2009-01-01</p> <p>For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors are being used world-wide for earth science research and applications. This paper discusses the lessons learned in developing the science algorithms and the data systems needed to produce these high quality data products for the earth sciences community. Strong science team leadership and communication, an evolvable and scalable data system, and central coordination of QA and validation activities enabled the data system to grow by two orders of magnitude from the initial at-launch system to the current system able to reprocess data from both the Terra and <span class="hlt">Aqua</span> missions in less than a year. Many of the lessons learned from <span class="hlt">MODIS</span> are already being applied to follow-on missions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171588','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171588"><span id="translatedtitle">Application of <span class="hlt">MODIS</span>-Derived Active Fire Radiative Energy to Fire Disaster and Smoke Pollution Monitoring</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Kaufman, Yoram J.; Hao, Wei Min; Habib, Shahid</p> <p>2004-01-01</p> <p>The radiative energy emitted by large fires and the corresponding smoke aerosol loading are simultaneously measured from the <span class="hlt">MODIS</span> sensor from both the Terra and <span class="hlt">Aqua</span> satellites. Quantitative relationships between the rates of emission of fire radiative energy and smoke are being developed for different fire-prone regions of the globe. Preliminary results are presented. When fully developed, the system will enable the use of <span class="hlt">MODIS</span> direct broadcast fire data for near real-time monitoring of fire strength and smoke emission as well as forecasting of fire progression and smoke dispersion, several hours to a few days in advance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B32D..02D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B32D..02D"><span id="translatedtitle">Urban Area Monitoring using <span class="hlt">MODIS</span> Time Series Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Devadiga, S.; Sarkar, S.; Mauoka, E.</p> <p>2015-12-01</p> <p>Growing urban sprawl and its impact on global climate due to urban heat island effects has been an active area of research over the recent years. This is especially significant in light of rapid urbanization that is happening in some of the first developing nations across the globe. But so far study of urban area growth has been largely restricted to local and regional scales, using high to medium resolution satellite observations, taken at distinct time periods. In this presentation we propose a new approach to detect and monitor urban area expansion using long time series of <span class="hlt">MODIS</span> data. This work characterizes data points using a vector of several annual metrics computed from the <span class="hlt">MODIS</span> 8-day and 16-day composite L3 data products, at 250M resolution and over several years and then uses a vector angle mapping classifier to detect and segment the urban area. The classifier is trained using a set of training points obtained from a reference vector point and polygon pre-filtered using the <span class="hlt">MODIS</span> VI product. This work gains additional significance, given that, despite unprecedented urban growth since 2000, the area covered by the urban class in the <span class="hlt">MODIS</span> Global Land Cover (MCD12Q1, MCDLCHKM and MCDLC1KM) product hasn't changed since the launch of Terra and <span class="hlt">Aqua</span>. The proposed approach was applied to delineate the urban area around several cities in Asia known to have maximum growth in the last 15 years. Results were verified using high resolution Landsat data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007001','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007001"><span id="translatedtitle">Detailed Evaluation of <span class="hlt">MODIS</span> Fire Radiative Power Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles</p> <p>2010-01-01</p> <p>Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the <span class="hlt">MODIS</span> sensors aboard the polar orbiting Terra and <span class="hlt">Aqua</span> satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has been gaining recognition as an important parameter for facilitating the development of various scientific studies relating to the quantitative characterization of biomass burning and their emissions. Therefore, we are conducting a detailed analysis of the FRP products from <span class="hlt">MODIS</span> to characterize the uncertainties associated with them, such as those due to the <span class="hlt">MODIS</span> bow-tie effects and other factors, in order to establish their error budget for use in scientific research and applications. In this presentation, we will show preliminary results of the <span class="hlt">MODIS</span> FRP data analysis, including comparisons with airborne measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EOSTr..84..313H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EOSTr..84..313H"><span id="translatedtitle"><span class="hlt">MODIS</span> detects oil spills in Lake Maracaibo, Venezuela</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hu, Chuanmin; Müller-Karger, Frank E.; Taylor, Charles (Judd); Myhre, Douglas; Murch, Brock; Odriozola, Ana L.; Godoy, Gonzalo</p> <p></p> <p>Starting December 2002, the oil industry operating in and around Lake Maracaibo in Venezuela suffered a series of accidents (Figure 1). Fires, the sinking of two barges, rupture of oil pipelines, spills from floating oil storage and transfer stations, and malfunctioning of oil extraction platforms led to extensive oil spills. Local and federal Venezuelan government oil industry experts directly observed the series of spills from aircraft, helicopter, and various surface vessels. The spills were recorded in December by official photography and video of leaking infrastructure, and unofficial recordings continued in January and February 2003 (http://wwwcomlago.com.ve/fotosvideos. html).These surveys did not provide sufficient spatial or temporal coverage to assess the magnitude, area covered, or duration of the spills. Clear images of the spill were captured with NASAs Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), however. <span class="hlt">MODIS</span> is effectively a sophisticated digital camera launched aboard the Terra satellite in December 1999, and aboard the <span class="hlt">Aqua</span> satellite in April 2002 [Esaias et al., 1998; http://<span class="hlt">modis</span>.gsfc.nasa.gov]. Its medium-resolution bands (250 and 500 m resolution) are available to the public, and have great potential in coastal monitoring. This article demonstrates how <span class="hlt">MODIS</span> can provide basic and critical assessments of oil spills.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22545030','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22545030"><span id="translatedtitle">Terra and <span class="hlt">Aqua</span>: new data for epidemiology and public health.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tatem, Andrew J; Goetz, Scott J; Hay, Simon I</p> <p>2004-11-01</p> <p>Earth-observing satellites have only recently been exploited for the measurement of environmental variables of relevance to epidemiology and public health. Such work has relied on sensors with spatial, spectral and geometric constraints that have allowed large-area questions associated with the epidemiology of vector-borne diseases to be addressed. Moving from pretty maps to pragmatic control tools requires a suite of satellite-derived environmental data of higher fidelity, spatial resolution, spectral depth and at similar temporal resolutions to existing meteorological satellites. Information derived from sensors onboard the next generation of moderate-resolution Earth-observing sensors may provide the key. The <span class="hlt">MODIS</span> and ASTER sensors onboard the Terra and <span class="hlt">Aqua</span> platforms provide substantial improvements in spatial resolution, number of spectral channels, choices of bandwidths, radiometric calibration and a much-enhanced set of pre-processed and freely available products. These sensors provide an important advance in moderate-resolution remote sensing and the data available to those concerned with improving public health.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..12012237M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..12012237M"><span id="translatedtitle">Investigating the impact of haze on <span class="hlt">MODIS</span> cloud detection</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mao, Feiyue; Duan, Miaomiao; Min, Qilong; Gong, Wei; Pan, Zengxin; Liu, Guangyi</p> <p>2015-12-01</p> <p>The cloud detection algorithm for passive sensors is usually based on a fuzzy logic system with thresholds determined from previous observations. In recent years, haze and high aerosol concentrations with high aerosol optical depth (AOD) occur frequently in China and may critically impact the accuracy of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) cloud detection. Thus, we comprehensively explore this impact by comparing the results from <span class="hlt">MODIS/Aqua</span> (passive sensor), Cloud-Aerosol Lidar with Orthogonal Polarization/CALIPSO (lidar sensor), and Cloud Profiling Radar/CloudSat (microwave sensor) of the A-Train suite of instruments using an averaged AOD as an index for an aerosol concentration value. Case studies concerning the comparison of the three sensors indicate that <span class="hlt">MODIS</span> cloud detection is reduced during haze events. In addition, statistical studies show that an increase in AOD creates an increase in the percentage of uncertain flags and a decrease in hit rate, a consistency index between consecutive sets of cloud retrievals. On average, AOD values lower than 0.1 give hit rate values up to 80.0% and uncertainty values lower than 16.8%, while AOD values greater than 1.0 reduce the hit rate below to 66.6% and increase the percentage of uncertain flags up to 46.6%. Therefore, we can conclude that the ability of <span class="hlt">MODIS</span> cloud detection is weakened by large concentrations of aerosols. This suggests that use of the <span class="hlt">MODIS</span> cloud mask, and derived higher-level products, in situations with haze requires caution. Further improvement of this retrieval algorithm is desired as haze studies based on <span class="hlt">MODIS</span> products are of great interest in a number of related fields.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9639E..13M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9639E..13M"><span id="translatedtitle">Evaluation of VIIRS and <span class="hlt">MODIS</span> thermal emissive band calibration consistency using Dome C</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Madhavan, Sriharsha; Wu, Aisheng; Brinkmann, Jake; Wenny, Brian; Xiong, Xiaoxiong</p> <p>2015-10-01</p> <p>The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is designed based on <span class="hlt">MODIS</span> heritage and uses a similar on-board calibrating source - a V-grooved blackbody for the Thermal Emissive Bands (TEBs). Except for the 10.7 μm band, the central wavelengths of the rest of the VIIRS TEBs match well with <span class="hlt">MODIS</span>. To ensure the continuity and consistency of data records between VIIRS and <span class="hlt">MODIS</span> TEBs, it is important to assess any systematic differences between the two instruments for scenes with temperatures significantly lower than blackbody operating temperatures at ~290 K. In previous studies, the <span class="hlt">MODIS</span> Calibration and Characterization Support Team (MCST) at NASA/GSFC uses recurrent observations of Dome C, Antarctica by both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> over the mission lifetime to track their calibration stability and consistency. Near-surface temperature measurements from an Automatic Weather Station (AWS) provide a proxy reference useful for tracking the stability and determining the relative bias between the two <span class="hlt">MODIS</span> instruments. In this study, the same approach is applied to VIIRS TEBs and the results are compared with those from the matched <span class="hlt">MODIS</span> TEBs. The results of this study provide a quantitative assessment for VIIRS TEBs performance over the first three years of the mission.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110006352','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110006352"><span id="translatedtitle">Results and Lessons from a Decade of Terra <span class="hlt">MODIS</span> On-Orbit Spectral Characterization</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Choi, T.; Che, N.; Wang, Z.; Dodd, J.</p> <p>2010-01-01</p> <p>Since its launch in December 1999, the NASA EOS Terra <span class="hlt">MODIS</span> has successfully operated for more than a decade. <span class="hlt">MODIS</span> makes observations in 36 spectral bands from visible (VIS) to longwave infrared (LWIR) and at three nadir spatial resolutions: 250m (2 bands), 500m (5 bands), and 1km (29 bands). In addition to its on-board calibrators designed for the radiometric calibration, <span class="hlt">MODIS</span> was built with a unique device, called the spectro-radiometric calibration assembly (SRCA). It can be configured in three different modes: radiometric, spatial, and spectral. When it is operated in the spectral modes, the SRCA can monitor changes in Sensor spectral performance for the VIS and near-infrared (NIR) spectral bands. For more than 10 years, the SRCA operation has continued to provide valuable information for <span class="hlt">MODIS</span> on-orbit spectral performance. This paper briefly describes SRCA on-orbit operation and calibration activities; it presents decade-long spectral characterization results for Terra <span class="hlt">MODIS</span> VIS and NIR spectral bands in terms of chances in their center wavelengths (CW) and bandwidths (BW). It is shown that the SRCA on-orbit wavelength calibration capability remains satisfactory. For most spectral bands, the changes in CW and BW are less than 0.5 and 1 nm, respectively. Results and lessons from Terra <span class="hlt">MODIS</span> on-orbit spectral characterization have and will continue to benefit its successor, <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, and other future missions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B11A0003M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B11A0003M"><span id="translatedtitle">Multiangular Contributions for Discriminate Seasonal Structural Changes in the Amazon Rainforest Using <span class="hlt">MODIS</span> MAIAC Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moura, Y. M.; Hilker, T.; Galvão, L. S.; Santos, J. R.; Lyapustin, A.; Sousa, C. H. R. D.; McAdam, E.</p> <p>2014-12-01</p> <p>The sensitivity of the Amazon rainforests to climate change has received great attention by the scientific community due to the important role that this vegetation plays in the global carbon, water and energy cycle. The spatial and temporal variability of tropical forests across Amazonia, and their phenological, ecological and edaphic cycles are still poorly understood. The objective of this work was to infer seasonal and spatial variability of forest structure in the Brazilian Amazon based on anisotropy of multi-angle satellite observations. We used observations from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>/Terra and <span class="hlt">Aqua</span>) processed by a new Multi-Angle Implementation Atmospheric Correction Algorithm (MAIAC) to investigate how multi-angular spectral response from satellite imagery can be used to analyze structural variability of Amazon rainforests. We calculated differences acquired from forward and backscatter <span class="hlt">reflectance</span> by modeling the bi-directional <span class="hlt">reflectance</span> distribution function to infer seasonal and spatial changes in vegetation structure. Changes in anisotropy were larger during the dry season than during the wet season, suggesting intra-annual changes in vegetation structure and density. However, there were marked differences in timing and amplitude depending on forest type. For instance differences between <span class="hlt">reflectance</span> hotspot and darkspot showed more anisotropy in the open Ombrophilous forest than in the dense Ombrophilous forest. Our results show that multi-angle data can be useful for analyzing structural differences in various forest types and for discriminating different seasonal effects within the Amazon basin. Also, multi-angle data could help solve uncertainties about sensitivity of different tropical forest types to light versus rainfall. In conclusion, multi-angular information, as expressed by the anisotropy of spectral <span class="hlt">reflectance</span>, may complement conventional studies and provide significant improvements over approaches that</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040055392','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040055392"><span id="translatedtitle">Land Surface Temperature Measurements from EOS <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wan, Zheng-Ming</p> <p>2004-01-01</p> <p>This report summarizes the accomplishments made by the <span class="hlt">MODIS</span> LST (Land-Surface Temperature) group at University of California, Santa Barbara, under NASA Contract. Version 1 of the <span class="hlt">MODIS</span> Land-Surface Temperature Algorithm Theoretical Basis Document (ATBD) was reviewed in June 1994, version 2 reviewed in November 1994, version 3.1 in August 1996, and version 3.3 updated in April 1999. Based on the ATBD, two LST algorithms were developed, one is the generalized split-window algorithm and another is the physics-based day/night LST algorithm. These two LST algorithms were implemented into the production generation executive code (PGE 16) for the daily standard <span class="hlt">MODIS</span> LST products at level-2 (MODII-L2) and level-3 (MODIIA1 at 1 km resolution and MODIIB1 at 5km resolution). PGE codes for 8-day 1 km LST product (MODIIA2) and the daily, 8-day and monthly LST products at 0.05 degree latitude/longitude climate model grids (CMG) were also delivered. Four to six field campaigns were conducted each year since 2000 to validate the daily LST products generated by PGE16 and the calibration accuracies of the <span class="hlt">MODIS</span> TIR bands used for the LST/emissivity retrieval from versions 2-4 of Terra <span class="hlt">MODIS</span> data and versions 3-4 of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data. Validation results from temperature-based and radiance-based methods indicate that the <span class="hlt">MODIS</span> LST accuracy is better than 1 C in most clear-sky cases in the range from -10 to 58 C. One of the major lessons learn from multi- year temporal analysis of the consistent V4 daily Terra <span class="hlt">MODIS</span> LST products in 2000-2003 over some selected target areas including lakes, snow/ice fields, and semi-arid sites is that there are variable numbers of cloud-contaminated LSTs in the <span class="hlt">MODIS</span> LST products depending on surface elevation, land cover types, and atmospheric conditions. A cloud-screen scheme with constraints on spatial and temporal variations in LSTs was developed to remove cloud-contaminated LSTs. The 5km LST product was indirectly validated through comparisons to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120010373&hterms=terra&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dterra','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120010373&hterms=terra&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dterra"><span id="translatedtitle">On-Orbit Spatial Characterization of <span class="hlt">MODIS</span> with ASTER Aboard the Terra Spacecraft</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xie, Yong; Xiong, Xiaoxiong</p> <p>2011-01-01</p> <p>This letter presents a novel approach for on-orbit characterization of MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) band-to-band registration (BBR) using Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER) aboard the Terra spacecraft. The spatial resolution of ASTER spectral bands is much higher than that of <span class="hlt">MODIS</span>, making it feasible to characterize <span class="hlt">MODIS</span> on-orbit BBR using their simultaneous observations. The ground target selected for on-orbit <span class="hlt">MODIS</span> BBR characterization in this letter is a water body, which is a uniform scene with high signal contrast relative to its neighbor areas. A key step of this approach is to accurately localize the measurements of each <span class="hlt">MODIS</span> band in an ASTER measurement plane coordinate (AMPC). The ASTER measurements are first interpolated and aggregated to simulate the measurements of each <span class="hlt">MODIS</span> band. The best measurement match between ASTER and each <span class="hlt">MODIS</span> band is obtained when the measurement difference reaches its weighted minimum. The position of each <span class="hlt">MODIS</span> band in the AMPC is then used to calculate the BBR. The results are compared with those derived from <span class="hlt">MODIS</span> onboard Spectro-Radiometric Calibration Assembly. They are in good agreement, generally less than 0.1 <span class="hlt">MODIS</span> pixel. This approach is useful for other sensors without onboard spatial characterization capability. Index Terms Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER), band-to-band registration (BBR), MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), spatial characterization.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080039625','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080039625"><span id="translatedtitle">An Emerging Global Aerosol Climatology from the <span class="hlt">MODIS</span> Satellite Sensors</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, Lorraine A.; Kleidman, Richard G.; Levy, Robert C.; Kaufman, Yoram J.; Tanre, Didier; Mattoo, Shana; Martins, J. Vandelei; Ichoku, Charles; Koren, Ilan; Hongbin, Yu; Holben, Brent N.</p> <p>2008-01-01</p> <p>The recently released Collection 5 <span class="hlt">MODIS</span> aerosol products provide a consistent record of the Earth's aerosol system. Comparison with ground-based AERONET observations of aerosol optical depth (AOD) we find that Collection 5 <span class="hlt">MODIS</span> aerosol products estimate AOD to within expected accuracy more than 60% of the time over ocean and more than 72% of the time over land. This is similar to previous results for ocean, and better than the previous results for land. However, the new Collection introduces a 0.01 5 offset between the Terra and <span class="hlt">Aqua</span> global mean AOD over ocean, where none existed previously. <span class="hlt">Aqua</span> conforms to previous values and expectations while Terra is high. The cause of the offset is unknown, but changes to calibration are a possible explanation. We focus the climatological analysis on the better understood <span class="hlt">Aqua</span> retrievals. We find that global mean AOD at 550 nm over oceans is 0.13 and over land 0.19. AOD in situations with 80% cloud fraction are twice the global mean values, although such situations occur only 2% of the time over ocean and less than 1% of the time over land. There is no drastic change in aerosol particle size associated with these very cloudy situations. Regionally, aerosol amounts vary from polluted areas such as East Asia and India, to the cleanest regions such as Australia and the northern continents. In almost all oceans fine mode aerosol dominates over dust, except in the tropical Atlantic downwind of the Sahara and in some months the Arabian Sea.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120002594&hterms=Cirrus+clouds&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3D%2528Cirrus%2Bclouds%2529','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120002594&hterms=Cirrus+clouds&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3D%2528Cirrus%2Bclouds%2529"><span id="translatedtitle">Utilizing the <span class="hlt">MODIS</span> 1.38 micrometer Channel for Cirrus Cloud Optical Thickness Retrievals: Algorithm and Retrieval Uncertainties</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meyer, Kerry; Platnick, Steven</p> <p>2010-01-01</p> <p>The cloud products from the Moderate Resolution Imaging Spectroradiometers (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span> have been widely used within the atmospheric research community. The retrieval algorithms, however, oftentimes have difficulty detecting and retrieving thin cirrus, due to sensitivities to surface <span class="hlt">reflectance</span>. Conversely, the 1.38 micron channel, located within a strong water vapor absorption band, is quite useful for detecting thin cirrus clouds since the signal from the surface can be blocked or substantially attenuated by the absorption of atmospheric water vapor below cirrus. This channel, however, suffers from nonnegligible attenuation due to the water vapor located above and within the cloud layer. Here we provide details of a new technique pairing the 1.38 micron and 1.24 micron channels to estimate the above/in-cloud water vapor attenuation and to subsequently retrieve thin cirrus optical thickness (tau) from attenuation-corrected 1.38 p.m <span class="hlt">reflectance</span> measurements. In selected oceanic cases, this approach is found to increase cirrus retrievals by up to 38% over MOD06. For these cases, baseline 1.38 micron retrieval uncertainties are estimated to be between 15 and 20% for moderately thick cirrus (tau > 1), with the largest error source being the unknown cloud effective particle radius, which is not retrieved with the described technique. Uncertainties increase to around 90% for the thinnest clouds (tau < 0.5) where instrument and surface uncertainties dominate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMIN21C1344C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMIN21C1344C"><span id="translatedtitle">Ground-based vicarious radiometric calibration of Landsat 7 ETM+ and Terra <span class="hlt">MODIS</span> using an automated test site</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Czapla-Myers, J.; Leisso, N.</p> <p>2010-12-01</p> <p>The Remote Sensing Group at the University of Arizona has operated the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley, Nevada, since 2004. It is an approach to ground-based vicarious calibration that does not require on-site personnel to make surface and atmospheric measurements during a satellite overpass. It was originally developed in 2002 in an attempt to increase the amount of data collected throughout the year while maintaining the accuracy of in-situ measurements. RadCaTS currently consists of four ground-viewing radiometers to measure surface <span class="hlt">reflectance</span>, a Cimel sun photometer to make atmospheric measurements, and a weather station to measure ambient conditions. The data from these instruments are used in MODTRAN 5 to determine the top-of-atmosphere (TOA) spectral radiance for a given overpass time, and the results are compared to the sensor under test. The work presented here describes the RadCaTS instrumentation suite and automated processing scheme used to determine the surface <span class="hlt">reflectance</span> and TOA spectral radiance. The instruments used to measure surface and atmospheric properties are presented, followed by a discussion of their spatial layout and their radiometric calibration. The RadCaTS ground-based results are compared to those from <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> overpasses in 2008, and Landsat 7 ETM+ overpasses in 2009.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006433','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006433"><span id="translatedtitle">Cloud Properties of CERES-<span class="hlt">MODIS</span> Edition 4 and CERES-VIIRS Edition 1</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky; Chu, Churngwei; Heckert, Elizabeth; Gibson, Sharon; Heck, Patrick W.</p> <p>2015-01-01</p> <p>The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from <span class="hlt">Aqua</span> using the CERES-<span class="hlt">MODIS</span> Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for <span class="hlt">Aqua</span>). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-<span class="hlt">MODIS</span> Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-<span class="hlt">MODIS</span> Edition-2 results.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AIPC.1100..105D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AIPC.1100..105D"><span id="translatedtitle">Surface Albedo Assessment in Clear Sky and Dense Smoke Atmospheres Using a Shortwave Radiation Stochastic Model and <span class="hlt">MODIS</span> 1B Image</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>de Souza, Juarez D.; Ceballos, Juan C.; da Silva, Bernardo B.</p> <p>2009-03-01</p> <p>The surface albedo, which is a fundamental parameter in the estimation of the radiation balance, corresponds to the <span class="hlt">reflectance</span> integrated in the solar spectrum. It can be obtained through satellite images that have great spatial coverage. A stochastic model of two-flux, presented by Ceballos [1] and developed by Souza and Ceballos [2], is used to establish a direct relationship between the <span class="hlt">reflectance</span> of the surface and the radiance measured by <span class="hlt">MODIS-Terra/Aqua</span> sensor. The propagation of radiation, in the solar spectrum from 0.3 to 3.0 μm, is described by an scheme of 16 layers. In such scheme, it is obtained the necessary parameters to establish the radiation balance in the top of the atmosphere. The optical properties of the atmospheric layers are defined by aerosol, ozone and water vapor. In this way, to determine the surface albedo, it is considered that the radiance originated from the system earth-atmosphere, measured by the satellite, is isotropic. A simple adjustment factor is introduced to compensate anisotropic and multiple <span class="hlt">reflections</span> effects between the surface and the atmosphere. An application for Amazonian region in conditions of low and high aerosol load due to smoke caused by forest burning, is presented. The results show similarity in the assessed surface <span class="hlt">reflectance</span>, with and without burning in the region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20000118270&hterms=Urbanization&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DUrbanization','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20000118270&hterms=Urbanization&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DUrbanization"><span id="translatedtitle">Remote Sensing of Aerosol Over the Land from the Earth Observing System <span class="hlt">MODIS</span> Instrument</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Einaudi, Franco (Technical Monitor)</p> <p>2000-01-01</p> <p>On Dec 18, 1999, NASA launched the Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument on the Earth Observing System (EOS) Terra mission, in a spectacular launch. The mission will provide morning (10:30 AM) global observations of aerosol and other related parameters. It will be followed a year later by a <span class="hlt">MODIS</span> instrument on EOS <span class="hlt">Aqua</span> for afternoon observations (1:30 PM). <span class="hlt">MODIS</span> will measure aerosol over land and ocean with its eight 500 m and 250 m channels in the solar spectrum (0-41 to 2.2 micrometers). Over the land <span class="hlt">MODIS</span> will measure the total column aerosol loading, and distinguish between submicron pollution particles and large soil particles. Standard daily products of resolution of ten kilometers and global mapped eight day and monthly products on a 1x1 degree global scale will be produced routinely and make available for no or small reproduction charge to the international community. Though the aerosol products will not be available everywhere over the land, it is expected that they will be useful for assessments of the presence, sources and transport of urban pollution, biomass burning aerosol, and desert dust. Other measurements from <span class="hlt">MODIS</span> will supplement the aerosol information, e.g., land use change, urbanization, presence and magnitude of biomass burning fires, and effect of aerosol on cloud microphysics. Other instruments on Terra, e.g. Multi-angle Imaging SpectroRadiometer (MISR) and the Clouds and the Earth's Radiant Energy System (CERES), will also measure aerosol, its properties and radiative forcing in tandem with the <span class="hlt">MODIS</span> measurements. During the <span class="hlt">Aqua</span> period, there are plans to launch in 2003 the Pathfinder Instruments for Cloud and Aerosol Spaceborne Observations (PICASSO) mission for global measurements of the aerosol vertical structure, and the PARASOL mission for aerosol characterization. <span class="hlt">Aqua-MODIS</span>, PICASSO and PARASOL will fly in formation for detailed simultaneous characterization of the aerosol three-dimensional field, which</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1815907B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1815907B"><span id="translatedtitle">Assessment of the <span class="hlt">MODIS</span>-Terra Collection 006 aerosol optical depth data over the greater Mediterranean basin and inter-comparison against <span class="hlt">MODIS</span> C005 and AERONET</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Betsikas, Marios; Hatzianastassiou, Nikos; Papadimas, Christos D.; Gkikas, Antonis; Matsoukas, Christos; Sayer, Andrew; Hsu, Christina; Vardavas, Ilias</p> <p>2016-04-01</p> <p>Aerosols are one of the key factors determining the Earth's solar radiation budget. The aerosol radiative effects are strongly dependent on aerosol optical depth (AOD) which is a good measure of atmospheric aerosol loading. Therefore, understanding better the spatial and temporal patterns of AOD at both global and regional scales is important for more accurate estimations of aerosol radiative effects. Nowadays, improved globally distributed AOD products are available largely based on satellite observations. Currently, one of the most acknowledged accurate AOD dataset is the one derived from measurements of the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument onboard the twin Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellite platforms. The <span class="hlt">MODIS</span> aerosol retrieval algorithm, which is used to produce AOD data, is continuously improved and updated, leading to releases of successive series, named as Collections. Recently, <span class="hlt">MODIS</span> Collection 6 (C006) dataset has been made available. Despite their advantages, satellite AOD products have to be assessed through comparisons against ground based AOD products, such as those from AERosol Robotic Network (AERONET). The aim of the present study is to assess the newest <span class="hlt">MODIS</span> C006 AOD product over the greater Mediterranean basin. The assessment is performed through comparisons of the <span class="hlt">MODIS</span>-Terra C006 Level-3 AOD data against corresponding data from the previous C005 <span class="hlt">MODIS</span> dataset, as well as versus AOD data from AERONET stations within the study region. The study period extends from 2001 to 2012 and our comparisons are performed on a monthly basis. Emphasis is given on differences between the <span class="hlt">MODIS</span> C006 AOD data and corresponding previous C005 data, as to their spatial and temporal, seasonal and inter-annual, patterns. The results show a better agreement of <span class="hlt">MODIS</span> C006 than C005 AOD data with AERONET, while the C006 data offer a complete spatial coverage of the study region, specifically over the northern African</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040161458&hterms=precursors&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dprecursors','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040161458&hterms=precursors&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dprecursors"><span id="translatedtitle"><span class="hlt">MODIS</span> Data in AWIPS: A Precursor of NPOESS and GOES-R Capabilities</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jedlovec, Gary; Haines, Stephanie; Suggs, Ron; Bradshaw, Tom; Burks, Jason</p> <p>2004-01-01</p> <p><span class="hlt">MODIS</span> data from NASA's Terra and <span class="hlt">Aqua</span> satellites are being sent to several NWS Forecast Offices in real time to assist in the preparation of short-term weather forecasts. The <span class="hlt">MODIS</span> imagery, in channels similar to those of the planned GOES-R instrument, is reformatted, sectorized, and ingested directly in Advanced Weather Interactive Processing System (AWIPS). A number of products derived from the imagery are available in near real-time as well. This transition activity, from research to operations, serves to prepare forecasters for the next generation satellite observing capabilities through real-time, hands on applications to their forecast problems. The presentation will provide examples of this transition activity and a preliminary assessment on the utility of several of the <span class="hlt">MODIS</span> products for improving short-term forecasts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006671','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006671"><span id="translatedtitle">Long Term Cloud Property Datasets From <span class="hlt">MODIS</span> and AVHRR Using the CERES Cloud Algorithm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; Hong, Gang; Bhatt, Rajendra</p> <p>2015-01-01</p> <p>Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to <span class="hlt">MODIS</span> data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the <span class="hlt">MODIS</span> and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A21C0142Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A21C0142Y"><span id="translatedtitle">Evaluation and Validation of Updated <span class="hlt">MODIS</span> C6 and VIIRS LAI/FPAR</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yan, K.; Park, T.; Chen, C.; Yang, B.; Yan, G.; Knyazikhin, Y.; Myneni, R. B.; CHOI, S.</p> <p>2015-12-01</p> <p>Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (0.4-0.7 μm) absorbed by vegetation (FPAR) play a key role in characterizing vegetation canopy functioning and energy absorption capacity. With radiative transfer realization, <span class="hlt">MODIS</span> onboard NASA EOS Terra and <span class="hlt">Aqua</span> satellites has provided globally continuous LAI/FPAR since 2000 and continuously updated the products with better quality. And NPP VIIRS shows the measurement capability to extend high-quality LAI/FPAR time series data records as a successor of <span class="hlt">MODIS</span>. The primary objectives of this study are 1) to evaluate and validate newly updated <span class="hlt">MODIS</span> Collection 6 (C6) LAI/FPAR product which has finer resolution (500m) and improved biome type input, and 2) to examine and adjust VIIRS LAI/FPAR algorithm for continuity with <span class="hlt">MODIS</span>'. For <span class="hlt">MODIS</span> C6 investigation, we basically measure the spatial coverage (i.e., main radiative transfer algorithm execution), continuity and consistency with Collection 5 (C5), and accuracy with field measured LAI/FPAR. And we also validate C6 LAI/FPAR via comparing other possible global LAI/FPAR products (e.g., GLASS and CYCLOPES) and capturing co-varying seasonal signatures with climatic variables (e.g., temperature and precipitation). For VIIRS evaluation and adjustment, we first quantify possible difference between C5 and <span class="hlt">MODIS</span> heritage based VIIRS LAI/FPAR. Then based on the radiative transfer theory of canopy spectral invariants, we find VIIRS- and biome-specific configurable parameters (single scattering albedo and uncertainty). These two practices for <span class="hlt">MODIS</span> C6 and VIIRS LAI/FPAR products clearly suggest that (a) <span class="hlt">MODIS</span> C6 has better coverage and accuracy than C5, (b) C6 shows consistent spatiotemporal pattern with C5, (c) VIIRS has the potential for producing <span class="hlt">MODIS</span>-like global LAI/FPAR Earth System Data Records.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B53E0620N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B53E0620N"><span id="translatedtitle">Recent Shift of Deforestation to High Elevation Areas from 2001 to 2013 in Borneo Detected by <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nagai, S.; Suzuki, R.</p> <p>2015-12-01</p> <p>The biomass of tropical forests sequestrates tons of carbon and plays an important role in the global carbon cycle regulating the climate. Also its high biodiversity ecosystems bring us many valuable resources and cultural and educational ecosystem services. However, large areas of the tropical forest are deforested and converted to oil palm or acacia plantation for the economic benefit of the local society mainly in Southeast Asia. Monitoring of the tropical forest from satellites provides us the information about the deforestation for decadal time period over extensive areas and enables us to discuss it from a scientific point of view. The purpose of this study is to reveal the interannual change and recent trend of deforestation in relation to the land elevation for decadal time period over Borneo by using data from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). We acquired the atmospherically corrected and cloud free Terra-<span class="hlt">MODIS</span> and <span class="hlt">Aqua-MODIS</span> daily data products (MOD09GA and MYD09GA; collection 5) from 2001 to 2013 for Borneo. We extracted the pixel values in the 500m surface <span class="hlt">reflectance</span> bands 1 (red) and 4 (green) products and calculated the green-red vegetation index (GRVI), (band 4 - band 1) / (band 4 + band 1), at a daily time step. GRVI shows a positive value for the land prevailed by green vegetation, while it shows a negative value for the land prevailed by no-green components such as bare land. As for the elevation data, ASTER Global Digital Elevation Model (GDEM) which has 33.3m spatial resolution was employed. The original resolution was resampled to the grid system of <span class="hlt">MODIS</span> data (i.e. 500m resolution). Pixels which had a negative GRVI ratio more than 80 % (termed as "no green pixel") in each year were regarded as the land characterized by no vegetation, and mapped the distribution for each year. Throughout the 13 years, no green pixels mainly found over the coastal low land below 20m of the elevation and the area was almost constant (around</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B53B0178S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B53B0178S"><span id="translatedtitle">Recent Shift of Deforestation to High Elevation Areas from 2001 to 2013 in Borneo Detected by <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Suzuki, R.; Nagai, S.</p> <p>2014-12-01</p> <p>The biomass of tropical forests sequestrates tons of carbon and plays an important role in the global carbon cycle regulating the climate. Also its high biodiversity ecosystems bring us many valuable resources and cultural and educational ecosystem services. However, large areas of the tropical forest are deforested and converted to oil palm or acacia plantation for the economic benefit of the local society mainly in Southeast Asia. Monitoring of the tropical forest from satellites provides us the information about the deforestation for decadal time period over extensive areas and enables us to discuss it from a scientific point of view. The purpose of this study is to reveal the interannual change and recent trend of deforestation in relation to the land elevation for decadal time period over Borneo by using data from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). We acquired the atmospherically corrected and cloud free Terra-<span class="hlt">MODIS</span> and <span class="hlt">Aqua-MODIS</span> daily data products (MOD09GA and MYD09GA; collection 5) from 2001 to 2013 for Borneo. We extracted the pixel values in the 500m surface <span class="hlt">reflectance</span> bands 1 (red) and 4 (green) products and calculated the green-red vegetation index (GRVI), (band 4 - band 1) / (band 4 + band 1), at a daily time step. GRVI shows a positive value for the land prevailed by green vegetation, while it shows a negative value for the land prevailed by no-green components such as bare land. As for the elevation data, ASTER Global Digital Elevation Model (GDEM) which has 33.3m spatial resolution was employed. The original resolution was resampled to the grid system of <span class="hlt">MODIS</span> data (i.e. 500m resolution). Pixels which had a negative GRVI ratio more than 80 % (termed as "no green pixel") in each year were regarded as the land characterized by no vegetation, and mapped the distribution for each year. Throughout the 13 years, no green pixels mainly found over the coastal low land below 20m of the elevation and the area was almost constant (around</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9840E..29L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9840E..29L"><span id="translatedtitle">Tracking the on-orbit spatial performance of <span class="hlt">MODIS</span> using ground targets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Link, Daniel; Brinkmann, Jake; Xiong, Xiaoxiong J.; Wang, Zhipeng</p> <p>2016-05-01</p> <p>Nearly-identical <span class="hlt">MODIS</span> instruments are operating onboard both the NASA EOS Terra and <span class="hlt">Aqua</span> spacecraft. Each instrument records earth-scene data using 490 detectors divided among 36 spectral bands. These bands range in center wavelength from 0.4 μm to 14.2 μm to benefit studies of the entire earth system including land, atmosphere, and ocean disciplines. Many of the resultant science data products are the result of multiple bands used in combination. Any mis-registration between the bands would adversely affect subsequent data products. The relative registration between <span class="hlt">MODIS</span> bands was measured pre-launch and continues to be monitored on-orbit via the Spectro-radiometric Calibration Assembly (SRCA), an on-board calibrator. Analysis has not only shown registration differences pre-launch, but also long-term and seasonal changes. While the ability to determine registration changes on-orbit using the SRCA is unique to <span class="hlt">MODIS</span>, the use of ground targets to determine relative registration has been used for other instruments. This paper evaluates a ground target for <span class="hlt">MODIS</span> spatial characterization using the <span class="hlt">MODIS</span> calibrated data product. Results are compared against previously reported findings using <span class="hlt">MODIS</span> data and the operational on-board characterization using the SRCA.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110023848&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3D%2528%2528%2528modis%2Bland%2529%2Bsurface%2529%2Btemperature%2529','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110023848&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3D%2528%2528%2528modis%2Bland%2529%2Bsurface%2529%2Btemperature%2529"><span id="translatedtitle">Discrepancies Between <span class="hlt">MODIS</span> and ISCCP Land Surface Temperature Products Analyzed with Microwave Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moncet, Jean-Luc; Liang, Pan; Lipton, Alan E.; Galantowicz, John F.; Prigent, Catherine</p> <p>2011-01-01</p> <p>This paper compares land surface temperature (LST) products from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the International Satellite Cloud Climatology Project (ISCCP). With both sources, the LST data are derived from infrared measurements. For ISCCP, LST is a secondary product in support of the primary cloud analyses, but the LST data have been used for several other purposes. The <span class="hlt">MODIS</span> measurements from the <span class="hlt">Aqua</span> spacecraft are taken at about 01:30 and 13:30 local time, and the ISCCP three-hourly data, based on several geostationary and polar orbiting satellites. were interpolated to the <span class="hlt">MODIS</span> measurement times. For July 2003 monthly averages over all clear-sky locations, the ISCCP-<span class="hlt">MODIS</span> differences were +5.0 K and +2.5 K for day and night, respectively, and there were areas with differences as large as 25 K. The day-night differences were as much as approximately 10 K higher for ISCCP than for <span class="hlt">MODIS</span>. The <span class="hlt">MODIS</span> measurements were more consistent with independent microwave measurements from AMSR-E, by several measures, with respect to day-night differences and day-to-day variations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....16.1255X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....16.1255X"><span id="translatedtitle">Evaluation of VIIRS, GOCI, and <span class="hlt">MODIS</span> Collection 6 AOD retrievals against ground sunphotometer observations over East Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.</p> <p>2016-02-01</p> <p>Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and <span class="hlt">Aqua</span> Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra <span class="hlt">MODIS</span> C6 3 km AOD, and 16 % of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan-South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra <span class="hlt">MODIS</span>, and 56 % of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> C6 3 km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and <span class="hlt">MODIS</span> C6 3 km products had positive biases.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080048051','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080048051"><span id="translatedtitle"><span class="hlt">MODIS</span> Atmospheric Data Handler</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Anantharaj, Valentine; Fitzpatrick, Patrick</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Atmosphere Data Handler software converts the HDF data to ASCII format, and outputs: (1) atmospheric profiles of temperature and dew point and (2) total precipitable water. Quality-control data are also considered in the export procedure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011lrsg.book..635Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011lrsg.book..635Z"><span id="translatedtitle"><span class="hlt">MODIS</span>-Derived Terrestrial Primary Production</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Maosheng; Running, Steven; Heinsch, Faith Ann; Nemani, Ramakrishna</p> <p></p> <p>Temporal and spatial changes in terrestrial biological productivity have a large impact on humankind because terrestrial ecosystems not only create environments suitable for human habitation, but also provide materials essential for survival, such as food, fiber and fuel. A recent study estimated that consumption of terrestrial net primary production (NPP; a list of all the acronyms is available in the appendix at the end of the chapter) by the human population accounts for about 14-26% of global NPP (Imhoff et al. 2004). Rapid global climate change is induced by increased atmospheric greenhouse gas concentration, especially CO2, which results from human activities such as fossil fuel combustion and deforestation. This directly impacts terrestrial NPP, which continues to change in both space and time (Melillo et al. 1993; Prentice et al. 2001; Nemani et al. 2003), and ultimately impacts the well-being of human society (Milesi et al. 2005). Additionally, substantial evidence show that the oceans and the biosphere, especially terrestrial ecosystems, currently play a major role in reducing the rate of the atmospheric CO2 increase (Prentice et al. 2001; Schimel et al. 2001). NPP is the first step needed to quantify the amount of atmospheric carbon fixed by plants and accumulated as biomass. Continuous and accurate measurements of terrestrial NPP at the global scale are possible using satellite data. Since early 2000, for the first time, the <span class="hlt">MODIS</span> sensors onboard the Terra and <span class="hlt">Aqua</span> satellites, have operationally provided scientists with near real-time global terrestrial gross primary production (GPP) and net photosynthesis (PsnNet) data. These data are provided at 1 km spatial resolution and an 8-day interval, and annual NPP covers 109,782,756 km2 of vegetated land. These GPP, PsnNet and NPP products are collectively known as MOD17 and are part of a larger suite of <span class="hlt">MODIS</span> land products (Justice et al. 2002), one of the core Earth System or Climate Data Records (ESDR or</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.4354K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.4354K"><span id="translatedtitle">Improvement of GOCI Yonsei Aerosol retrieval algorithm and validation during DRAGON campaign: Surface <span class="hlt">reflectance</span> issue according to land, clear water and turbid water</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, Jhoon; Choi, Myungje; Lee, Jaehwa</p> <p>2015-04-01</p> <p>Aerosol optical properties (AOPs) over East Asia are retrieved hourly from the first Geostationary Ocean Color Imager (GOCI). GOCI Yonsei aerosol retrieval (YAER) algorithm was developed and improved continuously. Final products of GOCI YAER are aerosol optical depth (AOD), fine-mode fraction (FMF), single scattering albedo (SSA), Angstrom exponent (AE) and aerosol type in high spatial and temporal resolution. Previous aerosol retrieval algorithm over ocean adopts surface <span class="hlt">reflectance</span> using cox and munk technique as fixed wind speed or the minimum <span class="hlt">reflectivity</span> technique for continuous characteristics between ocean and land. This study adopt cox and munk technique using real time ECMWF wind speed data over clear water and the minimum <span class="hlt">reflectivity</span> technique over turbid water. For detecting turbid water, TOA <span class="hlt">reflectance</span> of 412, 660, and 865nm was used. Over the turbid water, TOA <span class="hlt">reflectance</span> at 660nm increases more than 412 and 865nm. It also shows more sensitivity over turbid water than dust aerosol. We evaluated the accuracy of GOCI aerosol products using ground-based AERONET Level 2.0 products from total 38 East Asia sites and satellite-based <span class="hlt">MODIS-Aqua</span> aerosol C6 products. The period of assessment is 3 months from March to May, 2012. Comparison results show that a correlation coefficient between the AODs at 550 nm of AERONET and GOCI is 0.884. Comparison results over ocean between GOCI and <span class="hlt">MODIS</span> DT algorithm shows good agreement as R = 0.915.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26158600','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26158600"><span id="translatedtitle">Intercomparison of Aerosol Optical Thickness Derived from <span class="hlt">MODIS</span> and in Situ Ground Datasets over Jaipur, a Semi-arid Zone in India.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Payra, Swagata; Soni, Manish; Kumar, Anikender; Prakash, Divya; Verma, Sunita</p> <p>2015-08-01</p> <p>The first detailed seasonal validation has been carried out for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Terra and <span class="hlt">Aqua</span> satellites Level 2.0 Collection Version 5.1 AOT (τ<span class="hlt">MODIS</span>) with Aerosol Robotic Network (AERONET) Level 2.0 AOT (τAERONET) for the years 2009-2012 over semi-arid region Jaipur, northwestern India. The correlation between τ<span class="hlt">MODIS</span> versus τAERONET at 550 nm is determined with different spatial and temporal size windows. The τ<span class="hlt">MODIS</span> overestimates τAERONET within a range of +0.06 ± 0.24 during the pre-monsoon (April-June) season, while it underestimates the τAERONET with -0.04 ± 0.12 and -0.05 ± 0.18 during dry (December-March) and post-monsoon (October-November) seasons, respectively. Correlation without (with) error envelope has been found for pre-monsoon at 0.71 (0.89), post-monsoon at 0.76 (0.94), and dry season at 0.78 (0.95). τ<span class="hlt">MODIS</span> is compared to τAERONET at three more ground AERONET stations in India, i.e., Kanpur, Gual Pahari, and Pune. Furthermore, the performance of <span class="hlt">MODIS</span> Deep Blue and <span class="hlt">Aqua</span> AOT550 nm (τDB550 nm and τ<span class="hlt">Aqua</span>550 nm) with τAERONET is also evaluated for all considered sites over India along with a U.S. desert site at White Sand, Tularosa Basin, NM. The statistical results reveal that τ<span class="hlt">Aqua</span>550 nm performs better over Kanpur and Pune, whereas τDB550 nm performs better over Jaipur, Gual Pahari, and White Sand High Energy Laser Systems Test Facility (HELSTF) (U.S. site).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040171131&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bland%2Bsurface%2Btemperature','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040171131&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bland%2Bsurface%2Btemperature"><span id="translatedtitle">Near Real-time Derived Products from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Suggs, Ron; Jedlovec, Gary; Haines, Stephanie</p> <p>2004-01-01</p> <p>As part of the Short-term Prediction Research Transition (SPoRT) program at NASA/MSFC, near real-time total precipitable water and land/sea surface temperature products from <span class="hlt">MODIS</span>, on NASA's Terra and <span class="hlt">Aqua</span> satellites, are being derived from a subset of <span class="hlt">MODIS</span> channels with spectral characteristics similar to those planned for the GOES-R ABI. Under the SPoRT program these products are made available to several NWS Forecast Offices to assist in the preparation of short-term forecasts. This transition activity, from research to operations, serves to prepare forecasters for the next generation of satellite observing capabilities through real-time, hands-on applications to their forecast problems. The derived products are produced from a physical retrieval algorithm which can be applied to polar or geostationary measurements. The algorithm is a perturbation solution of the radiation transfer equation for a nonscattering atmosphere requiring first-guess temperature and moisture profiles. For this application first-guess information is obtained from the latest model forecasts. The utility of this retrieval approach is that it provides a near real-time high resolution update of a model's forecasted parameter allowing forecasters to validate and monitor the performance of the model's forecast. The poster will provide a description of the retrieval methodology and examples of the derived products. Case studies will also be presented comparing these products with those obtained from the Earth Observing System (EOS) <span class="hlt">MODIS</span> science team algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=309901','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=309901"><span id="translatedtitle">An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface <span class="hlt">reflectance</span> and <span class="hlt">MODIS</span>-based a priori anisotropy knowledge</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth’s radiative budget. While global climate studies can leverage albedo datasets from <span class="hlt">MODIS</span>, VIIRS, and other coarse-reso...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT........12I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT........12I"><span id="translatedtitle">Assessing the accuracy of the <span class="hlt">MODIS</span> LAI 1-km product in southeastern United States loblolly pine plantations: Accounting for measurement variance from ground to satellite</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Iiames, John Shepherd, Jr.</p> <p></p> <p>Leaf area index (LAI), defined here as one-half of the total leaf area per unit ground surface area (Chen, 1996), has been estimated at a global scale from spectral data processed from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor aboard two NASA EOS-AM spacecraft, Terra (launched in 1999) and <span class="hlt">Aqua</span> (launched in 2002). The MOD15A2 LAI product is a 1 km global data product composited over an 8-day period and is derived from a three-dimensional radiative transfer model driven by an atmosphere corrected surface <span class="hlt">reflectance</span> product (MOD09), a land cover product (MOD12) and ancillary information on surface characteristics. The United States Environmental Protection Agency (US EPA) initiated validation research (2002) in the evergreen needle leaf biome, as defined in the MOD12 classification, in a regional study located in the southeastern United States. The validation effort was prompted by the potential use of <span class="hlt">MODIS</span> LAI inputs into atmospheric deposition and biogenic emission models developed within the US EPA Office of Research and Development. The <span class="hlt">MODIS</span> LAI validation process involves the creation of a high spatial resolution LAI surface map, which when scaled to the MOD15A2 resolution (1 km) allowed for comparison and analysis with the 1 km <span class="hlt">MODIS</span> LAI product. Creation of this LAI surface map involved: (1) the collection of in situ LAI measurements via indirect optical measurements, (2) the correlation of land cover specific LAI estimates with spectral values retrieved from high resolution imagery (20 m--30 m), and (3) the aggregation of these 30 m cells to 1 km spatial resolution, matching the resolution of the <span class="hlt">MODIS</span> product and enabling a comparison of the two LAI values (Morisette et al. 2006). This research assessed the uncertainty associated with the creation of the high-resolution LAI reference map, specifically addressing uncertainty in the indirect in situ optical measurements of LAI and the uncertainty in the land cover classification</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.A53F0332H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.A53F0332H"><span id="translatedtitle">Intercomparison and Validation of AIRS, <span class="hlt">MODIS</span>, and ASTER Land Surface Emissivity Products over the Namib and Kalahari Deserts in Southern Africa</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hulley, G.; Hook, S.</p> <p>2008-12-01</p> <p>Land surface emissivity is a critical parameter for retrieving land surface temperatures from spaceborne Thermal Infrared (TIR) measurements. Land Surface Temperature and Emissivity (LST&E) data are key parameters in global climate change studies that involve climate modeling, ice dynamic analyses, surface- atmosphere interactions and land use, land cover change. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on NASA's <span class="hlt">Aqua</span> satellite, are strongly dependent on using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions where the variation in emissivity is large, both spatially and spectrally. LST&E products are available from spaceborne sensors such as AIRS, <span class="hlt">MODIS</span> and ASTER at varying spatial, spectral, temporal resolutions, and using different retrieval algorithms. ASTER provides LST&E data with the highest spatial resolution (90 m), compared with AIRS (50 km) and <span class="hlt">MODIS</span> (1 and 5 km). AIRS has the highest spectral sampling and both AIRS and <span class="hlt">MODIS</span> acquire data at much higher temporal frequencies (every 2-3 days) compared with ASTER (every 16 days). In this paper we present validation and intercomparisons of AIRS, <span class="hlt">MODIS</span> and ASTER emissivity products over the Namib and Kalahari deserts in Southern Africa. The Namib, Africa's second largest desert, and the Kalahari cover areas of 80,900 and 900, 000 km² respectively and consist of pure quartz, giving the sand a deep red color. The dunes provide excellent areas for validation as they have little or no vegetation, are spatially homogeneous with known composition, and have large spectral variations in TIR emissivity. <span class="hlt">MODIS</span> and ASTER data will be upsampled to the AIRS spatial resolution, and then compared to the emissivities of in-situ sand samples collected at designated areas at Sossusvlei in the Namib dunes and Kgalagadi Transfrontier Park in the Kalahari. The</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010295','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010295"><span id="translatedtitle">Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Wind, Galina; Meyer, Kerry; Amarasinghe, Nandana; Arnold, G. Thomas; Zhang, Zhibo; King, Michael D.</p> <p>2013-01-01</p> <p>The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of <span class="hlt">MODIS</span> on the NASA EOS Terra and <span class="hlt">Aqua</span> platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract <span class="hlt">reflected</span> solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=19910052093&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectrometer%2Bresolution','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=19910052093&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectrometer%2Bresolution"><span id="translatedtitle">The Moderate Resolution Imaging Spectrometer-tilt (<span class="hlt">MODIS</span>-T)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Magner, Thomas J.; Huegel, Frederick G.</p> <p>1990-01-01</p> <p>There will be several state-of-the-art spectrometers in operation on the NASA Polar Oribting Platform (NPOP-1) as part of the Earth Observing System. The Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) will consist of two imaging spectroradiometric instruments, one nadir-viewing (<span class="hlt">MODIS</span>-N) and the other tiltable (<span class="hlt">MODIS</span>-T) for ocean observation and land bidirectional <span class="hlt">reflectance</span> studies. The <span class="hlt">MODIS</span>-T instrument is required to cover the wavelength range of 400 to 880 nm in approximately 15 steps, have less than 2.3 percent instrument-induced polarization, be calibrated to an absolute radiometric accuracy of at least 5 percent over the full dynamic range of the instrument, have a 1.1 kilometer square instantaneous field of view at nadir, and be capable of + or - 50-deg along-track tilt.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70023443','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70023443"><span id="translatedtitle"><span class="hlt">MODIS</span> land data at the EROS data center DAAC</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jenkerson, C.B.; Reed, B.C.</p> <p>2001-01-01</p> <p>The US Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, SD, USA, is the primary national archive for land processes data and one of the National Aeronautics and Space Administration's (NASA) Distributed Active Archive Centers (DAAC) for the Earth Observing System (EOS). One of EDC's functions as a DAAC is the archival and distribution of Moderate Resolution Spectroradiometer (<span class="hlt">MODIS</span>) Land Data collected from the Earth Observing System (EOS) satellite Terra. More than 500,000 publicly available <span class="hlt">MODIS</span> land data granules totaling 25 Terabytes (Tb) are currently stored in the EDC archive. This collection is managed, archived, and distributed by EOS Data and Information System (EOSDIS) Core System (ECS) at EDC. EDC User Services support the use of <span class="hlt">MODIS</span> Land data, which include land surface <span class="hlt">reflectance</span>/albedo, temperature/emissivity, vegetation characteristics, and land cover, by responding to user inquiries, constructing user information sites on the EDC web page, and presenting <span class="hlt">MODIS</span> materials worldwide.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040070915','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040070915"><span id="translatedtitle">Deriving Albedo from Coupled MERIS and <span class="hlt">MODIS</span> Surface Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gao, Feng; Schaaf, Crystal; Jin, Yu-Fang; Lucht, Wolfgang; Strahler, Alan</p> <p>2004-01-01</p> <p>MERIS Level 2 surface <span class="hlt">reflectance</span> products are now available to the scientific community. This paper demonstrates the production of MERIS-derived surface albedo and Nadir Bidirectional <span class="hlt">Reflectance</span> Distribution Function (BRDF) adjusted <span class="hlt">reflectances</span> by coupling the MERIS data with <span class="hlt">MODIS</span> BRDF products. Initial efforts rely on the specification of surface anisotropy as provided by the global <span class="hlt">MODIS</span> BRDF product for a first guess of the shape of the BRDF and then make use all of the coincidently available, partially atmospherically corrected, cloud cleared, MERIS observations to generate MERIS-derived BRDF and surface albedo quantities for each location. Comparisons between <span class="hlt">MODIS</span> (aerosol-corrected) and MERIS (not-yet aerosol-corrected) surface values from April and May 2003 are also presented for case studies in Spain and California as well as preliminary comparisons with field data from the Devil's Rock Surfrad/BSRN site.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050060913','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050060913"><span id="translatedtitle">Estimating Coastal Turbidity using <span class="hlt">MODIS</span> 250 m Band Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Davies, James E.; Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Walker, Nan D.</p> <p>2004-01-01</p> <p>Terra <span class="hlt">MODIS</span> 250 m observations are being applied to a Suspended Sediment Concentration (SSC) algorithm that is under development for coastal case 2 waters where <span class="hlt">reflectance</span> is dominated by sediment entrained in major fluvial outflows. An atmospheric correction based on <span class="hlt">MODIS</span> observations in the 500 m resolution 1.6 and 2.1 micron bands is used to isolate the remote sensing <span class="hlt">reflectance</span> in the <span class="hlt">MODIS</span> 25Om resolution 650 and 865 nanometer bands. SSC estimates from remote sensing <span class="hlt">reflectance</span> are based on accepted inherent optical properties of sediment types known to be prevalent in the U.S. Gulf of Mexico coastal zone. We present our findings for the Atchafalaya Bay region of the Louisiana Coast, in the form of processed imagery over the annual cycle. We also apply our algorithm to selected sites worldwide with a goal of extending the utility of our approach to the global direct broadcast community.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C51A0638R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C51A0638R"><span id="translatedtitle">Cryosphere Broadband Surface Albedo Derivation with <span class="hlt">MODIS</span>-to-CERES Conversion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Radkevich, A.; Rose, F. G.; Charlock, T. P.; Kato, S.</p> <p>2011-12-01</p> <p>Clouds and the Earth's Radiant Energy System (CERES) instruments on NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellites measure broadband shortwave and longwave radiation <span class="hlt">reflected</span> and emitted at the Top of the atmosphere (TOA). CERES synthesizes broadband observations with other EOS data streams. The CERES Surface and Atmospheric Radiation Budget (SARB) group matches observations with a radiative transfer code to determine fluxes at several levels. The presentation describes how the next edition of CERES will improve the retrieval of cryosphere surface albedo. Surface albedo is one of the input parameters of numerous models such cloud-resolving model (CRM) simulation, general circulation models (GCMs) and transient climate change simulations. It was recently showed by Park and Wu (2010) that CRM simulation well represents the SW radiative budget during winter because the radiation calculation for the snow-covered period is improved by using prescribed evolving surface albedo. Qu and Hall (2007) analyzed snow albedo feedback (SAF) in several transient climate change models. They stated that high quality observations of albedo of snow-covered surfaces would be extremely useful in reducing SAF spread in the next generation of models. CERES measures radiance and infers flux by applying scene-dependent, empirically based angular distribution models (ADMs). The ADMs are obtained from the complex CERES rotating azimuth plane scan mode to establish BRDF on the scale of 30 km broadband footprints. While CERES has much coarser spatial resolution than <span class="hlt">MODIS</span>, the CERES measurement-based BRDF provides a keen advantage in accuracy over complex surfaces. CERES SARB retrievals of surface albedo have to date been based on only those 30 km footprints that are completely clear; there are too few (~5%) such footprints over sea ice. The upcoming edition of CERES will include <span class="hlt">MODIS</span> radiances in 7 SW bands (currently 4), which are point spread function weighted to both a whole</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AMTD....8.2409C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AMTD....8.2409C&link_type=ABSTRACT"><span id="translatedtitle">A cautionary use of DCC as a solar calibration target: explaining the regional difference in DCC <span class="hlt">reflectivity</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Choi, M.-J.; Sohn, B. J.</p> <p>2015-03-01</p> <p>This study attempted to explain why deep convective clouds (DCCs) over the western Pacific are generally darker than those found over tropical African and South American land regions. For defining 1 km pixel DCCs in this study, 205 K of <span class="hlt">Aqua-MODIS</span> brightness temperature at 11 μm (TB11) was used as a criterion. Corresponding <span class="hlt">MODIS</span>-measured <span class="hlt">reflectivities</span> at 0.645 μm were examined, and an analysis of collocated Cloud Profile Radar (CPR) onboard CloudSat and Cloud Aerosol Lidar Infrared Pathfinder Satellite Observation (CALIPSO) measurements and derived cloud products was conducted. From an analysis of the four January months of 2007-2010, a distinct difference in ice water path (IWP) between the western Pacific and the two tropical land regions was demonstrated. Small but meaningful differences in the effective radius were also found. The results led to a conjecture that smaller IWP over the western Pacific than over the tropical land regions is the main cause of smaller <span class="hlt">reflectivity</span> there. This finding suggests that regionally different <span class="hlt">reflectivity</span> of DCCs over the tropics up to 5% on average are to be counted when those DCCs are used for the solar channel calibration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN14A..01J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN14A..01J"><span id="translatedtitle">USAID Expands e<span class="hlt">MODIS</span> Coverage for Famine Early Warning</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jenkerson, C.; Meyer, D. J.; Evenson, K.; Merritt, M.</p> <p>2011-12-01</p> <p>Food security in countries at risk is monitored by U.S. Agency for International Development (USAID) through its Famine Early Warning Systems Network (FEWS NET) using many methods including Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data processed by U.S. Geological Survey (USGS) into e<span class="hlt">MODIS</span> Normalized Difference Vegetation Index (NDVI) products. Near-real time production is used comparatively with trends derived from the e<span class="hlt">MODIS</span> archive to operationally monitor vegetation anomalies indicating threatened cropland and rangeland conditions. e<span class="hlt">MODIS</span> production over Central America and the Caribbean (CAMCAR) began in 2009, and processes 10-day NDVI composites every 5 days from surface <span class="hlt">reflectance</span> inputs produced using predicted spacecraft and climatology information at Land and Atmosphere Near real time Capability for Earth Observing Systems (EOS) (LANCE). These expedited e<span class="hlt">MODIS</span> composites are backed by a parallel archive of precision-based NDVI calculated from surface <span class="hlt">reflectance</span> data ordered through Level 1 and Atmosphere Archive and Distribution System (LAADS). Success in the CAMCAR region led to the recent expansion of e<span class="hlt">MODIS</span> production to include Africa in 2010, and Central Asia in 2011. Near-real time 250-meter products are available for each region on the last day of an acquisition interval (generally before midnight) from an anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/e<span class="hlt">MODIS</span>). The FTP site concurrently hosts the regional historical collections (2000 to present) which are also searchable using the USGS Earth Explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer). As e<span class="hlt">MODIS</span> coverage continues to grow, these geographically gridded, georeferenced tagged image file format (GeoTIFF) NDVI composites increase their utility as effective tools for operational monitoring of near-real time vegetation data against historical trends.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.B41A0171L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.B41A0171L"><span id="translatedtitle">Mapping Africa Biomass with <span class="hlt">MODIS</span> Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Laporte, N.; Baccini, A.; Houghton, R.</p> <p>2006-12-01</p> <p>Central Africa contains the second largest block of tropical forest remaining in the world, and is one of the largest carbon reservoirs on Earth. The carbon dynamics of the region differ substantially from other tropical forests because most deforestation and land use is associated with selective logging and small-scale landholders practicing traditional "slash-and-burn" agriculture. Despite estimates of 1-2 PgC/yr released to the atmosphere from tropical deforestation, the amount released from Central Africa is highly uncertain relative to the amounts released from other tropical forest areas. The uncertainty in carbon fluxes results from inadequate estimates of both rates of deforestation and standing stocks of carbon (forest biomass). Here we present new results mapping above-ground forest biomass for tropical Africa using machine learning techniques to integrate <span class="hlt">MODIS</span> 1km spectral <span class="hlt">reflectance</span> with forest inventory measurements to calibrate an empirical relationship. The derived forest biomass at each <span class="hlt">MODIS</span> pixel shows the spatial distribution of forest biomass over the entire tropical forest region. The model has been tested in Uganda, Mali and part of Republic of Congo where field data were available. The regression tree model based on <span class="hlt">MODIS</span> NBAR surface <span class="hlt">reflectance</span> for Uganda, Mali and Republic of Congo explains 94 percent of the variance in above-ground biomass with a root mean square error (RMSE) of 27 Tons/ha. The approach shows promise for use of optical remote sensing data in mapping the spatial distribution of forest biomass across the region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070018757&hterms=collection+water&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dcollection%2Bwater','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070018757&hterms=collection+water&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dcollection%2Bwater"><span id="translatedtitle">Spatial and Temporal Distribution of Cloud Properties Observed by <span class="hlt">MODIS</span>: Preliminary Level-3 Results from the Collection 5 Reprocessing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Hubanks, Paul; Pincus, Robert</p> <p>2006-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and <span class="hlt">Aqua</span> spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for <span class="hlt">Aqua</span>. A comprehensive set of operational algorithms for the retrieval of cloud physical and optical properties (optical thickness, effective particle radius, water path, thermodynamic phase) have recently been updated and are being used in the new "Collection 5" processing stream being produced by the <span class="hlt">MODIS</span> Adaptive Processing System (MODAPS) at NASA GSFC. All Terra and <span class="hlt">Aqua</span> data are undergoing Collection 5 reprocessing with an expected completion date by the end of 2006. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. The cloud products have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In this talk, we will summarize the available Level-3 cloud properties and their associated statistical data sets, and show preliminary Terra and <span class="hlt">Aqua</span> results from the available Collection 5 reprocessing effort. Anticipated results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C43D0433M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C43D0433M"><span id="translatedtitle"><span class="hlt">MODIS</span> Data and Services at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McAllister, M.; Booker, L.; Fowler, D. K.; Haran, T. M.</p> <p>2014-12-01</p> <p>For close to 15 years, the National Snow and Ice Data Center (NSIDC) NASA Distributed Active Archive Center (NDAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra satellites. The archive contains a wide selection of snow and sea ice data products relevant to cryospheric science. NSIDC offers a variety of methods for obtaining these data. Users can ftp data directly from an online archive which allows for a very quick download. The Reverb Search & Order Tool contains a complete set of metadata for all products which can be searched for and ordered. Reverb allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new <span class="hlt">MODIS</span> data automatically ftp'd or staged on a local server as it is archived at NSIDC. Since <span class="hlt">MODIS</span> products are in HDF-EOS format, a number of tools have been developed to assist with browsing, editing, reprojection, resampling, and format conversion. One such service, Data Access, can be accessed through Reverb and performs subsetting, reformatting, and reprojection. This service can also be accessed via an Application Programming Interface (API) from a user-written client. Other tools include the <span class="hlt">MODIS</span> Swath-to-Grid Toolbox (MS2GT) and the <span class="hlt">MODIS</span> Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute <span class="hlt">MODIS</span> scenes. NSIDC also created the MIST to provide subsets of certain Version 5 <span class="hlt">MODIS</span> products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations. Tools from other sources include HDFView from the National Center for Supercomputing Applications (NCSA), and the <span class="hlt">MODIS</span> Reprojection Tool (MRT) and MRT Swath developed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AIPC.1553...69M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AIPC.1553...69M&link_type=ABSTRACT"><span id="translatedtitle">Towards identification of relevant variables in the observed aerosol optical depth bias between <span class="hlt">MODIS</span> and AERONET observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malakar, N. K.; Lary, D. J.; Gencaga, D.; Albayrak, A.; Wei, J.</p> <p>2013-08-01</p> <p>Measurements made by satellite remote sensing, Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), and globally distributed Aerosol Robotic Network (AERONET) are compared. Comparison of the two datasets measurements for aerosol optical depth values show that there are biases between the two data products. In this paper, we present a general framework towards identifying relevant set of variables responsible for the observed bias. We present a general framework to identify the possible factors influencing the bias, which might be associated with the measurement conditions such as the solar and sensor zenith angles, the solar and sensor azimuth, scattering angles, and surface <span class="hlt">reflectivity</span> at the various measured wavelengths, etc. Specifically, we performed analysis for remote sensing <span class="hlt">Aqua</span>-Land data set, and used machine learning technique, neural network in this case, to perform multivariate regression between the ground-truth and the training data sets. Finally, we used mutual information between the observed and the predicted values as the measure of similarity to identify the most relevant set of variables. The search is brute force method as we have to consider all possible combinations. The computations involves a huge number crunching exercise, and we implemented it by writing a job-parallel program.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AMTD....6..159L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AMTD....6..159L"><span id="translatedtitle">The Collection 6 <span class="hlt">MODIS</span> aerosol products over land and ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Mattoo, S.; Munchak, L. A.; Remer, L. A.; Sayer, A. M.; Hsu, N. C.</p> <p>2013-01-01</p> <p>The twin Moderate Imaging resolution Spectroradiometer (<span class="hlt">MODIS</span>) sensors have been flying on Terra since 2000 and <span class="hlt">Aqua</span> since 2002, creating an incredible dataset of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from <span class="hlt">MODIS</span>-observed spectral <span class="hlt">reflectance</span>. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there is significant impact on the products and their interpretation. The C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties (1) over ocean (dark in visible and near-IR wavelengths), (2) over vegetated/dark-soiled land (dark in the visible) and (3) over desert/arid land (bright in the visible). Here, we focus on the changes to both "dark target" algorithms (#1 and #2; DT-ocean and DT-land). Affecting both DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, and relaxed the solar zenith angle limit (up to ≤ 84°) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. All together, the changes to the DT algorithms result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.01) over land, along with some changes in spatial coverage. Preliminary validation shows that compared to surface-based sunphotometer data, the C6 DT-products should compare at least as well as those from C5. However, at the same time as we</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007890','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007890"><span id="translatedtitle">Estimation of Surface Air Temperature from <span class="hlt">MODIS</span> 1km Resolution Land Surface Temperature Over Northern China</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina</p> <p>2010-01-01</p> <p>Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from <span class="hlt">MODIS</span> over the dry and semiarid regions of northern China. Studies were conducted for both <span class="hlt">MODIS</span>-Terra and <span class="hlt">MODIS-Aqua</span> by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and <span class="hlt">MODIS</span> land surface temperature, surface maximum and minimum air temperatures are estimated from 1km <span class="hlt">MODIS</span> land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060047785','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060047785"><span id="translatedtitle">Aerosol Lidar and <span class="hlt">MODIS</span> Satellite Comparisons for Future Aerosol Loading Forecast</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>DeYoung, Russell; Szykman, James; Severance, Kurt; Chu, D. Allen; Rosen, Rebecca; Al-Saadi, Jassim</p> <p>2006-01-01</p> <p>Knowledge of the concentration and distribution of atmospheric aerosols using both airborne lidar and satellite instruments is a field of active research. An aircraft based aerosol lidar has been used to study the distribution of atmospheric aerosols in the California Central Valley and eastern US coast. Concurrently, satellite aerosol retrievals, from the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra and <span class="hlt">Aqua</span> satellites, were take over the Central Valley. The <span class="hlt">MODIS</span> Level 2 aerosol data product provides retrieved ambient aerosol optical properties (e.g., optical depth (AOD) and size distribution) globally over ocean and land at a spatial resolution of 10 km. The Central Valley topography was overlaid with <span class="hlt">MODIS</span> AOD (5x5 sq km resolution) and the aerosol scattering vertical profiles from a lidar flight. Backward air parcel trajectories for the lidar data show that air from the Pacific and northern part of the Central Valley converge confining the aerosols to the lower valley region and below the mixed layer. Below an altitude of 1 km, the lidar aerosol and <span class="hlt">MODIS</span> AOD exhibit good agreement. Both data sets indicate a high presence of aerosols near Bakersfield and the Tehachapi Mountains. These and other results to be presented indicate that the majority of the aerosols are below the mixed layer such that the <span class="hlt">MODIS</span> AOD should correspond well with surface measurements. Lidar measurements will help interpret satellite AOD retrievals so that one day they can be used on a routine basis for prediction of boundary layer aerosol pollution events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007302','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007302"><span id="translatedtitle">Multilayer Cloud Detection with the <span class="hlt">MODIS</span> Near-Infrared Water Vapor Absorption Band</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.</p> <p>2009-01-01</p> <p>Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) onboard the NASA Earth Observing System EOS Terra and <span class="hlt">Aqua</span> spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the <span class="hlt">MODIS</span> 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the <span class="hlt">MODIS</span> multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by <span class="hlt">MODIS</span> are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the <span class="hlt">MODIS</span> multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013GeoRL..40..772B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013GeoRL..40..772B"><span id="translatedtitle">Properties of linear contrails in the Northern Hemisphere derived from 2006 <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bedka, Sarah T.; Minnis, Patrick; Duda, David P.; Chee, Thad L.; Palikonda, Rabindra</p> <p>2013-02-01</p> <p>Understanding the role of contrails in the Earth's radiation budget requires an accurate characterization of their macrophysical and microphysical properties, such as cloud top temperature, optical depth, and effective particle size. These properties are derived from 2006 MODerate-resolution Imaging Spectroradiometer data over the Northern Hemisphere using a bi-spectral, infrared-only retrieval technique. Contrail temperature is estimated using a quadratic relationship of flight track pressure with latitude. The results reveal distinct seasonal trends in contrail microphysical properties, with slightly greater mean optical depths and slightly smaller particle sizes during summer. The average contrail optical depth and particle effective diameter are 0.216 and 35.7 µm, respectively. Although fewer contrails occurred at night, there are no appreciable diurnal differences in their retrieved properties. These results should help to fill the gap in our knowledge of contrail properties and will be valuable for model validation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005182&hterms=terra&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dterra','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005182&hterms=terra&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dterra"><span id="translatedtitle">Status of Terra <span class="hlt">MODIS</span> Operation, Calibration, and Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Wenny, B.; Wu, A.; Angal, A.; Geng, X.; Chen, H.; Dodd, J.; Link, D.; Madhavan, S.; Chen, N.; Li, Y.; Iacangelo, S.; Barnes, W.; Salomonson, V.</p> <p>2014-01-01</p> <p>Since launch in December 1999, Terra <span class="hlt">MODIS</span> has successfully operated for nearly 15 years, making continuous observations. Data products derived from <span class="hlt">MODIS</span> observations have significantly contributed to a wide range of studies of key geophysical parameters of the earth's eco-system of land, ocean, and atmosphere, and their changes over time. The quality of <span class="hlt">MODIS</span> data products relies on the dedicated effort to monitor and sustain instrument health and operation, to calibrate and update sensor parameters and properties, and to improve calibration algorithms. <span class="hlt">MODIS</span> observations are made in 36 spectral bands, covering wavelengths from visible to long-wave infrared. The <span class="hlt">reflective</span> solar bands (1-19 and 26) are primarily calibrated by a solar diffuser (SD) panel and regularly scheduled lunar observations. The thermal emissive bands (20-25 and 27- 36) calibration is referenced to an on-board blackbody (BB) source. On-orbit changes in the sensor spectral and spatial characteristics are monitored by a spectroradiometric calibration assembly (SRCA). This paper provides an overview of Terra <span class="hlt">MODIS</span> on-orbit operation and calibration activities and implementation strategies. It presents and summarizes sensor on-orbit performance using nearly 15 years of data from its telemetry, on-board calibrators, and lunar observations. Also discussed in this paper are changes in sensor characteristics, corrections applied to maintain <span class="hlt">MODIS</span> level 1B (L1B) data quality, and efforts for future improvements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015808','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015808"><span id="translatedtitle">Application of <span class="hlt">MODIS</span> Products to Infer Possible Relationships Between Basin Land Cover and Coastal Waters Turbidity Using the Magdalena River, Colombia, as a Case Study</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Madrinan, Max Jacobo Moreno; Cordova, Africa Flores; Olivares, Francisco Delgado; Irwin, Dan</p> <p>2012-01-01</p> <p>Basin development and consequent change in basin land cover have been often associated with an increased turbidity in coastal waters because of sediment yield and nutrients loading. The later leads to phytoplankton abundance further exacerbating water turbidity. This subsequently affects biological and physical processes in coastal estuaries by interfering with sun light penetration to coral reefs and sea grass, and even affecting public health. Therefore, consistent estimation of land cover changes and turbidity trend lines is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Ground solely methods to estimate land cover change would be unpractical and traditional methods of monitoring in situ water turbidity can be very expensive and time consuming. Accurate monitoring on the status and trends of basin land cover as well as the water quality of the receiving water bodies are required for analysis of relationships between the two variables. Use of remote sensing (RS) technology provides a great benefit for both fields of study, facilitating monitoring of changes in a timely and cost effective manner and covering wide areas with long term measurements. In this study, the Magdalena River basin and fixed geographical locations in the estuarine waters of its delta are used as a case to study the temporal trend lines of both, land cover change and the <span class="hlt">reflectance</span> of the water turbidity using satellite technology. Land cover data from a combined product between sensors Terra and <span class="hlt">Aqua</span> (MCD12Q1) from <span class="hlt">MODIS</span> will be adapted to the conditions in the Magdalena basin to estimate changes in land cover since year 2000 to 2009. Surface <span class="hlt">reflectance</span> data from a <span class="hlt">MODIS</span>, Terra (MOD09GQ), band 1, will be used in lieu of in situ water turbidity for the time period between 2000 and present. Results will be compared with available existing data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940028783','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940028783"><span id="translatedtitle"><span class="hlt">MODIS</span>. Volume 2: <span class="hlt">MODIS</span> level 1 geolocation, characterization and calibration algorithm theoretical basis document, version 1</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barker, John L.; Harnden, Joann M. K.; Montgomery, Harry; Anuta, Paul; Kvaran, Geir; Knight, ED; Bryant, Tom; Mckay, AL; Smid, Jon; Knowles, Dan, Jr.</p> <p>1994-01-01</p> <p>The EOS Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) is being developed by NASA for flight on the Earth Observing System (EOS) series of satellites, the first of which (EOS-AM-1) is scheduled for launch in 1998. This document describes the algorithms and their theoretical basis for the <span class="hlt">MODIS</span> Level 1B characterization, calibration, and geolocation algorithms which must produce radiometrically, spectrally, and spatially calibrated data with sufficient accuracy so that Global change research programs can detect minute changes in biogeophysical parameters. The document first describes the geolocation algorithm which determines geodetic latitude, longitude, and elevation of each <span class="hlt">MODIS</span> pixel and the determination of geometric parameters for each observation (satellite zenith angle, satellite azimuth, range to the satellite, solar zenith angle, and solar azimuth). Next, the utilization of the <span class="hlt">MODIS</span> onboard calibration sources, which consist of the Spectroradiometric Calibration Assembly (SRCA), Solar Diffuser (SD), Solar Diffuser Stability Monitor (SDSM), and the Blackbody (BB), is treated. Characterization of these sources and integration of measurements into the calibration process is described. Finally, the use of external sources, including the Moon, instrumented sites on the Earth (called vicarious calibration), and unsupervised normalization sites having invariant <span class="hlt">reflectance</span> and emissive properties is treated. Finally, algorithms for generating utility masks needed for scene-based calibration are discussed. Eight appendices are provided, covering instrument design and additional algorithm details.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20010090333&hterms=Science+DirecT&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DScience%2BDirecT','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20010090333&hterms=Science+DirecT&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DScience%2BDirecT"><span id="translatedtitle">Level 1 Processing of <span class="hlt">MODIS</span> Direct Broadcast Data at the GSFC DAAC</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lynnes, Christopher; Kempler, Steven J. (Technical Monitor)</p> <p>2001-01-01</p> <p>The GSFC DAAC is working to test and package the <span class="hlt">MODIS</span> Level 1 Processing software for <span class="hlt">Aqua</span> Direct Broadcast data. This entails the same code base, but different lookup tables for <span class="hlt">Aqua</span> and Terra. However, the most significant change is the use of ancillary attitude and ephemeris files instead of orbit/attitude information within the science data stream (as with Terra). In addition, we are working on Linux: ports of the algorithms, which could eventually enable processing on PC clusters. Finally, the GSFC DAAC is also working with the GSFC Direct Readout laboratory to ingest Level 0 data from the GSFC DB antenna into the main DAAC, enabling level 1 production in near real time in support of applications users, such as the Synergy project. The mechanism developed for this could conceivably be extended to other participating stations.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060046366','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060046366"><span id="translatedtitle">Multilayered Clouds Identification and Retrieval for CERES Using <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung</p> <p>2006-01-01</p> <p>Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on <span class="hlt">Aqua</span>, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to <span class="hlt">MODIS</span> and AMSR-E data taken from the <span class="hlt">Aqua</span> satellite over non-polar ocean surfaces.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMIN21A1682M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMIN21A1682M"><span id="translatedtitle">Quality Assessment of Collection 6 <span class="hlt">MODIS</span> Atmospheric Science Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.</p> <p>2015-12-01</p> <p>Since the launch of the NASA Terra and <span class="hlt">Aqua</span> satellites in December 1999 and May 2002, respectively, atmosphere and land data acquired by the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) sensor on-board these satellites have been reprocessed five times at the MODAPS (<span class="hlt">MODIS</span> Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA <span class="hlt">MODIS</span> science team investigators. MODAPS completed Collection 6 reprocessing of <span class="hlt">MODIS</span> Atmosphere science data products in April 2015 and is currently generating the Collection 6 products using the latest version of the science algorithms. This reprocessing has generated one of the longest time series of consistent data records for understanding cloud, aerosol, and other constituents in the earth's atmosphere. It is important to carefully evaluate and assess the quality of this data and remove any artifacts to maintain a useful climate data record. Quality Assessment (QA) is an integral part of the processing chain at MODAPS. This presentation will describe the QA approaches and tools adopted by the <span class="hlt">MODIS</span> Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of <span class="hlt">MODIS</span> operational Atmospheric products produced at MODAPS. Some of the tools include global high resolution images, time series analysis and statistical QA metrics. The new high resolution global browse images with pan and zoom have provided the ability to perform QA of products in real time through synoptic QA on the web. This global browse generation has been useful in identifying production error, data loss, and data quality issues from calibration error, geolocation error and algorithm performance. A time series analysis for various science datasets in the Level-3 monthly product was recently developed for assessing any long term drifts in the data arising from instrument errors or other artifacts. This presentation will describe and discuss some test cases from the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMIN31A1258J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMIN31A1258J"><span id="translatedtitle">e<span class="hlt">MODIS</span> Expedited: Overview of a Near Real Time <span class="hlt">MODIS</span> Production System for Operational Vegetation Monitoring</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jenkerson, C.; Meyer, D. J.; Werpy, J.; Evenson, K.; Merritt, M.</p> <p>2010-12-01</p> <p>The expedited <span class="hlt">MODIS</span>, or e<span class="hlt">MODIS</span> production system derives near-real time Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) surface <span class="hlt">reflectance</span> provided by the Land and Atmosphere Near-real time Capability for EOS (LANCE). There are currently three regions covered by this U.S. Geological Survey (USGS) capability, including the continental U.S., Africa, and the Central America/Caribbean regions. Each of the e<span class="hlt">MODIS</span> production streams is configured to output its data in map projections, compositing intervals, spatial resolutions, and file formats specific to its region and user community. The challenges of processing 1,000-meter, 500-m, and especially 250-m products by midnight on the last day of a product interval have been met with increasingly effective software and system architecture. An anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/e<span class="hlt">MODIS</span>) allows users direct access to e<span class="hlt">MODIS</span> NDVI products for operational (near-real time) monitoring of vegetation conditions like drought, crop failure, insect infestation, and other threats, thus supporting subsequent early warning of famine and the targeting of vulnerable populations for insecure food situations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CSR...112...14C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CSR...112...14C"><span id="translatedtitle">Estimation of water turbidity and analysis of its spatio-temporal variability in the Danube River plume (Black Sea) using <span class="hlt">MODIS</span> satellite data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Constantin, Sorin; Doxaran, David; Constantinescu, Ștefan</p> <p>2016-01-01</p> <p>Ocean colour remote sensing information brings important insights for monitoring coastal areas. These regions are home to important natural ecosystems and changes that occur here can have important impacts not only on the local environment, but also on connected wetlands or offshore areas. The present study proposes a new regional methodology for water turbidity retrieval using the <span class="hlt">MODIS</span> red band at 250 m spatial resolution in the Danube Delta coastal area. For this purpose, multiple in-situ turbidity observations were used in order to determine a valid relationship between data collected with turbidity meters and remote sensing <span class="hlt">reflectance</span> obtained from satellite data. A special attention is given to the atmospheric correction of satellite data, since complex optical waters require adapted methodologies for accurate remote sensing <span class="hlt">reflectance</span> computation. Based on products derived using the proposed algorithm, the dynamics of turbidity is evaluated for multiple time periods: from local Terra to <span class="hlt">Aqua</span> overpasses (couple of hours), daily and monthly. Results show a clear strong connection between the Danube discharge and water turbidity in the coastal area. However other environmental parameters (e.g., wind stress) also play an important role and contribute to the magnitude of the river plume extension.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.B22C..08D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.B22C..08D"><span id="translatedtitle">The <span class="hlt">MODIS</span> Rapid Response Project: Near-Real-Time Processing for Fire Monitoring and Other Applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Descloitres, J.; Justice, C.; Sohlberg, R.; Giglio, L.; Schmaltz, J.; Seaton, J.; Davies, D.; Anyamba, A.; Hansen, M.; Carroll, M.; Sullivan, M.</p> <p>2003-12-01</p> <p>The Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument on board the Terra and <span class="hlt">Aqua</span> satellites offers an unprecedented combination of daily spatial coverage, spatial resolution, and spectral characteristics. These capabilities make <span class="hlt">MODIS</span> ideal to observe a variety of rapid events: active fires, floods, smoke transport, dust storms, severe storms, iceberg calving, and volcanic eruptions. The <span class="hlt">MODIS</span> Rapid Response System (http://rapidfire.sci.gsfc.nasa.gov) was developed at NASA's Goddard Space Flight Center to provide a rapid response to those events, with initial emphasis on active fire detection and 250m-resolution imagery. <span class="hlt">MODIS</span> data for most of the Earth's land surface is processed just a few hours after data acquisition. A collaboration between NASA, the University of Maryland and the U.S.D.A. Forest Service has been developed to provide fire information derived from <span class="hlt">MODIS</span> to federal fire managers. Active fire locations in the conterminous United States are produced by the <span class="hlt">MODIS</span> Rapid Response System and communicated to the Forest Service within a few minutes of production. The <span class="hlt">MODIS</span> Rapid Response processing was also adapted to Direct Broadcast to reduce the product turn-around to just minutes after data acquisition regionally. <span class="hlt">MODIS</span> active fire locations are used by the Forest Service to generate regional fire maps over the United States, updated twice daily and provided to the fire managers to help them allocate firefighting resources. Active fire locations are also distributed in near-real-time to the Global Observation of Forest Cover (G.O.F.C.) user community through a web interface integrating <span class="hlt">MODIS</span> active fire locations and Geographic Information System (G.I.S.) datasets. The suite of <span class="hlt">MODIS</span> rapid fire products is currently being complemented with a Smoke Index product and a Burned Area product that will represent two new key tools available to the fire community. Finally a new collaboration with the U.S.D.A. Foreign Agricultural Service was</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMOS34A..01G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMOS34A..01G"><span id="translatedtitle"><span class="hlt">AQUA</span> AMSR-E Sea Surface Temperature</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gentemann, C. L.</p> <p>2011-12-01</p> <p>NASA's <span class="hlt">AQUA</span> satellite carries the JAXA's Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The <span class="hlt">AQUA</span> satellite was launched in May 2002 into a polar, sun-synchronous orbit at an altitude of 705 km, with a LECT of 1:30 AM/PM. AMSR-E has 12 channels corresponding to 6 frequencies; all except 23.8 GHz measure both vertical and horizontal polarizations. Geophysical retrievals of SST, wind speed, water vapor, cloud liquid water, and rain rates are calculated using a multi-stage linear regression algorithm derived through comprehensive radiative transfer model simulations. SST retrievals are prevented by rain, sun glint, near land emissions, and radio frequency interference due to geostationary satellite broadcasts. Since only a small number of retrievals are unsuccessful, almost complete global coverage is available daily. At high latitudes, where cloud cover regularly prevents infrared observations of SSTs, the microwave observations of SST provide a significant improvement to measurement capabilities. Validation of the datasets through comparison to the global drifting buoy networks yields mean biases of -0.02 K and standard deviations of 0.50 K. AMSR-E SSTs have been widely used for numerical weather prediction, ocean modeling, fisheries, and oceanographic research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUSM.A43A..03M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUSM.A43A..03M"><span id="translatedtitle">Comparing <span class="hlt">MODIS</span>-Terra and GOES surface albedo for New York City NY, Baltimore MD and Washington DC for 2005</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mubenga, K.; Hoff, R.; McCann, K.; Chu, A.; Prados, A.</p> <p>2006-05-01</p> <p>The NOAA GOES Aerosol and Smoke Product (GASP) is a product displaying the Aerosol Optical Depth (AOD) over the United States. The GASP retrieval involves discriminating the upwelling radiance from the atmosphere from that of the variable underlying surface. Unlike other sensors with more visible and near- infrared spectral channels such as <span class="hlt">MODIS</span>, the sensors on GOES 8 through 12 only have one visible and a several far infrared channels. The GASP algorithm uses the detection of the second-darkest pixel from the visible channel over a 28-day period as the reference from which a radiance look-up table gives the corresponding AOD. GASP is reliable in capturing the AOD during large events. As an example, GASP was able to precisely show the Alaska and British Columbia smoke plume advecting from Alaska to the northeastern U.S. during the summer of 2004. Knapp et al. (2005) has shown that the AOD retrieval for GOES- 8 is within +/-0.13 of AERONET ground data with a coefficient of correlation of 0.72. Prados (this meeting) will update that study. However, GASP may not be as reliable when it comes to observing smaller AOD events in the northeast where the surface brightness is relatively high. The presence of large cities, such as New York, increases the surface albedo and produces a bright background against which it may be difficult to deduce the AOD. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor on the Earth Observing System Terra and <span class="hlt">Aqua</span> platforms provides an independent measurement of the surface albedo at a resolution greater than available on GOES. In this research, the <span class="hlt">MODIS</span> and GOES surface albedo product for New York, Washington and Baltimore are compared in order to see how we can improve the AOD retrieval in urban areas for air quality applications. Ref: K. Knapp et al. 2005. Toward aerosol optical depth retrievals over land from GOES visible radiances: determining surface <span class="hlt">reflectance</span>. Int.Journal of Remote Sensing 26, 4097-4116</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C51A0477M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C51A0477M"><span id="translatedtitle"><span class="hlt">MODIS</span> Data and Services at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McAllister, M.; Fowler, D. K.</p> <p>2010-12-01</p> <p>For nearly a decade, the National Snow and Ice Data Center (NSIDC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra satellites. The archive contains a wide selection of data products relevant to cryospheric science, including snow and sea ice. NSIDC offers a variety of methods for obtaining these data. Our Data Pool is an online archive which allows a user to very quickly download desired products and also has a spatial and temporal search capability. The Warehouse Inventory Search Tool (WIST) contains a complete set of metadata for all products which can be searched for and ordered. WIST also allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new <span class="hlt">MODIS</span> data automatically ftp’d or staged on a local server as it is archived at NSIDC. Since <span class="hlt">MODIS</span> products are in HDF-EOS format, NSIDC has developed a number of tools to assist with browsing, editing, reprojection, resampling, and format conversion including <span class="hlt">MODIS</span> Swath-to-Grid Toolbox (MS2GT) and the <span class="hlt">MODIS</span> Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute <span class="hlt">MODIS</span> scenes. NSIDC created the MIST to also provide subsets of certain Version 5 <span class="hlt">MODIS</span> products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F"><span id="translatedtitle"><span class="hlt">MODIS</span> Collection 6 Data at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.</p> <p>2015-12-01</p> <p>For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra satellites. Collection 6 represents the next revision to NSIDC's <span class="hlt">MODIS</span> archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the <span class="hlt">MODIS</span> science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though <span class="hlt">MODIS</span> snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new <span class="hlt">MODIS</span> snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The <span class="hlt">MODIS</span> Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The <span class="hlt">MODIS</span> sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT........43G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT........43G"><span id="translatedtitle">Detection, evaluation, and analysis of global fire activity using <span class="hlt">MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Giglio, Louis</p> <p></p> <p>Global biomass burning plays a significant role in regional and global climate change, and spaceborne sensors offer the only practical way to monitor fire activity at these scales. This dissertation primarily concerns the development, evaluation, and use of the NASA Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instruments for fire monitoring. <span class="hlt">MODIS</span> is the first satellite sensor designed specifically for global monitoring of fires. An improved operational fire detection algorithm was developed for the <span class="hlt">MODIS</span> instrument. This algorithm offers a sensitivity to small, cool fires and minimizes false alarm rates. To support the accuracy assessment of the <span class="hlt">MODIS</span> global fire product, an operational fire detection algorithm was developed and evaluated for the ASTER instrument, which provides higher resolution observations coincident with the Terra <span class="hlt">MODIS</span>. The unique data set of multi-year <span class="hlt">MODIS</span> day and night fire observations was used to analyze the global distribution of biomass burning using five different temporal metrics which included, for the first time, mean fire radiative power, a measure of fire intensity. The metrics show the planetary extent, seasonality, and interannual variability of fire. Recognizing differences in fire activity between morning and afternoon overpasses, the impact of the diurnal cycle of fire activity was addressed using seven years of fire data from the VIRS sensor on-board the TRMM satellite. A strong diurnal cycle was found in all regions, with the time of peak burning varying between approximately 13:00 and 18:30 local time. Given interest in area burned among atmospheric chemical transport and carbon cycle modelers, a data set was developed utilizing the <span class="hlt">MODIS</span> global fire and vegetation cover products to estimate monthly burned area at 1-degree spatial resolution. The methods, products and results presented in this thesis provide the global change research and fire management communities with products for global fire monitoring and are currently being used in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010cosp...38..167R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010cosp...38..167R"><span id="translatedtitle">Ground based measurements on <span class="hlt">reflectance</span> towards validating atmospheric correction algorithms on IRS-P6 AWiFS data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rani Sharma, Anu; Kharol, Shailesh Kumar; Kvs, Badarinath; Roy, P. S.</p> <p></p> <p> aggregated ground measurements which showed a very good correlation of 0.96 in all four spectral bands (i.e. green, red, NIR and SWIR). In order to quantify the accuracy of the proposed method in the estimation of the surface <span class="hlt">reflectance</span>, the root mean square error (RMSE) associated to the proposed method was evaluated. The analysis of the ground measured versus retrieved AWiFS <span class="hlt">reflectance</span> yielded smaller RMSE values in case of all four spectral bands. EOS TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> derived AOD exhibited very good correlation of 0.92 and the data sets provides an effective means for carrying out atmospheric corrections in an operational way. Keywords: Atmospheric correction, 6S code, <span class="hlt">MODIS</span>, Spectroradiometer, Sun-Photometer</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT........27Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT........27Y"><span id="translatedtitle">Analysis, improvement and application of the <span class="hlt">MODIS</span> leaf area index products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Wenze</p> <p></p> <p>Green leaf area governs the exchanges of energy, mass and momentum between the Earth's surface and the atmosphere. Therefore, leaf area index (LAI) and fraction of incident photosynthetically active radiation (0.4-0.7 mum) absorbed by the vegetation canopy (FPAR) are widely used in vegetation monitoring and modeling. The launch of Terra and <span class="hlt">Aqua</span> satellites with the moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) instrument onboard provided the first global products of LAI and FPAR, derived mainly from an algorithm based on radiative transfer. The objective of this research is to comprehensively evaluate the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> LAI/FPAR products. Large volumes of these products have been analyzed with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus back-up), snow (snow-free versus snow on the ground) and cloud (cloud-free versus cloudy) conditions. Field validation efforts identified several key factors that influence the accuracy of algorithm retrievals. The strategy of validation efforts guiding algorithm refinements has led to progressively more accurate LAI/FPAR products. The combination of products derived from the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> sensors increases the success rate of the main radiative transfer algorithm by 10-20 percent over woody vegetation. The Terra Collection 4 LAI data reveal seasonal swings in green leaf area of about 25 percent in a majority of the Amazon rainforests caused by variability in cloud cover and light. The timing and the influence of this seasonal cycle are critical to understanding tropical plant adaptation patterns and ecological processes. The results presented in this dissertation suggest how the product quality has gradually improved largely through the efforts of validation activities. The Amazon case study highlights the utility of these data sets for monitoring global vegetation dynamics. Thus, these results can be seen as a benchmark for evaluation of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011354','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011354"><span id="translatedtitle">Improvement of Aerosol Optical Depth Retrieval from <span class="hlt">MODIS</span> Spectral <span class="hlt">Reflectance</span> over the Global Ocean Using New Aerosol Models Archived from AERONET Inversion Data and Tri-axial Ellipsoidal Dust Database</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lee, J.; Kim, J.; Yang, P.; Hsu, N. C.</p> <p>2012-01-01</p> <p>New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) in the case of high AOD (AOD greater than 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the singlescattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and <span class="hlt">MODIS</span> for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the <span class="hlt">MODIS</span> Collection 5 data. Moreover, the percentage of data within an expected error of +/-(0.03 + 0.05xAOD) is increased from 62 percent to 64 percent for overall data and from 39 percent to 51 percent for AOD greater than 0.3. Errors in the retrieved AOD are further characterized with respect to the Angstrom exponent (AE), scattering angle, SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1110474','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1110474"><span id="translatedtitle">Visual Modeling for <span class="hlt">Aqua</span> Ventus I off Monhegan Island, ME</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Hanna, Luke A.; Whiting, Jonathan M.; Copping, Andrea E.</p> <p>2013-11-27</p> <p>To assist the University of Maine in demonstrating a clear pathway to project completion, PNNL has developed visualization models of the <span class="hlt">Aqua</span> Ventus I project that accurately depict the <span class="hlt">Aqua</span> Ventus I turbines from various points on Monhegain Island, ME and the surrounding area. With a hub height of 100 meters, the <span class="hlt">Aqua</span> Ventus I turbines are large and may be seen from many areas on Monhegan Island, potentially disrupting important viewsheds. By developing these visualization models, which consist of actual photographs taken from Monhegan Island and the surrounding area with the <span class="hlt">Aqua</span> Ventus I turbines superimposed within each photograph, PNNL intends to support the project’s siting and permitting process by providing the Monhegan Island community and various other stakeholders with a probable glimpse of how the <span class="hlt">Aqua</span> Ventus I project will appear.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001276&hterms=farming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dfarming','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001276&hterms=farming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dfarming"><span id="translatedtitle">Argentina from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>This Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) image over Argentina was acquired on April 24, 2000, and was produced using a combination of the sensor's 250-m and 500-m resolution 'true color' bands. This image was presented on June 13, 2000 as a GIFt to Argentinian President Fernando de la Rua by NASA Administrator Dan Goldin. Note the Parana River which runs due south from the top of the image before turning east to empty into the Atlantic Ocean. Note the yellowish sediment from the Parana River mixing with the redish sediment from the Uruguay River as it empties into the Rio de la Plata. The water level of the Parana seems high, which could explain the high sediment discharge. A variety of land surface features are visible in this image. To the north, the greenish pixels show forest regions, as well as characteristic clusters of rectangular patterns of agricultural fields. In the lower left of the image, the lighter green pixels show arable regions where there is grazing and farming. (Image courtesy Jacques Descloitres, <span class="hlt">MODIS</span> Land Group, NASA GSFC)</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMEP21A0569G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMEP21A0569G"><span id="translatedtitle">Geomorphology of <span class="hlt">MODIS</span>-Visible Dust Plumes in the Chihuahuan Desert - Preliminary Results</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gill, T. E.; Mbuh, M. J.; Dominguez, M. A.; Lee, J. A.; Baddock, M. C.; Lee, C. E.; Whitehead, S. C.; Rivera Rivera, N. I.; Peinado, P.</p> <p>2009-12-01</p> <p>We identified 28 days since 2001 when blowing dust impacted El Paso, Texas and dust plumes were visible on NASA <span class="hlt">MODIS</span> Terra/<span class="hlt">Aqua</span> satellite images in the surrounding Chihuahuan Desert. Initiation points of >270 individual plumes were located on the <span class="hlt">MODIS</span> images. Land use/land cover for each point was determined by field work, aerial photography, and/or soil/geological maps, and points were assigned to the geomorphic classes proposed by Bullard et al. (this session). Although dust plume identification is subjective (weak plumes, plumes obscured by clouds, and plumes occurring when the satellites are not overhead will be missed), these data provide preliminary information on the relationship between geomorphology and the initiation of major dust storms in the Chihuahuan Desert. Ephemeral lakes and alluvial low-relief non-incised lands are roughly equal producers of satellite-visible dust plumes in the Chihuahuan Desert. Anthropogenic modification of alluvial floodplains for cropping (primarily in the Casas Grandes and Del Carmen river basins) impacts dust generation, since about 2/3 of alluvial low-relief sites show evidence of agriculture. These agricultural fields are generally fallow during the November- April windy season. Not including agricultural lands, playas represent ~2x the number of sources as low-relief alluvial deposits. Aeolian sand deposits (predominantly coppice dunes and sand sheets overlaying alluvial or lacustrine sediments) account for about 1/7 of the points. These sands may act as erosional agents, providing saltating particles for sandblasting and bombardment of other sediments exposed nearby. Edges of ephemeral lakes are proportionally important sources (~10% of the points), likely due to the convergence of saltating sand, fine lacustrine sediments, and low roughness lengths of playa surfaces. Alluvial fans and alluvial uplands are minor dust sources compared to their overall prevalence in the region. Gobi/gibber/stony deposits are known dust</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013JARS....7.3557T&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013JARS....7.3557T&link_type=ABSTRACT"><span id="translatedtitle">Terra and <span class="hlt">Aqua</span> moderate-resolution imaging spectroradiometer collection 6 level 1B algorithm</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toller, Gary; Xiong, Xiaoxiong; Sun, Junqiang; Wenny, Brian N.; Geng, Xu; Kuyper, James; Angal, Amit; Chen, Hongda; Madhavan, Sriharsha; Wu, Aisheng</p> <p>2013-01-01</p> <p>The moderate-resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) was launched on the Terra spacecraft on Dec.18, 1999 and on Aquaon May 4, 2002. The data acquired by these instruments have contributed to the long-term climate data record for more than a decade and represent a key component of NASA's Earth observing system. Each <span class="hlt">MODIS</span> instrument observes nearly the whole Earth each day, enabling the scientific characterization of the land, ocean, and atmosphere. The <span class="hlt">MODIS</span> Level 1B (L1B) algorithms input uncalibrated geo-located observations and convert instrument response into calibrated <span class="hlt">reflectance</span> and radiance, which are used to generate science data products. The instrument characterization needed to run the L1B code is currently implemented using time-dependent lookup tables. The <span class="hlt">MODIS</span> characterization support team, working closely with the <span class="hlt">MODIS</span> Science Team, has improved the product quality with each data reprocessing. We provide an overview of the new L1B algorithm release, designated collection 6. Recent improvements made as a consequence of on-orbit calibration, on-orbit analyses, and operational considerations are described. Instrument performance and the expected impact of L1B changes on the collection 6 L1B products are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A23G..02G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A23G..02G&link_type=ABSTRACT"><span id="translatedtitle">Investigating the impact of haze on cloud detection of passive satellite by comparing <span class="hlt">MODIS</span>, CloudSat and CALIPSO</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gong, W.; Mao, F.</p> <p>2015-12-01</p> <p>The cloud detection algorithm for passive sensors is usually based on a fuzzy logic system with thresholds determined from previous observations. In recent years, haze and high aerosol concentrations with high AOD occur frequently in China and may critically impact the accuracy of the <span class="hlt">MODIS</span> cloud detection. Thus, we comprehensively explore this impact by comparing the results from <span class="hlt">MODIS/Aqua</span> (passive sensor), CALIOP/CALIPSO (lidar sensor), and CPR/CloudSat (microwave sensor) of the A-Train suite of instruments using an averaged AOD as an index for an aerosol concentration value. Case studies concerning the comparison of the three sensors indicate that <span class="hlt">MODIS</span> cloud detection is reduced during haze events. In addition, statistical studies show that an increase in AOD creates an increase in the percentage of uncertain flags and a decrease in hit rate, a consistency index between consecutive sets of cloud retrievals. Therefore, we can conclude that the ability of <span class="hlt">MODIS</span> cloud detection is weakened by large concentrations of aerosols. This suggests that use of the <span class="hlt">MODIS</span> cloud mask, and derived higher level products, in situations with haze requires caution. Further improvement of this retrieval algorithm, is desired as haze studies based on <span class="hlt">MODIS</span> products are of great interest in a number of related fields.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013289','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013289"><span id="translatedtitle">An Examination of the Nature of Global <span class="hlt">MODIS</span> Cloud Regimes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.</p> <p>2014-01-01</p> <p>We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument aboard the <span class="hlt">Aqua</span> and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the <span class="hlt">MODIS</span> cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20100014358&hterms=TENS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DTENS','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20100014358&hterms=TENS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DTENS"><span id="translatedtitle">Ten Years of Cloud Optical and Microphysical Retrievals from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana</p> <p>2010-01-01</p> <p>The <span class="hlt">MODIS</span> cloud optical properties algorithm (MOD06/MYD06 for Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26197587','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26197587"><span id="translatedtitle">[Impact of Vegetation Structure on Drought Indices Based on <span class="hlt">MODIS</span> Spectrum].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Du, Ling-tong; Tian, Qing-jiu; Wang, Lei</p> <p>2015-04-01</p> <p>The drought indices based on <span class="hlt">MODIS</span> spectral <span class="hlt">reflectance</span> data are widely used for drought characterization and monitoring in agricultural context. Based on the PROSAIL model and <span class="hlt">MODIS</span> observational data in Shandong in 2010, the present paper studied the impact of vegetation structure of leaf area index and physiological growth cycle on <span class="hlt">MODIS</span> spectral drought index. The results showed that the <span class="hlt">reflectance</span> of three <span class="hlt">MODIS</span> bands in spectrum of near-infrared and shortwave infrared changes significantly with leaf water content of vegetation. Therefore, the five kinds of <span class="hlt">MODIS</span> spectral drought index constructed by those <span class="hlt">MODIS</span> bands can be used to monitor the leaf water content of vegetation. However, all drought indices are affected by leaf area index. In general, the impact is serious in the case of low LAI values and is weakened with the increase in LAI value. The study found that physiological vegetation growth cycle also affects the magnitude of <span class="hlt">MODIS</span> spectral drought indices. In conclusion, the impact of vegetation structure must be carefully considered when using <span class="hlt">MODIS</span> spectral drought indices to monitor drought. The conclusion of this study provides a theoretical basis for remote sensing of drought monitoring. PMID:26197587</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040015040','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040015040"><span id="translatedtitle"><span class="hlt">MODIS</span> Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fargion, Giulietta S.; McClain, Charles R.</p> <p>2003-01-01</p> <p>The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, satellite data processing, and data product validation. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Earth Observing System (EOS) Terra platform (similar evaluations of <span class="hlt">MODIS/Aqua</span> are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040034204','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040034204"><span id="translatedtitle">Passive and Active Detection of Clouds: Comparisons between <span class="hlt">MODIS</span> and GLAS Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mahesh, Ashwin; Gray, Mark A.; Palm, Stephen P.; Hart, William D.; Spinhirne, James D.</p> <p>2003-01-01</p> <p>The Geoscience Laser Altimeter System (GLAS), launched on board the Ice, Cloud and Land Elevation Satellite in January 2003 provides space-borne laser observations of atmospheric layers. GLAS provides opportunities to validate passive observations of the atmosphere for the first time from space with an active optical instrument. Data from the Moderate Resolution Imaging Spectrometer aboard the <span class="hlt">Aqua</span> satellite is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, <span class="hlt">MODIS</span> scene identification from spectral radiances agrees with GLAS. Disagreement between the two platforms is most significant over snow-covered surfaces in the northern hemisphere. Daytime clouds detected by GLAS are also more easily seen in the <span class="hlt">MODIS</span> data as well, compared to observations made at night. These comparisons illustrate the capabilities of active remote sensing to validate and assess passive measurements, and also to complement them in studies of atmospheric layers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140012657','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140012657"><span id="translatedtitle">Comparing <span class="hlt">MODIS</span> C6 'Deep Blue' and 'Dark Target' Aerosol Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. C.; Sayer, A. M.; Bettenhausen, C.; Lee, J.; Levy, R. C.; Mattoo, S.; Munchak, L. A.; Kleidman, R.</p> <p>2014-01-01</p> <p>The <span class="hlt">MODIS</span> Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110022522','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110022522"><span id="translatedtitle">Radiometric Quality of the <span class="hlt">MODIS</span> Bands at 667 and 678nm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Franz, Bryan A.</p> <p>2011-01-01</p> <p>The <span class="hlt">MODIS</span> instruments on Terra and <span class="hlt">Aqua</span> were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top-of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other <span class="hlt">MODIS</span> bands.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015306','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015306"><span id="translatedtitle">Radiometric Quality of the <span class="hlt">MODIS</span> Bands at 667 and 678nm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Franz, Bryan A.</p> <p>2010-01-01</p> <p>The <span class="hlt">MODIS</span> instruments on Terra and <span class="hlt">Aqua</span> were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top- of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other <span class="hlt">MODIS</span> bands.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27505382','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27505382"><span id="translatedtitle">Degradation nonuniformity in the solar diffuser bidirectional <span class="hlt">reflectance</span> distribution function.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sun, Junqiang; Chu, Mike; Wang, Menghua</p> <p>2016-08-01</p> <p>The assumption of angular dependence stability of the solar diffuser (SD) throughout degradation is critical to the on-orbit calibration of the <span class="hlt">reflective</span> solar bands (RSBs) in many satellite sensors. Recent evidence has pointed to the contrary, and in this work, we present a thorough investigative effort into the angular dependence of the SD degradation for the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite and for the twin Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) onboard Terra and <span class="hlt">Aqua</span> spacecrafts. One common key step in the RSB calibration is the use of the SD degradation performance measured by an accompanying solar diffuser stability monitor (SDSM) as a valid substitute for the SD degradation factor in the direction of the RSB view. If SD degradations between these two respective directions do not maintain the same relative relationship over time, then the unmitigated use of the SDSM-measured SD degradation factor in the RSB calibration calculation will generate bias, and consequently, long-term drift in derived science products. We exploit the available history of the on-orbit calibration events to examine the response of the SDSM and the RSB detectors to the incident illumination <span class="hlt">reflecting</span> off SD versus solar declination angle and show that the angular dependency, particularly at short wavelengths, evolves with respect to time. The generalized and the decisive conclusion is that the bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) of the SD degrades nonuniformly with respect to both incident and outgoing directions. Thus, the SDSM-based measurements provide SD degradation factors that are biased relative to the RSB view direction with respect to the SD. The analysis also reveals additional interesting phenomena, for example, the sharp behavioral change in the evolving angular dependence observed in Terra <span class="hlt">MODIS</span> and SNPP VIIRS. For SNPP VIIRS the mitigation for this</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/27505382','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/27505382"><span id="translatedtitle">Degradation nonuniformity in the solar diffuser bidirectional <span class="hlt">reflectance</span> distribution function.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sun, Junqiang; Chu, Mike; Wang, Menghua</p> <p>2016-08-01</p> <p>The assumption of angular dependence stability of the solar diffuser (SD) throughout degradation is critical to the on-orbit calibration of the <span class="hlt">reflective</span> solar bands (RSBs) in many satellite sensors. Recent evidence has pointed to the contrary, and in this work, we present a thorough investigative effort into the angular dependence of the SD degradation for the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite and for the twin Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) onboard Terra and <span class="hlt">Aqua</span> spacecrafts. One common key step in the RSB calibration is the use of the SD degradation performance measured by an accompanying solar diffuser stability monitor (SDSM) as a valid substitute for the SD degradation factor in the direction of the RSB view. If SD degradations between these two respective directions do not maintain the same relative relationship over time, then the unmitigated use of the SDSM-measured SD degradation factor in the RSB calibration calculation will generate bias, and consequently, long-term drift in derived science products. We exploit the available history of the on-orbit calibration events to examine the response of the SDSM and the RSB detectors to the incident illumination <span class="hlt">reflecting</span> off SD versus solar declination angle and show that the angular dependency, particularly at short wavelengths, evolves with respect to time. The generalized and the decisive conclusion is that the bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) of the SD degrades nonuniformly with respect to both incident and outgoing directions. Thus, the SDSM-based measurements provide SD degradation factors that are biased relative to the RSB view direction with respect to the SD. The analysis also reveals additional interesting phenomena, for example, the sharp behavioral change in the evolving angular dependence observed in Terra <span class="hlt">MODIS</span> and SNPP VIIRS. For SNPP VIIRS the mitigation for this</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160010516','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160010516"><span id="translatedtitle">Progress in Understanding the Impacts of 3-D Cloud Structure on <span class="hlt">MODIS</span> Cloud Property Retrievals for Marine Boundary Layer Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu</p> <p>2016-01-01</p> <p>Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in <span class="hlt">MODIS</span> retrievals caused by sub-pixel <span class="hlt">reflectance</span> inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences <span class="hlt">MODIS</span> LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed <span class="hlt">MODIS</span> cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRC..119.8646L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRC..119.8646L"><span id="translatedtitle">River runoff effect on the suspended sediment property in the upper Chesapeake Bay using <span class="hlt">MODIS</span> observations and ROMS simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Xiaoming; Wang, Menghua</p> <p>2014-12-01</p> <p>Ocean color data derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the satellite <span class="hlt">Aqua</span> from 2002 to 2012 and simulations from the Regional Ocean Modeling System (ROMS) are used to study the impact of the Susquehanna River discharge on the total suspended sediment (TSS) concentration in the upper Chesapeake Bay. Since the water in the upper Chesapeake Bay is highly turbid, the shortwave infrared (SWIR)-based atmospheric correction algorithm is used for deriving the normalized water-leaving radiance nLw(λ) spectra from <span class="hlt">MODIS-Aqua</span> measurements. nLw(λ) spectra are further processed into the diffuse attenuation coefficient at the wavelength of 490 nm Kd(490) and TSS. <span class="hlt">MODIS-Aqua</span>-derived monthly TSS concentration in the upper Chesapeake Bay and in situ Susquehanna River discharge data show similar patterns in seasonal variations. The TSS monthly temporal variation in the upper Chesapeake Bay is also found in phase with the monthly averaged river discharge data. Since the Susquehanna River discharge is mainly dominated by a few high discharge events due to winter-spring freshets or tropical storms in each year, the impact of these high discharge events on the upper Chesapeake Bay TSS is investigated. Both <span class="hlt">MODIS</span>-measured daily TSS images and sediment data derived from ROMS simulations show that the Susquehanna River discharge is the dominant factor for the variations of TSS concentration in the upper Chesapeake Bay. Although the high river discharge event usually lasts for only a few days, its induced high TSS concentration in the upper Chesapeake Bay can sustain for ˜10-20 days. The elongated TSS rebounding stage is attributed to horizontal advection of slowly settling fine sediment from the Susquehanna River.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001596&hterms=total+image&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dtotal%2Bimage','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001596&hterms=total+image&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dtotal%2Bimage"><span id="translatedtitle"><span class="hlt">MODIS</span> Measures Total U.S. Leaf Area</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>This composite image over the continental United States was produced with data acquired by the Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) during the period March 24 - April 8, 2000. The image is a map of the density of the plant canopy covering the ground. It is the first in a series of images over the continental U.S. produced by the <span class="hlt">MODIS</span> Land Discipline Group (refer to this site June 2 and 5 for the next two images in the series). The image is a <span class="hlt">MODIS</span> data product called 'Leaf Area Index,' which is produced by radiometrically measuring the visible and near infrared energy <span class="hlt">reflected</span> by vegetation. The Leaf Area Index provides information on the structure of plant canopy, showing how much surface area is covered by green foliage relative to total land surface area. In this image, dark green pixels indicate areas where more than 80 percent of the land surface is covered by green vegetation, light green pixels show where leaves cover about 10 to 50 percent of the land surface, and brown pixels show virtually no leaf coverage. The more leaf area a plant has, the more sunlight it can absorb for photosynthesis. Leaf Area Index is one of a new suite of measurements that scientists use to understand how the Earth's land surfaces are changing over time. Their goal is to use these measurements to refine computer models well enough to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. This image is the first of its kind from the <span class="hlt">MODIS</span> instrument, which launched in December 1999 aboard the Terra spacecraft. <span class="hlt">MODIS</span> began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The <span class="hlt">MODIS</span> instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, <span class="hlt">MODIS</span> Land Group Member, University of Montana</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.A21B0029E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.A21B0029E"><span id="translatedtitle">Detailed Analysis of the EOS-<span class="hlt">MODIS</span> Instrument's Fire Radiative Power Product</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ellison, L.; Ichoku, C. M.</p> <p>2010-12-01</p> <p>Fire emissions account for a significant amount of the earth's radiation budget, yet this process is still not well understood. The most practical way to gain a global perspective on biomass burning and its effects on the environment and climate is through spaceborne measurements, such as with the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor on board the Earth Observing System (EOS) satellites, Terra and <span class="hlt">Aqua</span>. Analysis of airborne measurements over active fires allowed the <span class="hlt">MODIS</span> fire science team to develop a semi-empirical algorithm for deriving the fire radiative power (FRP) product. Though this product has made its way into the scientific community, it has only been used tentatively due in part to the fact that it has not yet been validated. The algorithm itself has undergone dramatic changes in its latest update, but this has only resulted in more uncertainty especially due to the effects that <span class="hlt">MODIS</span>' scanning characteristics have on FRP measurements. This poster will present the work done insofar to characterize the uncertainty and gain an accepted, standard FRP product that can be used confidently within the scientific community. For instance, one of the error sources quantified and corrected for was the duplication of pixels for certain fires measured at a scan angle greater than about 15° due to <span class="hlt">MODIS</span>' ‘bow-tie’ effect. Comparisons between near-coincident FRP measurements from Terra and <span class="hlt">Aqua</span> at high latitudes where the two satellite overpass times are close, with one observing a specific fire near nadir and the other off nadir, has shown that, in addition to its scan angle dependency, differences also exist based on the fire strength. A brief illustration of fire visualization tools, specializing in the use of the FRP product, developed for both the scientific and public community will also be shown.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120014239','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120014239"><span id="translatedtitle">Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from <span class="hlt">MODIS</span> Collection 6</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent</p> <p>2012-01-01</p> <p>The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and <span class="hlt">Aqua</span> platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 <span class="hlt">MODIS</span> retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m <span class="hlt">MODIS</span> cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A44B..04P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A44B..04P"><span id="translatedtitle">Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from <span class="hlt">MODIS</span> Collection 6</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.</p> <p>2012-12-01</p> <p>The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and <span class="hlt">Aqua</span> platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 <span class="hlt">MODIS</span> retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m <span class="hlt">MODIS</span> cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A51N0281M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A51N0281M&link_type=ABSTRACT"><span id="translatedtitle">Aerosol Characterisitics Over Alberta Using <span class="hlt">Modis</span> and OMI Satellite Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marey, H. S.; Hashisho, Z., Sr.; Fu, L.; Gille, J. C.</p> <p>2015-12-01</p> <p>We present the first detailed analysis of optical aerosol characterization over Alberta based on satellite data analysis. Aerosol optical depth (AOD) at 550 nm for 11 years (2003-2013), derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor onboard NASA's <span class="hlt">Aqua</span> satellite, was analyzed. Additionally, UV aerosol index (AI) data for 9 years (2005-2013) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite was used to examine absorbing aerosols. Comparing AERONET to <span class="hlt">MODIS</span> 3 km and 10 km products indicated a stronger correlation (r=0.9 for the latter vs 0.7 for the former) thus 10 km product has been utilized for this study. Overall, gridded seasonal maps (0.1 deg.) of the 11 yr averaged AOD illustrate the highest AOD during summer, followed by spring, with the lowest observed values during fall (there is no enough valid <span class="hlt">MODIS</span> data in winter due to cloud cover). Aerosol optical properties exhibited large spatio-temporal heterogeneity in the summer with mean AOD of 0.25, followed by spring, while the fall had less variability with mean AOD below 0.1 for the entire region. However, the spatial analysis indicated hot spots around Edmonton and Calgary cities even in the fall when AODs are very low (close to background). All of the datasets showed interannual variability with no significant trend. The AI values ranged from 0.5 during winter to as high as 5 during summer suggesting mid- and long range transport of boreal fire emissions. Map correlation between AOD and UV AI showed large variability (0.2 to 0.7) indicating presence of different types of aerosols. These low correlations imply the presence of non-absorbing particles (e.g. sulfate) that comprise a relatively large mass fraction of AOD and/or low altitude particles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20000038134&hterms=ieee&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dieee','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20000038134&hterms=ieee&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dieee"><span id="translatedtitle">Improving the <span class="hlt">MODIS</span> Global Snow-Mapping Algorithm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Klein, Andrew G.; Hall, Dorothy K.; Riggs, George A.</p> <p>1997-01-01</p> <p>An algorithm (Snowmap) is under development to produce global snow maps at 500 meter resolution on a daily basis using data from the NASA <span class="hlt">MODIS</span> instrument. <span class="hlt">MODIS</span>, the Moderate Resolution Imaging Spectroradiometer, will be launched as part of the first Earth Observing System (EOS) platform in 1998. Snowmap is a fully automated, computationally frugal algorithm that will be ready to implement at launch. Forests represent a major limitation to the global mapping of snow cover as a forest canopy both obscures and shadows the snow underneath. Landsat Thematic Mapper (TM) and <span class="hlt">MODIS</span> Airborne Simulator (MAS) data are used to investigate the changes in <span class="hlt">reflectance</span> that occur as a forest stand becomes snow covered and to propose changes to the Snowmap algorithm that will improve snow classification accuracy forested areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940007013','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940007013"><span id="translatedtitle">Global monitoring of atmospheric properties by the EOS <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.</p> <p>1993-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) being developed for the Earth Observing System (EOS) is well suited to the global monitoring of atmospheric properties from space. Among the atmospheric properties to be examined using <span class="hlt">MODIS</span> observations, clouds are especially important, since they are a strong modulator of the shortwave and longwave components of the earth's radiation budget. A knowledge of cloud properties (such as optical thickness and effective radius) and their variation in space and time, which are our task objectives, is also crucial to studies of global climate change. In addition, with the use of related airborne instrumentation, such as the Cloud Absorption Radiometer (CAR) and <span class="hlt">MODIS</span> Airborne Simulator (MAS) in intensive field experiments (both national and international campaigns, see below), various types of surface and cloud properties can be derived from the measured bidirectional <span class="hlt">reflectances</span>. These missions have provided valuable experimental data to determine the capability of narrow bandpass channels in examining the Earth's atmosphere and to aid in defining algorithms and building an understanding of the ability of <span class="hlt">MODIS</span> to remotely sense atmospheric conditions for assessing global change. Therefore, the primary task objective is to extend and expand our algorithm for retrieving the optical thickness and effective radius of clouds from radiation measurements to be obtained from <span class="hlt">MODIS</span>. The secondary objective is to obtain an enhanced knowledge of surface angular and spectral properties that can be inferred from airborne directional radiance measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150023340','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150023340"><span id="translatedtitle">Improvements of VIIRS and <span class="hlt">MODIS</span> Solar Diffuser and Lunar Calibration</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Butler, James J.; Lei, Ning; Sun, Junqiang; Fulbright, Jon; Wang, Zhipeng; McIntire, Jeff; Angal, Amit Avinash</p> <p>2013-01-01</p> <p>Both VIIRS and <span class="hlt">MODIS</span> instruments use solar diffuser (SD) and lunar observations to calibrate their <span class="hlt">reflective</span> solar bands (RSB). A solar diffuser stability monitor (SDSM) is used to track the SD on-orbit degradation. On-orbit observations have shown similar wavelength-dependent SD degradation (larger at shorter VIS wavelengths) and SDSM detector response degradation (larger at longer NIR wavelengths) for both VIIRS and <span class="hlt">MODIS</span> instruments. In general, the <span class="hlt">MODIS</span> scan mirror has experienced more degradation in the VIS spectral region whereas the VIIRS rotating telescope assembly (RTA) mirrors have seen more degradation in the NIR and SWIR spectral region. Because of this wavelength dependent mirror degradation, the sensor's relative spectral response (RSR) needs to be modulated. Due to differences between the solar and lunar spectral irradiance, the modulated RSR could have different effects on the SD and lunar calibration. In this paper, we identify various factors that should be considered for the improvements of VIIRS and <span class="hlt">MODIS</span> solar and lunar calibration and examine their potential impact. Specifically, we will characterize and assess the calibration impact due to SD and SDSM attenuation screen transmission (uncertainty), SD BRF uncertainty and onorbit degradation, SDSM detector response degradation, and modulated RSR resulting from the sensor's optics degradation. Also illustrated and discussed in this paper are the calibration strategies implemented in the VIIRS and <span class="hlt">MODIS</span> SD and lunar calibrations and efforts that could be made for future improvements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23016343','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23016343"><span id="translatedtitle">[On-orbit response variation analysis of FY-3 MERSI <span class="hlt">reflective</span> solar bands based on Dunhuang site calibration].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sun, Ling; Guo, Mao-Hua; Xu, Na; Zhang, Li-Jun; Liu, Jing-Jing; Hu, Xiu-Qing; Li, Yuan; Rong, Zhi-Guo; Zhao, Ze-Hui</p> <p>2012-07-01</p> <p>MERSI is the keystone payload of FengYun-3 and there have been two sensors operating on-orbit since 2008. The on-orbit response changes obviously at <span class="hlt">reflective</span> solar bands (RSBs) and must be effectively monitored and corrected. However MERSI can not realize the RSBs onboard absolute radiometric calibration. This paper presents a new vicarious calibration (VC) method for RSBs based on in-situ BRDF model, and vector radiometric transfer model 6SV with gaseous absorption correction using MOTRAN. The results of synchronous VC experiments in 4 years show that the calibration uncertainties are within 5% except for band at the center of water vapor absorption, and 3% for most bands. <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> was taken as the radiometric reference to evaluate the accuracy of this VC method. By comparison of the simulated radiation at top of atmosphere (TOA) with <span class="hlt">MODIS</span> measurement, it was revealed that the average relative differences are within 3% for window bands with wavelengths less than 1 microm, and 5% for bands with wavelengths larger than 1 microm (except for band 7 at 2.1 microm). Besides, the synchronous nadir observation cross analysis shows the excellent agreement between re-calibrated MERSI TOA apparent <span class="hlt">reflectance</span> and <span class="hlt">MODIS</span> measurements. Based on the multi-year site calibration results, it was found that the calibration coefficients could be fitted with two-order polynomials, thus the daily calibration updates could be realized and the response variation between two calibration experiments could be corrected timely; there are large response changes at bands with wavelengths less than 0.6 microm, the degradation rate of the first year at band 8 (0.41 microm) is about 14%; the on-orbit response degradation is maximum at the beginning, the degradation rates slow down after one year in operation, and after two years the responses even increase at some band with wavelengths larger than 0.6 microm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015305','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015305"><span id="translatedtitle">Adjustments to the <span class="hlt">MODIS</span> Terra Radiometric Calibration and Polarization Sensitivity in the 2010 Reprocessing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Franz, Bryan A.</p> <p>2011-01-01</p> <p>The Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on NASA s Earth Observing System (EOS) satellite Terra provides global coverage of top-of-atmosphere (TOA) radiances that have been successfully used for terrestrial and atmospheric research. The <span class="hlt">MODIS</span> Terra ocean color products, however, have been compromised by an inadequate radiometric calibration at the short wavelengths. The Ocean Biology Processing Group (OBPG) at NASA has derived radiometric corrections using ocean color products from the SeaWiFS sensor as truth fields. In the R2010.0 reprocessing, these corrections have been applied to the whole mission life span of 10 years. This paper presents the corrections to the radiometric gains and to the instrument polarization sensitivity, demonstrates the improvement to the Terra ocean color products, and discusses issues that need further investigation. Although the global averages of <span class="hlt">MODIS</span> Terra ocean color products are now in excellent agreement with those of SeaWiFS and <span class="hlt">MODIS</span> <span class="hlt">Aqua</span>, and image quality has been significantly improved, the large corrections applied to the radiometric calibration and polarization sensitivity require additional caution when using the data.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017659','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017659"><span id="translatedtitle">Corrections to <span class="hlt">MODIS</span> Terra Calibration and Polarization Trending Derived from Ocean Color Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Eplee, Robert E.; Franz, Bryan A.</p> <p>2014-01-01</p> <p>Remotely sensed ocean color products require highly accurate top-of-atmosphere (TOA) radiances, on the order of 0.5% or better. Due to incidents both prelaunch and on-orbit, meeting this requirement has been a consistent problem for the <span class="hlt">MODIS</span> instrument on the Terra satellite, especially in the later part of the mission. The NASA Ocean Biology Processing Group (OBPG) has developed an approach to correct the TOA radiances of <span class="hlt">MODIS</span> Terra using spatially and temporally averaged ocean color products from other ocean color sensors (such as the SeaWiFS instrument on Orbview-2 or the <span class="hlt">MODIS</span> instrument on the <span class="hlt">Aqua</span> satellite). The latest results suggest that for <span class="hlt">MODIS</span> Terra, both linear polarization parameters of the Mueller matrix are temporally evolving. A change to the functional form of the scan angle dependence improved the quality of the derived coefficients. Additionally, this paper demonstrates that simultaneously retrieving polarization and gain parameters improves the gain retrieval (versus retrieving the gain parameter only).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70027625','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70027625"><span id="translatedtitle">Multi-platform comparisons of <span class="hlt">MODIS</span> and AVHRR normalized difference vegetation index data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Gallo, K.; Ji, L.; Reed, B.; Eidenshink, J.; Dwyer, J.</p> <p>2005-01-01</p> <p>The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor. NDVI data derived from visible and near-infrared data acquired by the <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span> platforms) and AVHRR (NOAA-16 and NOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the <span class="hlt">MODIS</span> NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the <span class="hlt">MODIS</span> NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems. ?? 2005 Elsevier Inc. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26458381','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26458381"><span id="translatedtitle">Undiagnosed <span class="hlt">MODY</span>: Time for Action.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kleinberger, Jeffrey W; Pollin, Toni I</p> <p>2015-12-01</p> <p>Maturity-onset diabetes of the young (<span class="hlt">MODY</span>) is a monogenic form of diabetes that accounts for at least 1 % of all cases of diabetes mellitus. <span class="hlt">MODY</span> classically presents as non-insulin-requiring diabetes in lean individuals typically younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of <span class="hlt">MODY</span> is important for selecting the right treatment, yet ~95 % of <span class="hlt">MODY</span> cases in the USA are misdiagnosed. <span class="hlt">MODY</span> prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible; at the same time, they are detecting other mutations in the same genes of unknown clinical significance. This review will cover the current epidemiological studies of <span class="hlt">MODY</span> and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals. PMID:26458381</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001471&hterms=colder+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcolder%2Bnear%2Bocean','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001471&hterms=colder+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcolder%2Bnear%2Bocean"><span id="translatedtitle"><span class="hlt">MODIS</span> Global Sea Surface Temperature</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>Every day the Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) measures sea surface temperature over the entire globe with high accuracy. This false-color image shows a one-month composite for May 2001. Red and yellow indicates warmer temperatures, green is an intermediate value, while blues and then purples are progressively colder values. The new <span class="hlt">MODIS</span> sea surface temperature product will be particularly useful in studies of temperature anomalies, such as El Nino, as well as research into how air-sea interactions drive changes in weather and climate patterns. In the high resolution image, notice the amazing detail in some of the regional current patterns. For instance, notice the cold water currents that move from Antarctica northward along South America's west coast. These cold, deep waters upwell along an equatorial swath around and to the west of the Galapagos Islands. Note the warm, wide currents of the Gulf Stream moving up the United States' east coast, carrying Caribbean warmth toward Newfoundland and across the Atlantic toward Western Europe. Note the warm tongue of water extending from Africa's east coast to well south of the Cape of Good Hope. <span class="hlt">MODIS</span> was launched in December 1999 aboard NASA's Terra satellite. For more details on this and other <span class="hlt">MODIS</span> data products, please see NASA Unveils Spectacular Suite of New Global Data Products from <span class="hlt">MODIS</span>. Image courtesy <span class="hlt">MODIS</span> Ocean Group, NASA GSFC, and the University of Miami</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=19930063699&hterms=earth+surface+dynamics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dearth%2Bsurface%2Bdynamics','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=19930063699&hterms=earth+surface+dynamics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dearth%2Bsurface%2Bdynamics"><span id="translatedtitle">Moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) and observations of the land surface</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, V. V.; Toll, D. L.; Lawrence, W. T.</p> <p>1992-01-01</p> <p>The moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) is a NASA facility instrument that is being designed for flight on the Earth Observing System (EOS) series of missions. It is designed to measure biophysical states and dynamics of the land, atmosphere, and ocean. Plans are required for use of other instruments that will be accompanying <span class="hlt">MODIS</span> on the EOS missions, such as the High-Resolution Imaging Spectrometer (HIRIS) and the Multi-angle Imaging Spectro-Radiometer (MISR). The HIRIS instrument, a spectrometer operating in the visible to shortwave infrared parts of the spectrum, would be employed in combination with the <span class="hlt">MODIS</span> to understand the impact of sampling the spectrum and the effects of land cover mixtures within the <span class="hlt">MODIS</span> pixel. The MISR will help in understanding the effects of anisotropy in <span class="hlt">reflected</span> solar radiation. Both instruments will work in combination with <span class="hlt">MODIS</span> to better quantify the effects of the atmosphere on observations of surface properties.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011189','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011189"><span id="translatedtitle"><span class="hlt">MODIS</span> 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Munchak, L. A.; Levy, R. C.; Mattoo, S.; Remer, L. A.; Holben, B. N.; Schafer, J. S.; Hostetler, C. A.; Ferrare, R. A.</p> <p>2013-01-01</p> <p>MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments aboard the Terra and <span class="hlt">Aqua</span> satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the <span class="hlt">MODIS</span> aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, <span class="hlt">MODIS</span> Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km <span class="hlt">MODIS</span> pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of <span class="hlt">MODIS</span>/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the <span class="hlt">MODIS</span> 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030054535','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030054535"><span id="translatedtitle">Exploring New Methods of Displaying Bit-Level Quality and Other Flags for <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Khalsa, Siri Jodha Singh; Weaver, Ron</p> <p>2003-01-01</p> <p>The NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC) archives and distributes snow and sea ice products derived from the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board NASA's Terra and <span class="hlt">Aqua</span> satellites. All <span class="hlt">MODIS</span> standard products are in the Earth Observing System version of the Hierarchal Data Format (HDF-EOS). The <span class="hlt">MODIS</span> science team has packed a wealth of information into each HDF-EOS file. In addition to the science data arrays containing the geophysical product, there are often pixel-level Quality Assurance arrays which are important for understanding and interpreting the science data. Currently, researchers are limited in their ability to access and decode information stored as individual bits in many of the <span class="hlt">MODIS</span> science products. Commercial and public domain utilities give users access, in varying degrees, to the elements inside <span class="hlt">MODIS</span> HDF-EOS files. However, when attempting to visualize the data, users are confronted with the fact that many of the elements actually represent eight different 1-bit arrays packed into a single byte array. This project addressed the need for researchers to access bit-level information inside <span class="hlt">MODIS</span> data files. In an previous NASA-funded project (ESDIS Prototype ID 50.0) we developed a visualization tool tailored to polar gridded HDF-EOS data set. This tool,called the Polar researchers to access, geolocate, visualize, and subset data that originate from different sources and have different spatial resolutions but which are placed on a common polar grid. The bit-level visualization function developed under this project was added to PHDIS, resulting in a versatile tool that serves a variety of needs. We call this the EOS Imaging Tool.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030054456&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3D%2528%2528%2528modis%2Bland%2529%2Bsurface%2529%2Btemperature%2529','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030054456&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3D%2528%2528%2528modis%2Bland%2529%2Bsurface%2529%2Btemperature%2529"><span id="translatedtitle">Land Surface Temperature Retrievals from GOES-8 Using Emissivities Retrieved from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Arnold, James E. (Technical Monitor); Suggs, Ronnie J.; Jedlovec, Gary J.; Lapenta, William M.; Haines, Stephanie L.</p> <p>2002-01-01</p> <p>Recent studies at the Global Hydrology and Climate Center (GHCC) have shown that the assimilation of land skin temperature (LST) tendencies into a mesoscale model can significantly improve short-term forecasts of near surface air temperature and moisture. Derived land surface products from the GOES satellites were used in these studies to provide high spatial and temporal resolution information about the spatial and temporal variability of the land surface forcing simulated in the model. In the model assimilation studies, LST was derived using a split window technique using the 11 and 12 pm channels found on the GOES-8 Sounder. These studies used a constant surface emissivity of 0.98 for both channels. However, this emissivity assumption over the land does not take into account emissivity variations due to varying terrain characteristics and differences between channels. These emissivity variations are seen to be significant as indicated by emissivity products from the polar orbiting <span class="hlt">MODIS</span> instrument channels similar to the GOES-8 Sounder channels mentioned above. <span class="hlt">MODIS</span> is a key instrument aboard the Terra (EOS AM) and <span class="hlt">Aqua</span> (EOS PM) satellites. In an attempt to improve the emissivity assumptions used in the GOES Sounder LST retrieval procedure, the incorporation of <span class="hlt">MODIS</span> high spatial resolution (1 km) emissivity measurements into the LST procedure is being explored. This paper intercompares the LST retrievals from the GOES-8 Sounder using a constant emissivity assumption with those using <span class="hlt">MODIS</span> retrieved emissivities. The effects of <span class="hlt">MODIS</span> emissivities on the LST retrievals are discussed. Potential improvements in model forecasts using assimilated LST products incorporating <span class="hlt">MODIS</span> emissivities are also examined.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.A41J3201R&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.A41J3201R&link_type=ABSTRACT"><span id="translatedtitle">Investigating Correlations of Horizontally Oriented Ice and Precipitation in North and South Pacific Maritime Clouds Using Collocated CloudSat, CALIOP, and <span class="hlt">MODIS</span> Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ross, A.; Holz, R.; Ackerman, S. A.</p> <p>2014-12-01</p> <p>In late 2007, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the A-train changed its nadir-viewing angle. The original viewing angle of 0.3° (changed to 3° in 2007) allowed the polarization capabilities of the Lidar to determine the orientation of ice crystals. This is because viewing ice clouds at a nadir angle closer to 0° will yield specular <span class="hlt">reflection</span> due to horizontally oriented ice. Similarly to how a vertical mirror will <span class="hlt">reflect</span> a laser that is pointed vertically, oriented ice crystals return a strong integrated attenuated backscatter while also returning low depolarization values. This results in a distinguished depolarization and attenuated backscatter signature for horizontally oriented ice crystals as opposed to ice crystals that have no pattern in orientation (i.e. randomly oriented ice). In a preliminary search, it is found that up to 20% of warm (250 - 270 K) mid-latitude middle level clouds contain horizontally oriented ice. By taking advantage of the nearly synchronous orbits of the A-train constellation, an opportune dataset from 2006 and 2007 is compiled. This dataset includes collocated products from the CloudSat Cloud Profiling Radar (CPR), CALIOP, and the <span class="hlt">Aqua</span> Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). The Lidar capabilities of CALIOP in conjunction with the microwave sensitivity to precipitation provided by the CloudSat CPR give a unique point of view to explore the connection between these two physical phenomena. Similarly, the spatial imaging from <span class="hlt">MODIS</span> yields insights into the phase of cloud layer tops and particles' effective radii. <span class="hlt">MODIS</span> aerosol optical depths may also shed light upon the cloud ice nucleation mechanisms that also may play a large role in the precipitation process. Preliminary results suggest that not all marine regions have the same occurrences of HOIC; the Northern Hemisphere demonstrates a strong seasonal dependence with a maximum in the winter months while the Southern Hemisphere is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1112471Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1112471Z"><span id="translatedtitle">Comparasion of Cloud Cover restituted by POLDER and <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.</p> <p>2009-04-01</p> <p>PARASOL and <span class="hlt">AQUA</span> are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and <span class="hlt">MODIS</span> provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and <span class="hlt">MODIS</span> level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and <span class="hlt">MODIS</span>. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, <span class="hlt">MODIS</span> can better detect the fractional clouds thus explaining as one part</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AIPC.1531...31L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AIPC.1531...31L"><span id="translatedtitle">Growing up <span class="hlt">MODIS</span>: Towards a mature aerosol climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, Robert C.</p> <p>2013-05-01</p> <p>. There are two orbiting <span class="hlt">MODIS</span> sensors (on Terra and <span class="hlt">Aqua</span>), and like human twins, they have had different life experiences; the result is a slightly different perspective on global aerosol distribution. To assess simple questions like "Is global aerosol increasing or decreasing?" requires detailed analyses into diverse subjects, such as instrument calibration, assumptions for gas correction, and aggregations of spatial sampling. With the recent launch of VIIRS on Suomi-NPP, there is a new addition to the aerosol monitoring "family." While preliminary indications are that it will produce a successful aerosol product, work on its position within the CDR is just beginning. In 1998, in addition to starting a new job, I joined a unique family composed of scientists around the world. I am grateful that the community has been supportive and nurturing. Of course, like in any family, there are many stories to tell. Here, at IRS-2012, I share some of my experiences of working within the collective <span class="hlt">MODIS</span> aerosol project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('//www.loc.gov/pictures/collection/hh/item/ca2039.photos.323803p/','SCIGOV-HHH'); return false;" href="//www.loc.gov/pictures/collection/hh/item/ca2039.photos.323803p/"><span id="translatedtitle">Building No. 905, showing typical <span class="hlt">aqua</span> medias or rain hoods ...</span></a></p> <p><a target="_blank" href="http://www.loc.gov/pictures/collection/hh/">Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey</a></p> <p></p> <p></p> <p>Building No. 905, showing typical <span class="hlt">aqua</span> medias or rain hoods - Presidio of San Francisco, Enlisted Men's Barracks Type, West end of Crissy Field, between Pearce & Maudlin Streets, San Francisco, San Francisco County, CA</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AdSpR..57..127G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AdSpR..57..127G"><span id="translatedtitle">Investigation and validation of <span class="hlt">MODIS</span> SST in the northern Persian Gulf</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ghanea, Mohsen; Moradi, Masoud; Kabiri, Keivan; Mehdinia, Ali</p> <p>2016-01-01</p> <p>Validation of satellite derived sea surface temperature (SST) is necessary since satellite minus buoy SST (= bias) relies on atmospheric and oceanographic conditions and time periods. This research validates <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span>) satellite daytime SST with buoy SST at the northern Persian Gulf. Sixteen dates during June 2011 to June 2015 were selected for validation. The buoy-satellite matchups were gained within one image pixel (1 km at nadir) and ±6 h in time. For most matchups, time interval was ±3 h. Effects of total column water vapor, aerosol optical depth, wind speed, glint, and satellite zenith angle on bias are then investigated. These parameters are classified based on root mean square (RMS) difference between satellite and buoy SST. Final results represent a near-perfect R2 (>0.989) for both satellites. The bias was 0.07 ± 0.53 °C and -0.06 ± 0.44 °C for <span class="hlt">MODIS-Aqua</span> and -Terra, respectively.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ISPAr.XL8.1383S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ISPAr.XL8.1383S"><span id="translatedtitle"><span class="hlt">Modis</span> data acquisition and utilization for forest fire management in india</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Satyanarayana, A. N.; Chandrashekara Rao, B.; Lalitha, D.; Lakshmi, B.</p> <p>2014-12-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument onboard Terra & <span class="hlt">Aqua</span> Spacecrafts Scans the earth in 36 spectral bands & covers the entire earth in two days. <span class="hlt">MODIS</span> data has proved to be very useful for ocean & land studies with resolution ranging from 250 m to 1000 meters. The Data Reception system at Shadnagar (Refer to the Block diagram Fig.1), receives the data transmitted in X-band on 8160 MHz carrier SQPSK modulated with a data rate of 15 MBPS from the <span class="hlt">Aqua</span> satellite. The down converted IF signal is fed to the demodulator & bit-synchronizer unit. The data and clock output signals of bitsynchronizer unit are given to a PC based DAQLB system where real-time telemetry processing is carried out and data is recorded onto hard disk in real time. The effectiveness of the system in supporting the forest fire management during the 2011, 12, 13 & 14 is also presented in the paper. Near real-time active fire monitoring, interactive fire visualization, fire database and statistical analysis functions also presented. Preliminary results of the upgrading satellite receiving system and in expanding the utilization of satellite data for multi-disciplinary resources management will also be presented and discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050180543','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050180543"><span id="translatedtitle">Validation of AIRS/AMSU Cloud Retrievals Using <span class="hlt">MODIS</span> Cloud Analyses</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Molnar, Gyula I.; Susskind, Joel</p> <p>2005-01-01</p> <p>The AIRS/AMSU (flying on the EOS-<span class="hlt">AQUA</span> satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by <span class="hlt">MODIS/AQUA</span> (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from <span class="hlt">MODIS</span>. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020081113','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020081113"><span id="translatedtitle"><span class="hlt">MODIS</span> Snow-Cover Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)</p> <p>2002-01-01</p> <p>On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Many geophysical products are derived from <span class="hlt">MODIS</span> data including global snow-cover products. <span class="hlt">MODIS</span> snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. <span class="hlt">MODIS</span> snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the <span class="hlt">MODIS</span> products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The <span class="hlt">MODIS</span> snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving <span class="hlt">MODIS</span> data and field and aircraft measurements, is presented to show some early validation work.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060028491','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060028491"><span id="translatedtitle">Overview of CERES Cloud Properties Derived From VIRS AND <span class="hlt">MODIS</span> DATA</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minis, Patrick; Geier, Erika; Wielicki, Bruce A.; Sun-Mack, Sunny; Chen, Yan; Trepte, Qing Z.; Dong, Xiquan; Doelling, David R.; Ayers, J. Kirk; Khaiyer, Mandana M.</p> <p>2006-01-01</p> <p>Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and <span class="hlt">Aqua</span> during late 1999 and early 2002, respectively. When combined, these satellites should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and <span class="hlt">Aqua</span> scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span> are analyzed to define the cloud properties for each CERES footprint. To minimize inter-satellite differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each satellite imager is calibrated in a fashion consistent with its counterpart on the other CERES satellites (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080044857&hterms=thermodynamics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dthermodynamics','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080044857&hterms=thermodynamics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dthermodynamics"><span id="translatedtitle">Comparison of the <span class="hlt">MODIS</span> Multilayer Cloud Detection and Thermodynamic Phase Products with CALIPSO and CloudSat</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; King, Michael D.; Wind, Gala; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.</p> <p>2008-01-01</p> <p>CALIPSO and CloudSat, launched in June 2006, provide global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the <span class="hlt">Aqua</span> spacecraft and other A-Train platforms. The most recent processing effort for the <span class="hlt">MODIS</span> Atmosphere Team, referred to as the "Collection 5" stream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the <span class="hlt">MODIS</span> cloud optical and microphysical product retrieval, which are generated at a 1 h resolution. Using pixel-level collocations of <span class="hlt">MODIS</span> <span class="hlt">Aqua</span>, CALIOP, and CloudSat radar measurements, we investigate the global performance of the thermodynamic phase and multilayer cloud detection algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010069265','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010069265"><span id="translatedtitle"><span class="hlt">MODIS</span> Snow-Cover Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)</p> <p>2001-01-01</p> <p>On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Many geophysical products are derived from <span class="hlt">MODIS</span> data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. <span class="hlt">MODIS</span> snow-cover products represent potential improvement to the currently available operation products mainly because the <span class="hlt">MODIS</span> products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving <span class="hlt">MODIS</span> data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940028781','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940028781"><span id="translatedtitle"><span class="hlt">MODIS</span>. Volume 1: <span class="hlt">MODIS</span> level 1A software baseline requirements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Masuoka, Edward; Fleig, Albert; Ardanuy, Philip; Goff, Thomas; Carpenter, Lloyd; Solomon, Carl; Storey, James</p> <p>1994-01-01</p> <p>This document describes the level 1A software requirements for the moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) instrument. This includes internal and external requirements. Internal requirements include functional, operational, and data processing as well as performance, quality, safety, and security engineering requirements. External requirements include those imposed by data archive and distribution systems (DADS); scheduling, control, monitoring, and accounting (SCMA); product management (PM) system; <span class="hlt">MODIS</span> log; and product generation system (PGS). Implementation constraints and requirements for adapting the software to the physical environment are also included.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713206M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713206M"><span id="translatedtitle">Detection of changes in snow line elevation from <span class="hlt">MODIS</span> imagery in the Romanian Carpathians</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Micu, Mihai; Micu, Dana; Sandric, Ionut; Mihalache, Sorin</p> <p>2015-04-01</p> <p>Mountain snow cover is particularly sensitive to the observed shifts in the regime of its two determinants (air temperature and precipitation), in response to climate warming. The climate of the Romanian Carpathians became warmer particularly in winter, spring and summer, exibiting an increasing frequency of hot extremes and a decrease of freezing days. There is also an obvious trend towards a late snowpack onset in Autumn, more evident in the areas below 1,700 m, and towards an earlier Spring snowmelting, generalized across the entire region. The observed changes in the timing of snowmelt due to milder winters, are explaining most of the decline of snow cover duration in the areas below 2,000 m. Snow line, separating snow covered from snow free areas, is considered a key indicator for monitoring the changes in snow coverage under the changing climate behavior. This study aims at deriving and analysing the changes in snowline elevation (SLE) using the multi-temporal Moderate-resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) <span class="hlt">reflectance</span> products (MYD10 and MOD10 daily and 8-day composite) and a high-resolution Digital Elevation Model (DEM) of the Romanian Carpathians (30 m). The changes in SLE were analyzed in relation to the shifts in freezing height (FH) across the Romanian Carpathians, derived from MYD11A1, MYD11A2, MOD11A1 and MOD11A2 daily and 8-day composite products, available at a spatial resolution of 1 km. Python batch scripts using Esri ArcPy were developed and applied to download, subset, reproject and mask each <span class="hlt">MODIS</span> product. The analyses were focused on producing and using daily and 8-day composites time series from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> products for a period of about 12 years, starting from 2002 up to present day. The variability of snow cover persistence was investigated at both monthly and seasonal time steps, allowing to identify the trends in SLE and FH, as well as the changes in the timing of snow melt across the region. The paper is revealing the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=19900039864&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectrometer%2Bresolution','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=19900039864&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectrometer%2Bresolution"><span id="translatedtitle">The Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, Vincent V.</p> <p>1990-01-01</p> <p>The Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) observing facility on the Earth Observing System (EOS) is composed of two instruments, <span class="hlt">MODIS</span>-Nadir (N) and <span class="hlt">MODIS</span>-Tilt (T). <span class="hlt">MODIS</span>-N has 36 spectral bands between 0.4 and 14.2 micrometers with spatial resolution between 214 and 856 meters. <span class="hlt">MODIS</span>-T has 32 bands with 10-15 nanometer bandwidths between 0.4 and 0.9 micrometers. <span class="hlt">MODIS</span>-T scans fore and aft + or - 50 degrees. Both instruments scan cross-track so as to provide daily (<span class="hlt">MODIS</span>-N) or once every 2 days (<span class="hlt">MODIS</span>-T) coverage at 705 kilometers altitude. Both instruments are entering into the execution phases of their development in 1990.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010EGUGA..12.5532D&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010EGUGA..12.5532D&link_type=ABSTRACT"><span id="translatedtitle">Snow cover retrieval over Rhone and Po river basins from <span class="hlt">MODIS</span> optical satellite data (2000-2009).</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo</p> <p>2010-05-01</p> <p>Estimation of the Snow Covered Area (SCA) is an important issue for meteorological application and hydrological modeling of runoff. With spectral bands in the visible, near and middle infrared, the <span class="hlt">MODIS</span> optical satellite sensor can be used to detect snow cover because of large differences between <span class="hlt">reflectance</span> from snow covered and snow free surfaces. At the same time, it allows separation between snow and clouds. Moreover, the sensor provides a daily coverage of large areas (2,500 km range). However, as the pixel size is 500m x 500m, a <span class="hlt">MODIS</span> pixel may be partially covered by snow, particularly in Alpine areas, where snow may not be present in valleys lying at lower altitudes. Also, variation of <span class="hlt">reflectance</span> due to differential sunlit effects as a function of slope and aspect, as well as bidirectional effects may be present in images. Nevertheless, it is possible to estimate snow cover at the Sub-Pixel level with a relatively good accuracy and with very good results if the sub-pixel estimations are integrated for a few pixels relative to an entire watershed. Integrated into the EU-FP7 ACQWA Project (www.acqwa.ch), this approach was first applied over Alpine area of Rhone river basin upper Geneva Lake: Canton du Valais, Switzerland (5 375 km²). In a second step over Alps, rolling hills and plain areas in Po catchment for Val d'Aosta and Piemonte regions, Italy (37 190 km²). Watershed boundaries were provided respectively by GRID (Ch) and ARPA (It) partners. The complete satellite images database was extracted from the U.S. <span class="hlt">MODIS</span>/NASA website (http://<span class="hlt">modis</span>.gsfc.nasa.gov/) for MOD09_B1 <span class="hlt">Reflectance</span> images, and from the <span class="hlt">MODIS</span>/NSIDC website (http://nsidc.org/index.html) for MOD10_A2 snow cover images. Only the Terra platform was used because images are acquired in the morning and are therefore better correlated with dry snow surface, avoiding cloud coverage of the afternoon (<span class="hlt">Aqua</span> Platform). The MOD9 Image <span class="hlt">reflectance</span> and MOD10_A2 products were respectively analyzed to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013SPIE.8921E..06X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013SPIE.8921E..06X"><span id="translatedtitle">Marine oil pollution detection with <span class="hlt">MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Lina; Niu, Ruiqing; Xiao, Kang; Fang, Shenghui; Dong, Yanfang</p> <p>2013-10-01</p> <p>Marine oil pollution is one of the most serious pollutants on the damage to the contemporary marine environment, with the characteristics of a wide range of proliferation, which is difficult to control and eliminate. As a result, marine oil pollution has caused huge economic losses. The remote sensing sensors can detect and record the spectral information of sea film and background seawater. Here we chose to use 250-resolution <span class="hlt">MODIS</span> data in the area of Dalian Xingang, China where ill spill case was happened on April.4th, 2005. Based on the image pre-processing and enhanced image processing, the spectral features of different bands were analyzed. More obvious characteristics of the spectral range of film was obtained. The oil-water contrast was calculated to evaluate the feature of oil at different spectral band. The result indicates that IR band has the maximum value of <span class="hlt">reflective</span>. So band ratio was used between 400nm and 800nm and the original radiance images were used between 800nm and 2130nm. In order to get the most obvious images of entropy windows of different sizes were tested in order to decide the optimum window. At last, a FCM fuzzy clustering method and image texture analysis was combined for the <span class="hlt">MODIS</span> images of the oil spill area segmentation. At last, the oil spill zone was estimated, the results were satisfied.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120017006','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120017006"><span id="translatedtitle">Multi-Angle Implementation of Atmospheric Correction for <span class="hlt">MODIS</span> (MAIAC). Part 3: Atmospheric Correction</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Wang, Y.; Laszlo, I.; Hilker, T.; Hall, F.; Sellers, P.; Tucker, J.; Korkin, S.</p> <p>2012-01-01</p> <p>This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional <span class="hlt">reflectance</span> distribution function (BRDF), spectral surface albedo and bidirectional <span class="hlt">reflectance</span> factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16 days of <span class="hlt">MODIS</span> data gridded to 1 km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free <span class="hlt">MODIS</span> top of atmosphere (TOA) <span class="hlt">reflectance</span> data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the <span class="hlt">MODIS</span> operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of <span class="hlt">reflectance</span> in the Red and NIR bands during the accumulation period. To adjust for the <span class="hlt">reflectance</span> variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of <span class="hlt">MODIS</span> data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized <span class="hlt">reflectance</span> stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing <span class="hlt">MODIS</span> data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional <span class="hlt">MODIS</span> products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C21C0629J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C21C0629J"><span id="translatedtitle"><span class="hlt">MODIS</span> Data at the National Snow and Ice Data Center: Improvements for Collection 6</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Johnston, T.; Fowler, D. K.; McAllister, M.; Hall, D. K.; Riggs, G. A.</p> <p>2012-12-01</p> <p>For more than a decade, the National Snow and Ice Data Center (NSIDC) has archived and distributed snow cover and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments, onboard NASA's Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra satellites. As the <span class="hlt">MODIS</span> science team studies and refines the algorithms that generate these products, the Earth Observing System Data and Information System (EOSDIS) periodically reprocesses an entire collection of <span class="hlt">MODIS</span> data and produces a new suite of products incorporating the latest enhancements. Collection 6 represents the next revision to NSIDC's <span class="hlt">MODIS</span> archive, mainly affecting the snow-cover products. Based on scores of journal papers and workshop proceedings, Collection 6 specifically addresses the needs of the <span class="hlt">MODIS</span> science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps. Although <span class="hlt">MODIS</span> snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered region, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Finally, Collection 6 introduces new <span class="hlt">MODIS</span> snow products, including a daily climate modeling-grid, cloud gap-filled (CGF) snow-cover map. The CGF algorithm generates cloud-free maps by using the most recent clear observation of the surface when the current day is cloudy, and tracks cloud persistence to account for uncertainties created by the age of a snow observation. By considering prior days, the CGF dramatically increases the number of observable grid cells and can potentially improve the accuracy of other snow-cover products</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080038648','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080038648"><span id="translatedtitle">Mapping Snow Grain Size over Greenland from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, Alexei; Tedesco, Marco; Wang, Yujie; Kokhanovsky, Alexander</p> <p>2008-01-01</p> <p>This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow <span class="hlt">reflectance</span> as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding <span class="hlt">MODIS</span> data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded <span class="hlt">MODIS</span> measurements and an image-based rather than pixel-based processing. Extensive processing of <span class="hlt">MODIS</span> TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from <span class="hlt">MODIS</span> over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, <span class="hlt">MODIS</span> SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than <span class="hlt">MODIS</span>-derived SGS. Overall, the agreement between CROCUS and <span class="hlt">MODIS</span> results was satisfactory, in particular before and during the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.U33B0066L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.U33B0066L"><span id="translatedtitle">Dark Target aerosol retrievals from <span class="hlt">MODIS</span>: What have we learned in 10 years?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Remer, L. A.; Mattoo, S.; Kleidman, R. G.; Leptoukh, G. G.; Kahn, R. A.; Tanré, D.</p> <p>2009-12-01</p> <p>As we celebrate the ten-year anniversary of Terra launch, we can step back and assess Yoram Kaufman’s vision of the global aerosol system. From Terra’s space vantage, the MODerate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) has observed global production and transport of aerosols, including plumes of desert dust, billows of smoke, and streams of pollution. From <span class="hlt">MODIS</span>, we now have a ten-year climatology that can be used to quantify not only the mean, but also interannual variability, anomalies and possibly trends. However, before we are able to interpret the results with confidence, we must ensure we have performed solid validation analyses. An identical twin <span class="hlt">MODIS</span>, launched aboard <span class="hlt">Aqua</span> two years after, has given us complementary characterization of the global aerosol system. We have applied consistent retrieval algorithms and processing procedures to both sensors for the entire mission, deriving the Collection 5 (C005) dark-target aerosol products. By comparing to measurements from over 300 globally distributed, ground-based AERONET sunphotometers, we have ‘validated’ along-orbit, aerosol optical depth (AOD or τ) over both ocean (66% within ±(0.04+0.05τ)) and land (66% within ±(0.05+0.15τ)). At the same time, we are learning why there are systematic biases in certain regions and seasons, and how we might correct for them. Yet there are differences between the two <span class="hlt">MODIS</span> instruments that are puzzling. They seem to give us inconsistent pictures of global means and trends. Some possible reasons include tiny calibration drifts, differences in sampling due to orbital geometry and clouds, as well as methods of aggregating the along-orbit (Level 2) data for deriving gridded daily and monthly statistics (Level 3). <span class="hlt">MODIS</span> has been observing aerosol for ten years, and we are working towards characterizing regional and global aerosol climatology with confidence.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.9090C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.9090C"><span id="translatedtitle">Methodology to obtain 30 m resolution of snow cover area from FSCA <span class="hlt">MODIS</span> and NDSI Landsat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cepeda, Javier; Vargas, Ximena</p> <p>2016-04-01</p> <p>In the last years numerous free images and product satellites have been released, with different spatial and temporal resolution. Out of them, the most commonly used to describe the snow area are <span class="hlt">MODIS</span> and Landsat. Fractional snow cover area (FSCA) is a daily <span class="hlt">MODIS</span> product with a 500 m spatial resolution; Landsat images have around 16 days and 30 m respectively. In this work we use both images to obtain a new daily 30 m resolution snow distribution product based in probabilistic and geospatial information. This can be useful because a higher resolution can be used to improve the estimation of the accuracy of a physically-based distributed model to represent the snow cover distribution. We choose three basins in central Chile, with an important snow and glacier presence, to analyze the spatial and temporal distribution of snow using (1) the mean value between MOD10A1 (terra) and MYD10A1 (<span class="hlt">aqua</span>) and (2) the corrected images by topography and atmosphere from Landsat 5 and Landsat 8 computing the normalized difference snow index (NDSI). When both satellites data are available in the same day, each <span class="hlt">MODIS</span> pixel is studied considering the Landsat pixels contained in it. A new matrix is created, covering all <span class="hlt">MODIS</span> pixels, using a 30 m spatial resolution, where each pixel value represents the probability of snow presence in time from Landsat images, and then each pixel is corrected by its neighbour's pixels, elevation, slope and aspect. Then snow is distributed, for each <span class="hlt">MODIS</span> pixel, considering the corrected probability matrix and sorted between pixels with high probability until the area from FSCA is completed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20010016270&hterms=KREBS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DKREBS','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20010016270&hterms=KREBS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DKREBS"><span id="translatedtitle"><span class="hlt">MODIS</span> Solar Diffuser: Modelled and Actual Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Waluschka, Eugene; Xiong, Xiao-Xiong; Esposito, Joe; Wang, Xin-Dong; Krebs, Carolyn (Technical Monitor)</p> <p>2001-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument's solar diffuser is used in its radiometric calibration for the <span class="hlt">reflective</span> solar bands (VIS, NTR, and SWIR) ranging from 0.41 to 2.1 micron. The sun illuminates the solar diffuser either directly or through a attenuation screen. The attenuation screen consists of a regular array of pin holes. The attenuated illumination pattern on the solar diffuser is not uniform, but consists of a multitude of pin-hole images of the sun. This non-uniform illumination produces small, but noticeable radiometric effects. A description of the computer model used to simulate the effects of the attenuation screen is given and the predictions of the model are compared with actual, on-orbit, calibration measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980018319','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980018319"><span id="translatedtitle">Land Surface Temperature Measurements from EOS <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wan, Zhengming</p> <p>1997-01-01</p> <p>We made modifications to the linear kernel bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) models from Roujean et al. and Wanner et al. that extend the spectral range into the thermal infrared (TIR). With these TIR BRDF models and the IGBP land-cover product, we developed a classification-based emissivity database for the EOS/<span class="hlt">MODIS</span> land-surface temperature (LST) algorithm and used it in version V2.0 of the <span class="hlt">MODIS</span> LST code. Two V2.0 LST codes have been delivered to the <span class="hlt">MODIS</span> SDST, one for the daily L2 and L3 LST products, and another for the 8-day 1km L3 LST product. New TIR thermometers (broadband radiometer with a filter in the 10-13 micron window) and an IR camera have been purchased in order to reduce the uncertainty in LST field measurements due to the temporal and spatial variations in LST. New improvements have been made to the existing TIR spectrometer in order to increase its accuracy to 0.2 C that will be required in the vicarious calibration of the <span class="hlt">MODIS</span> TIR bands.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1616014H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1616014H"><span id="translatedtitle">Aerosol radiative effects over global arid and semi-arid regions based on <span class="hlt">MODIS</span> Deep Blue satellite observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hatzianastassiou, Nikolaos; Papadimas, Christos D.; Gkikas, Antonis; Matsoukas, Christos; Sayer, Andrew M.; Hsu, N. Christina; Vardavas, Ilias</p> <p>2014-05-01</p> <p>Aerosols are a key parameter for several atmospheric processes related to weather and climate of our planet. Specifically, the aerosol impact on Earth's climate is exerted and quantified through their radiative effects, which are induced by their direct, indirect and semi-direct interactions with radiation, in particular at short wavelengths (solar). It is acknowledged that the uncertainty of present and future climate assessments is mainly associated with aerosols and that a better understanding of their physico-chemical, optical and radiative effects is needed. The contribution of satellites to this aim is important as a complementary tool to climate and radiative transfer models, as well as to surface measurements, since space observations of aerosol properties offer an extended spatial coverage. However, such satellite based aerosol properties and associated model radiation computations have suffered from unavailability over highly <span class="hlt">reflecting</span> surfaces, namely polar and desert areas. This is also the case for <span class="hlt">MODIS</span> which, onboard the Terra and <span class="hlt">Aqua</span> satellites, has been providing high quality aerosol data since 2000 and 2002, respectively. These data, more specifically the aerosol optical depth (AOD) which is the most important optical property used in radiative and climate models, are considered to be of best quality. In order to address this problem, the <span class="hlt">MODIS</span> Deep Blue (DB) algorithm has been developed which enables the retrieval of AOD above arid and semi-arid areas of the globe, including the major deserts. In the present study we make use of the FORTH detailed spectral radiative transfer model (RTM) with <span class="hlt">MODIS</span> DB AOD data, supplemented with single scattering albedo (SSA) and asymmetry parameter (AP) aerosol data from the Global Aerosol DataSet (GADS) to estimate the aerosol DREs over the arid and semi-arid regions of the globe. The RTM is run using surface and atmospheric data from the ISCCP-D2 dataset and the NCEP global reanalysis project and computes the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013042','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013042"><span id="translatedtitle">The Collection 6 'dark-target' <span class="hlt">MODIS</span> Aerosol Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Levy, Robert C.; Mattoo, Shana; Munchak, Leigh A.; Kleidman, Richard G.; Patadia, Falguni; Gupta, Pawan; Remer, Lorraine</p> <p>2013-01-01</p> <p>Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on both Terra and <span class="hlt">Aqua</span>, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the <span class="hlt">MODIS</span> data as a benchmark. In order to keep up with the needs of AEROCOM and other <span class="hlt">MODIS</span> data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001609&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bland%2Bsurface%2Btemperature','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001609&hterms=modis+land+surface+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bland%2Bsurface%2Btemperature"><span id="translatedtitle">First Complete Day from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>This spectacular, full-color image of the Earth is a composite of the first full day of data gathered by the Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard NASA's Terra spacecraft. <span class="hlt">MODIS</span> collected the data for each wavelength of red, green, and blue light as Terra passed over the daylit side of the Earth on April 19, 2000. Terra is orbiting close enough to the Earth so that it cannot quite see the entire surface in a day, resulting in the narrow gaps around the equator. Although the sensor's visible channels were combined to form this true-color picture, <span class="hlt">MODIS</span> collects data in a total of 36 wavelengths, ranging from visible to thermal infrared energy. Scientists use these data to measure regional and global-scale changes in marine and land-based plant life, sea and land surface temperatures, cloud properties, aerosols, fires, and land surface properties. Notice how cloudy the Earth is, and the large differences in brightness between clouds, deserts, oceans, and forests. The Antarctic, surrounded by clockwise swirls of cloud, is shrouded in darkness because the sun is north of the equator at this time of year. The tropical forests of Africa, Southeast Asia, and South America are shrouded by clouds. The bright Sahara and Arabian deserts stand out clearly. Green vegetation is apparent in the southeast United States, the Yucatan Peninsula, and Madagascar. Image by Mark Gray, <span class="hlt">MODIS</span> Atmosphere Team, NASA GSFC</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040081254','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040081254"><span id="translatedtitle">Application of Polarization to the <span class="hlt">MODIS</span> Aerosol Retrieval Over Land</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Levy, Robert C.; Remer, Lorraine R.; Kaufman, Yoram J.</p> <p>2004-01-01</p> <p><span class="hlt">Reflectance</span> measurements in the visible and infrared wavelengths, from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), are used to derive aerosol optical thicknesses (AOT) and aerosol properties over land surfaces. The measured spectral <span class="hlt">reflectance</span> is compared with lookup tables, containing theoretical <span class="hlt">reflectance</span> calculated by radiative transfer (RT) code. Specifically, this RT code calculates top of the atmosphere (TOA) intensities based on a scalar treatment of radiation, neglecting the effects of polarization. In the red and near infrared (NIR) wavelengths the use of the scalar RT code is of sufficient accuracy to model TOA <span class="hlt">reflectance</span>. However, in the blue, molecular and aerosol scattering dominate the TOA signal. Here, polarization effects can be large, and should be included in the lookup table derivation. Using a RT code that allows for both vector and scalar calculations, we examine the <span class="hlt">reflectance</span> differences at the TOA, with and without polarization. We find that the differences in blue channel TOA <span class="hlt">reflectance</span> (vector - scalar) may reach values of 0.01 or greater, depending on the sun/surface/sensor scattering geometry. <span class="hlt">Reflectance</span> errors of this magnitude translate to AOT differences of 0.1, which is a very large error, especially when the actual AOT is low. As a result of this study, the next version of aerosol retrieval from <span class="hlt">MODIS</span> over land will include polarization.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ESASP.707E..30V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ESASP.707E..30V"><span id="translatedtitle">Analysing <span class="hlt">MODIS</span> Phenometrics Quality on Cropped Land in West Africa</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vintrou, Elodie; Begue, Agnes; Baron, Christian; Lo Seen, Danny; Alexandre, Saad; Traore, Seydou</p> <p>2012-04-01</p> <p>Crop phenology is essential information when evaluating crop production in the food insecure regions of West Africa. The only currently available global product that includes phenological variables is the <span class="hlt">MODIS</span> Land Cover Dynamics Yearly (MCD12Q2) product. This product is produced each year at 500 m spatial resolution, from the 8-day vegetation index EVI (Enhanced Vegetation Index) calculated from the NBAR <span class="hlt">reflectance</span> (Nadir Bidirectional <span class="hlt">Reflectance</span> Distribution Function - Adjusted <span class="hlt">Reflectance</span>). In order to analyze the information content of <span class="hlt">MODIS</span> MCD12Q2 product, the phenological variables were extracted for areas previously identified as cropped on eight specific sites in Mali and compared to rainfall data and expert knowledge on Malian agriculture. <span class="hlt">MODIS</span> MCD12Q2 data analysis showed that only 70% of the cropped pixels in Southern Mali had a complete phenology information on the whole vegetation cycle (four phenometrics values), and that a large part of the pixels displayed unrealistic late Start-Of-Season (SOS) values. A close analysis of the original EVI data indicated that these inconsistent SOS values were due to missing EVI data during the vegetation development phase (due to the presence of cloud cover) conducting to a false detection of SOS. We then proposed a simple way to correct the SOS values. In Africa, food security systems could benefit from such a phenology product, by utilizing its spatially continuous information in agro-meteorological modeling, and thus improving agricultural production estimation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002SPIE.4483..203T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002SPIE.4483..203T"><span id="translatedtitle">Radiometric calibration of <span class="hlt">MODIS</span> with reference to Landsat-7 ETM+</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thome, Kurtis J.; Whittington, Emily E.; Smith, Noel</p> <p>2002-01-01</p> <p>The Remote Sensing Group at the University of Arizona has used ground-based test sites for the vicarious calibration of airborne and satellite-based sensors. Past work has focused on high-spatial-resolution sensors that are well- suited to the <span class="hlt">reflectance</span>-, irradiance-, and radiance-based methods. Application of these methods to the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) with its lower spatial resolution pose a challenge for vicarious calibraiton. This work presents a cross-calibration approach using the high spatial resolution sensor Enhanced Thematic Mapper Plus (TEM+) on the Landat-7 platform that allows the <span class="hlt">reflectance</span>-based results of ETM+ to be scaled to the larger footprint of <span class="hlt">MODIS</span>. This calibration takes into account the changes in solar zenith angle due to the 40- minute separation in overpass times of the two sensors which view the test sites on the same day with the same view angle. Also included are corrections due to the spectral differences between the sensors. Early results show that <span class="hlt">MODIS</span> and ETM+ agree to better than 5% in the solar <span class="hlt">reflective</span> for bands not affected by atmospheric absorption.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612018L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612018L"><span id="translatedtitle">Comparison of Landsat and <span class="hlt">MODIS</span> for assessing surface properties of snow and ice</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lhermitte, Stef; Van Lipzig, Nicole P. M.</p> <p>2014-05-01</p> <p>Assessment of the spatio-temporal variations in snow and ice properties provides valuable input for a variety of climatological, hydrological, glaciological applications ranging from energy and mass budget calculations to distributed snowmelt modelling. Within this context a variety of retrieval methods has been developed to assess surface properties from multi-spectral Landsat and <span class="hlt">MODIS</span> data. These methods range from spectral index calculations and unmixing methods to combined remote sensing and radiative transfer approaches. This study provides a quantitative analysis of the trade-offs between the state-of-the-art retrieval methodologies applied on Landsat and <span class="hlt">MODIS</span> data. Within this context, spatio-temporal patterns of surface properties (e.g., snow cover fraction, albedo, grain size, impurity load, ponding melt water, snow/ice classification) are derived from Landsat and <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> data over two study areas covering parts of the Greenland Ice Sheet and the Chilean Andes from 2000 to present. The retrieved properties are subsequently compared and validated based on reference in-situ measurements. Analysis of the differences in derived surface properties from Landsat and <span class="hlt">MODIS</span> reveals the importance of understanding the spatial and temporal scales at which variations occur. Large spatial variability within a <span class="hlt">MODIS</span> pixel complicates the performance of retrieval methods for <span class="hlt">MODIS</span> time series, especially for surface properties not related to snow cover fractions. Large temporal variability, on the other hand, constrains the validity of time series of Landsat retrievals and also has a large impact on the use of multi-day composite <span class="hlt">MODIS</span> data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713613K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713613K"><span id="translatedtitle">Monitoring the state of vegetation in Hungary using 15 years long <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kern, Anikó; Bognár, Péter; Pásztor, Szilárd; Barcza, Zoltán; Timár, Gábor; Lichtenberger, János; Ferencz, Csaba</p> <p>2015-04-01</p> <p>Monitoring the state and health of the vegetation is essential to understand causes and severity of environmental change and to prepare for the negative effects of climate change on plant growth and productivity. Satellite remote sensing is the fundamental tool to monitor and study the changes of vegetation activity in general and to understand its relationship with the climate fluctuations. Vegetation indices and other vegetation related measures calculated from remotely sensed data are widely used to monitor and characterize the state of the terrestrial vegetation. Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are among the most popular indices that can be calculated from measurements of the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor onboard the NASA EOS-AM1/Terra and EOS-PM1/<span class="hlt">Aqua</span> satellites (since 1999 and 2002 respectively). Based on the available, 15 years long <span class="hlt">MODIS</span> data (2000-2014) the vegetation characteristics of Hungary was investigated in our research, primarily using vegetation indices. The <span class="hlt">MODIS</span> NDVI and EVI (both part of the so-called MOD13 product of NASA) are freely available with a finest spatial resolution of 250 meters and a temporal resolution of 16 days since 2000/2002 (for Terra and <span class="hlt">Aqua</span> respectively). The accuracy, the spatial resolution and temporal continuity of the <span class="hlt">MODIS</span> products makes these datasets highly valuable despite of its relatively short temporal coverage. NDVI is also calculated routinely from the raw <span class="hlt">MODIS</span> data collected by the receiving station of Eötvös Loránd University. In order to characterize vegetation activity and its variability within the Carpathian Basin the area-averaged annual cycles and their interannual variability were determined. The main aim was to find those years that can be considered as extreme according to specific indices. Using archive meteorological data the effects of extreme weather on vegetation activity and growth were investigated with</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010SPIE.7807E..0HC','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010SPIE.7807E..0HC"><span id="translatedtitle">Study of instrument temperature effect on <span class="hlt">MODIS</span> thermal emissive band responses</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, Tiejun; Xiong, Xiaoxiong</p> <p>2010-09-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) has 16 thermal emissive bands (TEB) over a spectral range from mid-wave infrared (MWIR) to long-wave infrared (LWIR), using photovoltaic (PV) HgCdTe detectors for bands 20-25 and 27-30 with wavelengths from 3.75μm to 9.73μm and photoconductive (PC) HgCdTe detectors for bands 31-36 with wavelengths from 11.0μm to 14.2μm. A total of 160 individual detectors, 10 per band, are distributed on the short- and mid-wave (SMIR) and LWIR cold focal-plane assemblies (CFPA) with temperature controlled at 83K. The instrument temperature affects the detector response and this effect varies with the detector type. Detector responses from on-orbit calibration and pre-launch measurements have been examined to characterize this effect. Results from this analysis show that, for the PV detectors on the SMIR CFPA, the detector responses (gains) increase with instrument temperature whereas the PC detector responses decrease with the instrument temperature. The calibration impact due to on-orbit changes in instrument temperatures is examined. On-orbit detector offset and nonlinear response characterization obtained from the on-boar blackbody (BB) warm-up and cool-down (WUCD) cycle is discussed. This investigation was performed for both Terra <span class="hlt">MODIS</span> and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050156904','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050156904"><span id="translatedtitle">Crop Surveillance Demonstration Using a Near-Daily <span class="hlt">MODIS</span> Derived Vegetation Index Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don</p> <p>2005-01-01</p> <p>Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument flown on the Terra and <span class="hlt">Aqua</span> satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily <span class="hlt">MODIS</span> imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI <span class="hlt">MODIS</span> products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A32C..04W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A32C..04W"><span id="translatedtitle">Validation of AIRS Cloud Cleared Radiances Using <span class="hlt">MODIS</span> and its Affect on QualityControl</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wilson, R. C.; Schreier, M. M.</p> <p>2015-12-01</p> <p>The Atmospheric Infrared Sounder (AIRS) was launched aboard the <span class="hlt">AQUA</span> satellite to provide measurements of temperature, humidity, and various trace gases in support of climate research and weather prediction. Only clear sky measurements of the outgoing radiance are used in the AIRS physical retrieval of temperature, water vapor, and certain trace gases. To overcome cloud contamination the clear sky radiance is estimated using an iterative procedure that combines an initial estimate of the clear state from a neural network along with a three by three grid of AIRS measurements. The radiance error estimate, a component critical to the AIRS physical retrieval, must include contributions from all assumed parameters input to the forward model on top of instrument noise and amplification from cloud clearing. When the error estimate is too large the AIRS physical retrieval becomes over-constrained to the first guess profile. Therefore quantifying the cloud cleared error estimate is essential to an effective physical retrieval. We will validate the cloud-cleared radiances through the use of nearby clear ocean scenes and with comparisons to clear pixels from the Moderate Resolution Imaging Spectro-radiometer (<span class="hlt">MODIS</span>). AIRS cloud cleared radiances are spectrally convolved to <span class="hlt">MODIS</span> channels for this comparison. This analysis quantifies error due to cloud-clearing and demonstrates that clear <span class="hlt">MODIS</span> pixels can be used with the standard AIRS quality control procedure to improve identification poor retrievals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030025758','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030025758"><span id="translatedtitle">Cloud and Aerosol Properties, Precipitable Water, and Profiles of Temperature and Water Vapor from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Menzel, W. Paul; Kaufman, Yoram J.; Tanre, Didier; Gao, Bo-Cai; Platnick, Steven; Ackerman, Steven A.; Remer, Lorraine A.; Pincus, Robert; Hubanks, Paul A.</p> <p>2003-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is an earth-viewing sensor that flies on the Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellites, launched in 1999 and 2002, respectively. <span class="hlt">MODIS</span> scans a swath width of 2330 km that is sufficiently wide to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km. <span class="hlt">MODIS</span> provides images in 36 spectral bands between 0.415 and 14.235 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to en- able advanced studies of land, ocean, and atmospheric properties. Twenty-six bands are used to derive atmospheric properties such as cloud mask, atmospheric profiles, aerosol properties, total precipitable water, and cloud properties. In this paper we describe each of these atmospheric data products, including characteristics of each of these products such as file size, spatial resolution used in producing the product, and data availability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.G21A0746Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.G21A0746Y"><span id="translatedtitle">Global Characterization of Tropospheric Noise for InSAR Analysis Using <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yun, S.; Hensley, S.; Chaubell, M.; Fielding, E. J.; Pan, L.; Rosen, P. A.</p> <p>2013-12-01</p> <p>Radio wave's differential phase delay variation through the troposphere is one of the largest error sources in Interferometric Synthetic Aperture Radar (InSAR) measurements, and water vapor variability in the troposphere is known to be the dominant factor. We use the precipitable water vapor products from NASA's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors mounted on Terra and <span class="hlt">Aqua</span> satellites to produce tropospheric noise maps of InSAR. Then we extract a small set of characteristic parameters of its power spectral density curve and 1-D covariance function, and calculate the structure function to estimate the expected tropospheric noise level as a function of distance. The results serve two purposes: 1) to provide guidance on the expected covariance matrix for geophysical modeling, 2) to provide quantitative basis of the measurement requirements for the planned US L-band SAR mission. We build over a decade span (2000-2013) of a lookup table of the parameters derived from 2-by-2 degree tiles at 1-by-1 degree posting of global coverage, representing 10 days of each season in each year. The <span class="hlt">MODIS</span> data were retrieved from OSCAR (Online Services for Correcting Atmosphere in Radar) server. <span class="hlt">MODIS</span> images with 5 percent or more cloud cover were discarded. Cloud mask and sensor scanning artifacts were removed with interpolation and spectral filtering, respectively. We also mitigate topography dependent stratified tropospheric delay variation using the European Centre for Medium-Range Weather Forecasts (ECMWF) and Shuttle Radar Topography Mission Digital Elevation Models (SRTM DEMs).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008SPIE.7152E..0PK','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008SPIE.7152E..0PK"><span id="translatedtitle">Detection of dust and sandstorms from Taklamakan Desert to Japan by using <span class="hlt">MODIS</span> mosaic images</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kato, Yoshinobu</p> <p>2008-12-01</p> <p>In recent years, the number of days which dust and sandstorms (DSS) events were observed is increasing in Japan, Korea, China and Mongolia. The Aerosol Vapor Index (AVI) method is a DSS detection method. The AVI is defined as AVI=Tb32-Tb31 for <span class="hlt">MODIS</span> data of Terra and <span class="hlt">Aqua</span> satellites, where Tb31 is the brightness temperature of band 31 (10.780-11.280μm) and Tb32 is that of band 32 (11.770-12.270μm). The <span class="hlt">MODIS</span> mosaic images of true-color, AVI and thermal images are made for the detection of DSS from Taklamakan Desert to Japan. The detection of DSS is possible both at daytime and night, because the AVI method is used. The density of DSS is classified into six levels from 0 (DSS none) to 5 (DSS strong) according to the AVI values. The DSS phenomena during 6-11 April 2006 are analyzed by using the mosaic images of Terra-<span class="hlt">MODIS</span>. The number of pixels, which is approximately equal to the area of square kilometers, at each level of DSS density is measured. The AVI value at sea is about 0.2-2.3K lower than that at land, because of the influence of water vapor. In daytime, the generation place of DSS hidden under the cloud can be estimated by comparing AVI image with true-color and thermal images.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080014145','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080014145"><span id="translatedtitle">Integrated Cloud-Aerosol-Radiation Product using CERES, <span class="hlt">MODIS</span>, CALIPSO and CloudSat Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave</p> <p>2007-01-01</p> <p>This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the <span class="hlt">Aqua</span> Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-<span class="hlt">MODIS</span> analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3- dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-<span class="hlt">MODIS</span> global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013035','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013035"><span id="translatedtitle">Validation and Uncertainty Estimates for <span class="hlt">MODIS</span> Collection 6 "Deep Blue" Aerosol Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.</p> <p>2013-01-01</p> <p>The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of <span class="hlt">MODIS</span> products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other satellite AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AtmEn.141..186X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AtmEn.141..186X"><span id="translatedtitle">On the influence of the diurnal variations of aerosol content to estimate direct aerosol radiative forcing using <span class="hlt">MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Hui; Guo, Jianping; Ceamanos, Xavier; Roujean, Jean-Louis; Min, Min; Carrer, Dominique</p> <p>2016-09-01</p> <p>Long-term measurements of aerosol optical depth (AOD) from the Aerosol Robotic Network (AERONET) located in Beijing reveal a strong diurnal cycle of aerosol load staged by seasonal patterns. Such pronounced variability is matter of importance in respect to the estimation of daily averaged direct aerosol radiative forcing (DARF). Polar-orbiting satellites could only offer a daily revisit, which turns in fact to be even much less in case of frequent cloudiness. Indeed, this places a severe limit to properly capture the diurnal variations of AOD and thus estimate daily DARF. Bearing this in mind, the objective of the present study is however to evaluate the impact of AOD diurnal variations for conducting quantitative assessment of DARF using Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) AOD data over Beijing. We provide assessments of DARF with two different assumptions about diurnal AOD variability: taking the observed hourly-averaged AOD cycle into account and assuming constant <span class="hlt">MODIS</span> (including Terra and <span class="hlt">Aqua</span>) AOD value throughout the daytime. Due to the AOD diurnal variability, the absolute differences in annual daily mean DARFs, if the constant <span class="hlt">MODIS</span>/Terra (<span class="hlt">MODIS/Aqua</span>) AOD value is used instead of accounting for the observed hourly-averaged daily variability, is 1.2 (1.3) Wm-2 at the top of the atmosphere, 27.5 (30.6) Wm-2 at the surface, and 26.4 (29.3) Wm-2 in the atmosphere, respectively. During the summertime, the impact of the diurnal AOD variability on seasonal daily mean DARF estimates using <span class="hlt">MODIS</span> Terra (<span class="hlt">Aqua</span>) data can reach up to 2.2 (3.9) Wm-2 at the top of the atmosphere, 43.7 (72.7) Wm-2 at the surface, and 41.4 (68.8) Wm-2 in the atmosphere, respectively. Overall, the diurnal variation in AOD tends to cause large bias in the estimated DARF on both seasonal and annual scales. In summertime, the higher the surface albedo, the stronger impact on DARF at the top of the atmosphere caused by dust and biomass burning (continental) aerosol. This</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUSM.A33C..08H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUSM.A33C..08H"><span id="translatedtitle">Satellite Monitoring of Urban Air Pollution using <span class="hlt">MODIS</span> and VIIRS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hsu, N. C.; Bettenhausen, C.; Sayer, A. M.</p> <p>2013-05-01</p> <p>Due to rapid economical growth in many developing countries, the problem of deteriorating air quality is becoming an important societal issue of public health over mega cities around the world. Although there are many networks of surface PM2.5 and PM10 measurements in place to monitor the level of air pollutant over these urban sites, satellite data are still required to provide comprehensive information on the overall big picture regarding the spatial distribution of aerosols and their transport paths into the surrounding regions. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-<span class="hlt">reflecting</span> surfaces such as urban areas. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface <span class="hlt">reflectance</span>. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as <span class="hlt">MODIS</span> and VIIRS to infer the properties of aerosols, since the surface <span class="hlt">reflectance</span> over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness from both <span class="hlt">MODIS</span> Collection 6 and new VIIRS Deep Blue products with data from AERONET sunphotometers over urban sites. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from <span class="hlt">MODIS</span> and VIIRS instruments. The multiyear satellite measurements since 2000 from <span class="hlt">MODIS</span> will be utilized to investigate the interannual variability of source, pathway, and aerosol loading associated with these urban pollutions. The quantitative effects of direct radiative forcing of these air borne aerosol</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://files.eric.ed.gov/fulltext/ED460942.pdf','ERIC'); return false;" href="http://files.eric.ed.gov/fulltext/ED460942.pdf"><span id="translatedtitle"><span class="hlt">Aqua</span>SMART: Water & Boating Safety, Grades 3-5. Teacher's Guide.</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Texas State Dept. of Parks and Wildlife, Austin.</p> <p></p> <p>This teacher's guide accompanies a program designed to teach water and boating safety to students in grades 3-5. The written curriculum accompanies a video, <span class="hlt">Aqua</span>SMART 3-5. The theme of the curriculum is <span class="hlt">Aqua</span>SMART. To become <span class="hlt">Aqua</span>SMART, students must learn 10 basic lessons for water and boating safety. The written curriculum begins with an overview…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://files.eric.ed.gov/fulltext/ED460941.pdf','ERIC'); return false;" href="http://files.eric.ed.gov/fulltext/ED460941.pdf"><span id="translatedtitle"><span class="hlt">Aqua</span>SMART: Water & Boating Safety, Grades K-2. Teacher's Guide.</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Texas State Dept. of Parks and Wildlife, Austin.</p> <p></p> <p>This teacher's guide accompanies a program designed to teach water and boating safety to students in grades K-2. The written curriculum accompanies a video, <span class="hlt">Aqua</span>SMART K-2. The theme of the curriculum is <span class="hlt">Aqua</span>SMART. To become <span class="hlt">Aqua</span>SMART, students must learn 10 basic lessons for water and boating safety. The teacher's guide begins with an overview of…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=19920047064&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dspectrometer%2Bresolution','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=19920047064&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dspectrometer%2Bresolution"><span id="translatedtitle">Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Kaufman, Yoram J.; Menzel, W. Paul; Tanre, Didier D.</p> <p>1992-01-01</p> <p>The authors describe the status of <span class="hlt">MODIS</span>-N and its companion instrument <span class="hlt">MODIS</span>-T (tilt), a tiltable cross-track scanning spectrometer with 32 uniformly spaced channels between 0.410 and 0.875 micron. They review the various methods being developed for the remote sensing of atmospheric properties using <span class="hlt">MODIS</span>, placing primary emphasis on the principal atmospheric applications of determining the optical, microphysical, and physical properties of clouds and aerosol particles from spectral <span class="hlt">reflection</span> and thermal emission measurements. In addition to cloud and aerosol properties, <span class="hlt">MODIS</span>-N will be used for determining the total precipitable water vapor and atmospheric stability. The physical principles behind the determination of each of these atmospheric products are described, together with an example of their application to aircraft and/or satellite measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC23L1260Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC23L1260Z"><span id="translatedtitle">Air Temperature Estimation over the Third Pole Using <span class="hlt">MODIS</span> LST</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, H.; Zhang, F.; Ye, M.; Che, T.</p> <p>2015-12-01</p> <p>The Third Pole is centered on the Tibetan Plateau (TP), which is the highest large plateau around the world with extremely complex terrain and climate conditions, resulting in very scarce meteorological stations especially in the vast west region. For these unobserved areas, the remotely sensed land surface temperature (LST) can greatly contribute to air temperature estimation. In our research we utilized the <span class="hlt">MODIS</span> LST production from both TERRA and <span class="hlt">AQUA</span> to estimate daily mean air temperature over the TP using multiple statistical models. Other variables used in the models include longitudes, latitudes, Julian day, solar zenith, NDVI and elevation. To select a relatively optimal model, we chose six popular and representative statistical models as candidate models including the multiple linear regression (MLR), the partial least squares regression (PLS), back propagate neural network (BPNN), support vector regression (SVR), random forests (RF) and Cubist regression (CR). The performances of the six models were compared for each possible combination of LSTs at four satellite pass times and two quality situations. Eventually a ranking table consisting of optimal models for each LST combination and quality situation was built up based on the validation results. By this means, the final production is generated providing daily mean air temperature with the least cloud blockage and acceptable accuracy. The average RMSEs of cross validation are mostly around 2℃. Stratified validations were also performed to test the expansibility to unobserved and high-altitude areas of the final models selected.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020070202&hterms=System+offset&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSystem%2Boffset','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020070202&hterms=System+offset&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSystem%2Boffset"><span id="translatedtitle">An Overview of the Earth Observing System <span class="hlt">MODIS</span> Instrument Performance, Data Systems Performance, and Data Products Status and Availability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, Vincent V.</p> <p>2002-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. Now, approximately 2 years from that time, the instrument is operating well. All subsystems of the instrument are performing as expected, the signal-to-noise (S/N) performance meets or exceeds specifications, band-to-band registration meets specifications, geodetic registration of observations is nearing 50 meters (one sigma) and the spectral bands are located where they were intended to be pre-launch and attendant gains and offsets are stable to date. The data systems have performed well and are producing a wide variety of data products useful for scientific and applications studies in relatively consistent fashion extending from November 2000 to the present. Within the approximately 40 <span class="hlt">MODIS</span> data products, several are new and represent powerful and exciting capabilities. The remainder of the <span class="hlt">MODIS</span> products exceed or, at a minimum, match the capabilities of products from heritage sensors such as, for example, the Advanced Very High Resolution Radiometer (AVHRR). Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAAC's) or through Direct Broadcast (DB) stations. The <span class="hlt">MODIS</span> instrument on the EOS <span class="hlt">Aqua</span> mission should also be expected to be in orbit and functioning in the Spring of 2002.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015SPIE.9607E..0KP&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015SPIE.9607E..0KP&link_type=ABSTRACT"><span id="translatedtitle">Improving AIRS radiance spectra in high contrast scenes using <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pagano, Thomas S.; Aumann, Hartmut H.; Manning, Evan M.; Elliott, Denis A.; Broberg, Steven E.</p> <p>2015-09-01</p> <p>The Atmospheric Infrared Sounder (AIRS) on the EOS <span class="hlt">Aqua</span> Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 um with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS is designed to measure temperature and water vapor profiles for improvement in weather forecast accuracy and improved understanding of climate processes. As with most instruments, the AIRS Point Spread Functions (PSFs) are not the same for all detectors. When viewing a non-uniform scene, this causes a significant radiometric error in some channels that is scene dependent and cannot be removed without knowledge of the underlying scene. The magnitude of the error depends on the combination of non-uniformity of the AIRS spatial response for a given channel and the non-uniformity of the scene, but is typically only noticeable in about 1% of the scenes and about 10% of the channels. The current solution is to avoid those channels when performing geophysical retrievals. In this effort we use data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument to provide information on the scene uniformity that is used to correct the AIRS data. For the vast majority of channels and footprints the technique works extremely well when compared to a Principal Component (PC) reconstruction of the AIRS channels. In some cases where the scene has high inhomogeneity in an irregular pattern, and in some channels, the method can actually degrade the spectrum. Most of the degraded channels appear to be slightly affected by random noise introduced in the process, but those with larger degradation may be affected by alignment errors in the AIRS relative to <span class="hlt">MODIS</span> or uncertainties in the PSF. Despite these errors, the methodology shows the ability to correct AIRS radiances in non-uniform scenes under some of the worst case conditions and improves the ability to match</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN11B1279W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN11B1279W"><span id="translatedtitle"><span class="hlt">MODIS</span> Near real-time (NRT) data for fire applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wong, M.; Davies, D.; Ilavajhala, S.; Molinario, G.; Justice, C.; Latham, J.; Martucci, A.; Murphy, K. J.</p> <p>2011-12-01</p> <p>This paper describes the lessons learned from the development of the Fire Information for Resource Management System (FIRMS) prototype and its transition to an operational system, the Global Fire Information Management System (GFIMS), at the United Nations Food and Agriculture Organization (FAO) in August 2010. These systems provide active fire data from the <span class="hlt">MODIS</span> sensor, on board NASA's Terra and <span class="hlt">Aqua</span> Earth Observing Satellites, to users at no cost, in near-real time and in easy-to-use formats. The FIRMS prototype evolved from simply providing daily active fire text files via FTP, to include services such as providing fire data in various data formats, an interactive WebGIS allowing users to view and query the data and an email alert service enabling users to receive emails of near real-time fire data of their chosen area of interest. FIRMS was designed to remove obstacles to the uptake and use of fire data by addressing issues often associated with satellite data: cost, timeliness of delivery, limited data formats and the need for technical expertise to process and analyze the data. We also illustrate how the <span class="hlt">MODIS</span> active fire data are routinely used for firefighting and conservation monitoring. We present results from a user survey, completed by approximately 345 people from 65 countries, and provide case studies highlighting how the provision of <span class="hlt">MODIS</span> active fire data have made an impact on conservation and firefighting, especially in remote areas where it is difficult to have on-the-ground surveillance. We highlight the gaps in current capabilities, both with users and the data. A major obstacle still for some users is having low or no internet connectivity and a possible solution is through the use of cell phone technologies such as SMS text messaging of fire locations and information. GFIMS, and its precursor, FIRMS, were developed by the University of Maryland with funding from NASA's Applied Sciences Program. With GFIMS established at FAO as an operational</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160011558','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160011558"><span id="translatedtitle">EOS <span class="hlt">Aqua</span>: Mission Status at Earth Science Constellation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Guit, Bill</p> <p>2016-01-01</p> <p>This is an EOS <span class="hlt">Aqua</span> Mission Status presentation to be given at the MOWG meeting in Albuquerque NM. The topics to discus are: mission summary, spacecraft subsystems summary, recent and planned activities, inclination adjust maneuvers, propellant usage and lifetime estimate, and mission summary.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160011149','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160011149"><span id="translatedtitle">The Calibration of the DSCOVR EPIC Multiple Visible Channel Instrument Using <span class="hlt">MODIS</span> and VIIRS as a Reference</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Haney, Conor; Doeling, David; Minnis, Patrick; Bhatt, Rajendra; Scarino, Benjamin; Gopalan, Arun</p> <p>2016-01-01</p> <p>The Deep Space Climate Observatory (DSCOVR), launched on 11 February 2015, is a satellite positioned near the Lagrange-1 (L1) point, carrying several instruments that monitor space weather, and Earth-view sensors designed for climate studies. The Earth Polychromatic Imaging Camera (EPIC) onboard DSCOVR continuously views the sun-illuminated portion of the Earth with spectral coverage in the UV, VIS, and NIR bands. Although the EPIC instrument does not have any onboard calibration abilities, its constant view of the sunlit Earth disk provides a unique opportunity for simultaneous viewing with several other satellite instruments. This arrangement allows the EPIC sensor to be inter-calibrated using other well-characterized satellite instrument reference standards. Two such instruments with onboard calibration are <span class="hlt">MODIS</span>, flown on <span class="hlt">Aqua</span> and Terra, and VIIRS, onboard Suomi-NPP. The <span class="hlt">MODIS</span> and VIIRS reference calibrations will be transferred to the EPIC instrument using both all-sky ocean and deep convective clouds (DCC) ray-matched EPIC and <span class="hlt">MODIS</span>/VIIRS radiance pairs. An automated navigation correction routine was developed to more accurately align the EPIC and <span class="hlt">MODIS</span>/VIIRS granules. The automated navigation correction routine dramatically reduced the uncertainty of the resulting calibration gain based on the EPIC and <span class="hlt">MODIS</span>/VIIRS radiance pairs. The SCIAMACHY-based spectral band adjustment factors (SBAF) applied to the <span class="hlt">MODIS</span>/ VIIRS radiances were found to successfully adjust the reference radiances to the spectral response of the specific EPIC channel for over-lapping spectral channels. The SBAF was also found to be effective for the non-overlapping EPIC channel 10. Lastly, both ray-matching techniques found no discernable trends for EPIC channel 7 over the year of publically released EPIC data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18542490','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18542490"><span id="translatedtitle">Depolarization ratio and attenuated backscatter for nine cloud types: analyses based on collocated CALIPSO lidar and <span class="hlt">MODIS</span> measurements.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cho, Hyoun-Myoung; Yang, Ping; Kattawar, George W; Nasiri, Shaima L; Hu, Yongxiang; Minnis, Patrick; Trepte, Charles; Winker, David</p> <p>2008-03-17</p> <p>This paper reports on the relationship between lidar backscatter and the corresponding depolarization ratio for nine types of cloud systems. The data used in this study are the lidar returns measured by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite and the collocated cloud products derived from the observations made by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard <span class="hlt">Aqua</span> satellite. Specifically, the operational <span class="hlt">MODIS</span> cloud optical thickness and cloud-top pressure products are used to classify cloud types on the basis of the International Satellite Cloud Climatology Project (ISCCP) cloud classification scheme. While the CALIPSO observations provide information for up to 10 cloud layers, in the present study only the uppermost clouds are considered. The layer-averaged attenuated backscatter (gamma') and layer-averaged depolarization ratio (delta) from the CALIPSO measurements show both water- and ice-phase features for global cirrus, cirrostratus, and deep convective cloud classes. Furthermore, we screen both the <span class="hlt">MODIS</span> and CALIPSO data to eliminate cases in which CALIPSO detected two- or multi-layered clouds. It is shown that low gamma' values corresponding to uppermost thin clouds are largely eliminated in the CALIPSO delta-gamma' relationship for single-layered clouds. For mid-latitude and polar regions corresponding, respectively, to latitude belts 30 degrees -60 degrees and 60 degrees -90 degrees in both the hemispheres, a mixture of water and ice is also observed in the case of the altostratus class. <span class="hlt">MODIS</span> cloud phase flags are also used to screen ice clouds. The resultant water clouds flagged by the <span class="hlt">MODIS</span> algorithm show only water phase feature in the delta-gamma' relation observed by CALIOP; however, in the case of the ice clouds flagged by the <span class="hlt">MODIS</span> algorithm, the co-existence of ice- and water-phase clouds is still observed in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/18542490','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/18542490"><span id="translatedtitle">Depolarization ratio and attenuated backscatter for nine cloud types: analyses based on collocated CALIPSO lidar and <span class="hlt">MODIS</span> measurements.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cho, Hyoun-Myoung; Yang, Ping; Kattawar, George W; Nasiri, Shaima L; Hu, Yongxiang; Minnis, Patrick; Trepte, Charles; Winker, David</p> <p>2008-03-17</p> <p>This paper reports on the relationship between lidar backscatter and the corresponding depolarization ratio for nine types of cloud systems. The data used in this study are the lidar returns measured by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite and the collocated cloud products derived from the observations made by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard <span class="hlt">Aqua</span> satellite. Specifically, the operational <span class="hlt">MODIS</span> cloud optical thickness and cloud-top pressure products are used to classify cloud types on the basis of the International Satellite Cloud Climatology Project (ISCCP) cloud classification scheme. While the CALIPSO observations provide information for up to 10 cloud layers, in the present study only the uppermost clouds are considered. The layer-averaged attenuated backscatter (gamma') and layer-averaged depolarization ratio (delta) from the CALIPSO measurements show both water- and ice-phase features for global cirrus, cirrostratus, and deep convective cloud classes. Furthermore, we screen both the <span class="hlt">MODIS</span> and CALIPSO data to eliminate cases in which CALIPSO detected two- or multi-layered clouds. It is shown that low gamma' values corresponding to uppermost thin clouds are largely eliminated in the CALIPSO delta-gamma' relationship for single-layered clouds. For mid-latitude and polar regions corresponding, respectively, to latitude belts 30 degrees -60 degrees and 60 degrees -90 degrees in both the hemispheres, a mixture of water and ice is also observed in the case of the altostratus class. <span class="hlt">MODIS</span> cloud phase flags are also used to screen ice clouds. The resultant water clouds flagged by the <span class="hlt">MODIS</span> algorithm show only water phase feature in the delta-gamma' relation observed by CALIOP; however, in the case of the ice clouds flagged by the <span class="hlt">MODIS</span> algorithm, the co-existence of ice- and water-phase clouds is still observed in</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010119957','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010119957"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span> Aerosol Optical Depth Retrieval Over Land</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chu, D. A.; Kaufman, Y. J.; Ichoku, C.; Remer, L. A.; Tanre, D.; Holben, B. N.; Einaudi, Franco (Technical Monitor)</p> <p>2001-01-01</p> <p>Aerosol optical depths are derived operationally for the first time over land in the visible wavelengths by <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) onboard the EOSTerra spacecraft. More than 300 Sun photometer data points from more than 30 AERONET (Aerosol Robotic Network) sites globally were used in validating the aerosol optical depths obtained during July - September 2000. Excellent agreement is found with retrieval errors within (Delta)tau=+/- 0.05 +/- 0.20 tau, as predicted, over (partially) vegetated surfaces, consistent with pre-launch theoretical analysis and aircraft field experiments. In coastal and semi-arid regions larger errors are caused predominantly by the uncertainty in evaluating the surface <span class="hlt">reflectance</span>. The excellent fit was achieved despite the ongoing improvements in instrument characterization and calibration. This results show that <span class="hlt">MODIS</span>-derived aerosol optical depths can be used quantitatively in many applications with cautions for residual clouds, snow/ice, and water contamination.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020008210','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020008210"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span> Aerosol Retrieval Over Ocean</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Mattoo, Shana; Levy, Robert; Chu, D. Allen; Holben, Brent N.; Dubovik, Oleg; Ahmad, Ziauddin; Einaudi, Franco (Technical Monitor)</p> <p>2001-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) algorithm for determining aerosol characteristics over ocean is performing with remarkable accuracy. A two-month data set of <span class="hlt">MODIS</span> retrievals co-located with observations from the AErosol RObotic NETwork (AERONET) ground-based sunphotometer network provides the necessary validation. Spectral radiation measured by <span class="hlt">MODIS</span> (in the range 550 - 2100 nm) is used to retrieve the aerosol optical thickness, effective particle radius and ratio between the submicron and micron size particles. <span class="hlt">MODIS</span>-retrieved aerosol optical thickness at 660 nm and 870 nm fall within the expected uncertainty, with the ensemble average at 660 nm differing by only 2% from the AERONET observations and having virtually no offset. <span class="hlt">MODIS</span> retrievals of aerosol effective radius agree with AERONET retrievals to within +/- 0.10 micrometers, while <span class="hlt">MODIS</span>-derived ratios between large and small mode aerosol show definite correlation with ratios derived from AERONET data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000114847','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000114847"><span id="translatedtitle">Pre-Launch Algorithm and Data Format for the Level 1 Calibration Products for the EOS AM-1 Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Guenther, Bruce W.; Godden, Gerald D.; Xiong, Xiao-Xiong; Knight, Edward J.; Qiu, Shi-Yue; Montgomery, Harry; Hopkins, M. M.; Khayat, Mohammad G.; Hao, Zhi-Dong; Smith, David E. (Technical Monitor)</p> <p>2000-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) radiometric calibration product is described for the thermal emissive and the <span class="hlt">reflective</span> solar bands. Specific sensor design characteristics are identified to assist in understanding how the calibration algorithm software product is designed. The <span class="hlt">reflected</span> solar band software products of radiance and <span class="hlt">reflectance</span> factor both are described. The product file format is summarized and the <span class="hlt">MODIS</span> Characterization Support Team (MCST) Homepage location for the current file format is provided.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A21C0131H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A21C0131H"><span id="translatedtitle">New Global Deep Blue Aerosol Product over Land and Ocean from VIIRS, and Its comparisons with <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hsu, N. Y. C.; Bettenhausen, C.; Sayer, A. M.; Lee, J.; Tsay, S. C.; Carletta, N.</p> <p>2015-12-01</p> <p>The impacts of natural and anthropogenic sources of air pollution on climate and human health have continued to gain attention from the scientific community. In order to facilitate these effects, high quality consistent long-term global aerosol data records from satellites are essential. Several EOS-era instruments (e.g., SeaWiFS, <span class="hlt">MODIS</span>, and MISR) are able to provide such information with a high degree of fidelity. However, with the aging <span class="hlt">MODIS</span> sensors and the launch of the VIIRS instrument on Suomi NPP in late 2011, the continuation of long-term aerosol data records suitable for climate studies from <span class="hlt">MODIS</span> to VIIRS is needed urgently. VIIRS was designed to have similar capabilities to <span class="hlt">MODIS</span>, with similar visible/infrared spectral channels, and spatial/ temporal resolution. However, small but significant differences in several key channels used in aerosol retrievals between <span class="hlt">MODIS</span> and VIIRS mean that significant effort is required to revise aerosol models and surface <span class="hlt">reflectance</span> determination modules previously developed using <span class="hlt">MODIS</span> data. In this study, we will show the global (land and ocean) distribution of aerosols from Version 1 of the VIIRS Deep Blue data set. The preliminary validation results of these new VIIRS Deep Blue aerosol products using data from AERONET sunphotometers over land and ocean will be discussed. We will also compare the monthly averaged Deep Blue aerosol optical thickness (AOT) from VIIRS with the <span class="hlt">MODIS</span> C6 products to investigate if any systematic biases may exist between <span class="hlt">MODIS</span> C6 and VIIRS AOT.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011703','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011703"><span id="translatedtitle">Comparative Analysis of Aerosol Retrievals from <span class="hlt">MODIS</span>, OMI and MISR Over Sahara Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Wang, Y.; Hsu, C.; Terres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.</p> <p>2011-01-01</p> <p><span class="hlt">MODIS</span> is a wide field-of-view sensor providing daily global observations of the Earth. Currently, global <span class="hlt">MODIS</span> aerosol retrievals over land are performed with the main Dark Target algorithm complimented with the Deep Blue (DB) Algorithm over bright deserts. The Dark Target algorithm relies on surface parameterization which relates <span class="hlt">reflectance</span> in <span class="hlt">MODIS</span> visible bands with the 2.1 micrometer region, whereas the Deep Blue algorithm uses an ancillary angular distribution model of surface <span class="hlt">reflectance</span> developed from the time series of clear-sky <span class="hlt">MODIS</span> observations. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been developed for <span class="hlt">MODIS</span>. MAIAC uses a time series and an image based processing to perform simultaneous retrievals of aerosol properties and surface bidirectional <span class="hlt">reflectance</span>. It is a generic algorithm which works over both dark vegetative surfaces and bright deserts and performs retrievals at 1 km resolution. In this work, we will provide a comparative analysis of DB, MAIAC, MISR and OMI aerosol products over bright deserts of northern Africa.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040075015&hterms=Ecosystem&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DEcosystem','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040075015&hterms=Ecosystem&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DEcosystem"><span id="translatedtitle">Use of <span class="hlt">MODIS</span>-Derived Fire Radiative Energy to Estimate Smoke Aerosol Emissions over Different Ecosystems</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Kaufman, Yoram J.</p> <p>2003-01-01</p> <p>Biomass burning is the main source of smoke aerosols and certain trace gases in the atmosphere. However, estimates of the rates of biomass consumption and emission of aerosols and trace gases from fires have not attained adequate reliability thus far. Traditional methods for deriving emission rates employ the use of emission factors e(sub x), (in g of species x per kg of biomass burned), which are difficult to measure from satellites. In this era of environmental monitoring from space, fire characterization was not a major consideration in the design of the early satellite-borne remote sensing instruments, such as AVHRR. Therefore, although they are able to provide fire location information, they were not adequately sensitive to variations in fire strength or size, because their thermal bands used for fire detection saturated at the lower end of fire radiative temperature range. As such, hitherto, satellite-based emission estimates employ proxy techniques using satellite derived fire pixel counts (which do not express the fire strength or rate of biomass consumption) or burned areas (which can only be obtained after the fire is over). The <span class="hlt">MODIS</span> sensor, recently launched into orbit aboard EOS Terra (1999) and <span class="hlt">Aqua</span> (2002) satellites, have a much higher saturation level and can, not only detect the fire locations 4 times daily, but also measures the at-satellite fire radiative energy (which is a measure of the fire strength) based on its 4 micron channel temperature. Also, <span class="hlt">MODIS</span> measures the optical thickness of smoke and other aerosols. Preliminary analysis shows appreciable correlation between the <span class="hlt">MODIS</span>-derived rates of emission of fire radiative energy and smoke over different regions across the globe. These relationships hold great promise for deriving emission coefficients, which can be used for estimating smoke aerosol emissions from <span class="hlt">MODIS</span> active fire products. This procedure has the potential to provide more accurate emission estimates in near real</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/23792258','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/23792258"><span id="translatedtitle">Zebrafish locomotor capacity and brain acetylcholinesterase activity is altered by Aphanizomenon flos-<span class="hlt">aquae</span> DC-1 aphantoxins.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, De Lu; Hu, Chun Xiang; Li, Dun Hai; Liu, Yong Ding</p> <p>2013-08-15</p> <p>Aphanizomenon flos-<span class="hlt">aquae</span> (A. flos-<span class="hlt">aquae</span>) is a source of neurotoxins known as aphantoxins or paralytic shellfish poisons (PSPs) that present a major threat to the environment and to human health. Generally, altered neurological function is <span class="hlt">reflected</span> in behavior. Although the molecular mechanism of action of PSPs is well known, its neurobehavioral effects on adult zebrafish and its relationship with altered neurological functions are poorly understood. Aphantoxins purified from a natural isolate of A. flos-<span class="hlt">aquae</span> DC-1 were analyzed by HPLC. The major analogs found in the toxins were the gonyautoxins 1 and 5 (GTX1 and GTX5; 34.04% and 21.28%, respectively) and the neosaxitoxin (neoSTX, 12.77%). Zebrafish (Danio rerio) were intraperitoneally injected with 5.3 and 7.61 μg STXeq/kg (low and high dose, respectively) of A. flos-<span class="hlt">aquae</span> DC-1 aphantoxins. The swimming activity was investigated by observation combined with video at 6 timepoints from 1 to 24 h post-exposure. Both aphantoxin doses were associated with delayed touch responses, reduced head-tail locomotory abilities, inflexible turning of head, and a tailward-shifted center of gravity. The normal S-pattern (or undulating) locomotor trajectory was replaced by a mechanical motor pattern of swinging the head after wagging the tail. Finally, these fish principally distributed at the top and/or bottom water of the aquarium, and showed a clear polarized distribution pattern at 12 h post-exposure. Further analysis of neurological function demonstrated that both aphantoxin doses inhibited brain acetylcholinesterase activity. All these changes were dose- and time-dependent. These results demonstrate that aphantoxins can alter locomotor capacity, touch responses and distribution patterns by damaging the cholinergic system of zebrafish, and suggest that zebrafish locomotor behavior and acetylcholinesterase can be used as indicators for investigating aphantoxins and blooms in nature. PMID:23792258</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012EGUGA..14.4855M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012EGUGA..14.4855M&link_type=ABSTRACT"><span id="translatedtitle">The effect of land cover heterogeneity of <span class="hlt">MODIS</span> pixel on canopy LAI estimation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manninen, T.; Puttonen, N.</p> <p>2012-04-01</p> <p>The boreal zone land cover has a very significant influence on the northern hemisphere albedo and is an important component of the northern hemisphere carbon budget. Both albedo and the leaf area index (LAI) are one of the most important biophysical vegetation parameters and belong to the Essential Climate Variables (ECV) . In addition, in winter time the boreal forest albedo is a complicated combination of snow and canopy radiative properties, so that the albedo is a function of the canopy LAI. One possibility to estimate LAI using optical satellite data is by determination of spectral vegetation indices (SVIs), such as the reduced simple ratio (RSR). It uses the visible near infrared and short wave infrared channels. In large areas moderate resolution instruments, like <span class="hlt">MODIS</span>, are suitable for LAI mapping. Yet, the heterogeneity of land cover in many boreal areas, for example in Finland, causes a challenge for LAI estimation. This effect was studied using several Landsat and <span class="hlt">MODIS</span> images and the high resolution CORINE land cover map covering the same area in various parts of Finland. The atmospheric correction of the Landsat images was adjusted so that each <span class="hlt">MODIS</span> pixel <span class="hlt">reflectance</span> matched the average of the Landsat pixel <span class="hlt">reflectances</span> within the <span class="hlt">MODIS</span> pixel. The LAI values for Landsat and <span class="hlt">MODIS</span> images were then determined using the RSR index. The LAI average of forested Landsat pixels was compared to the corresponding <span class="hlt">MODIS</span> pixel LAI as a function of open water area fraction in the <span class="hlt">MODIS</span> pixel. A regression function was determined to derive a method to correct the <span class="hlt">MODIS</span> based LAI values with the open water area fraction. It turned out that the existence of open water in the <span class="hlt">MODIS</span> pixels reduces the determined canopy LAI value on the average 30%. Also other land cover classes affect the LAI value, but the effect of water is largest, because the <span class="hlt">reflectance</span> of water deviates so much from that of the canopy. The canopy LAI map of whole Finland was then calculated</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AMT.....9..973T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AMT.....9..973T"><span id="translatedtitle">Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated <span class="hlt">MODIS</span> and CALIOP data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip T.; Cronk, Heather Q.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert Y.; Fisher, Brenden; Osterman, Gregory B.; Pollock, Randy H.; Crisp, David; Eldering, Annmarie; Gunson, Michael R.</p> <p>2016-03-01</p> <p>The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of <span class="hlt">reflected</span> sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>), aboard the <span class="hlt">Aqua</span> platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of ≃ 20-25 % of all OCO-2 soundings</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMTD....812663T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMTD....812663T"><span id="translatedtitle">Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms; validation against collocated <span class="hlt">MODIS</span> and CALIOP data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Taylor, T. E.; O'Dell, C. W.; Frankenberg, C.; Partain, P.; Cronk, H. Q.; Savtchenko, A.; Nelson, R. R.; Rosenthal, E. J.; Chang, A. Y.; Fisher, B.; Osterman, G.; Pollock, R. H.; Crisp, D.; Eldering, A.; Gunson, M. R.</p> <p>2015-12-01</p> <p>The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of <span class="hlt">reflected</span> sunlight in the near-infrared. These estimates can be biased by clouds and aerosols within the instrument's field of view (FOV). Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 μm O2 A-band, neglecting scattering by clouds and aerosols, which introduce photon path-length (PPL) differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 μm (weak CO2 band) and 2.06 μm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which key off of different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>), aboard the <span class="hlt">Aqua</span> platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning to allow throughputs of ≃ 30 %, agreement between the OCO-2 and <span class="hlt">MODIS</span> cloud screening methods is found to be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412485D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412485D"><span id="translatedtitle">Using <span class="hlt">MODIS</span> imagery to assign dates to maps of burn scars in Portugal</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>DaCamara, C. C.; Libonati, R.; Barros, A.; Gaspar, G.; Calado, T. J.</p> <p>2012-04-01</p> <p>In the European context, Portugal presents the highest number of fire occurrences and has the largest area affected by wildfires. Like other southern regions of Europe, Portugal has experienced a dramatic increase in fire incidence during the last few decades that has been attributed to modifications in land-use as well as to climatic changes and associated occurrence of weather extremes. Wildfire activity also presents a large inter-annual variability that has been related to changes in the frequency of occurrence of atmospheric conditions favorable to the onset and spreading of large-fires. Since 1990, the Portuguese Authority for Forests (AFN) has been producing yearly maps of fire perimeters under a protocol with the Department of Forest Engineering of the Institute of Agronomy (DEF/ISA). The AFN fire atlas uses end of fire season Landsat TM/ETM imagery to map all fire perimeters with area larger than 5ha. Because it relies on end-of-season imagery, the atlas provides a spatial snapshot of the yearly area burned, and dates of burn for individual events cannot be estimated. Such information is nevertheless crucial to understand the fire regime and fire seasonality and to disentangle the complex interactions among fire, land cover and meteorology. The aim of the present work is to develop an automated procedure that allows using time series of moderate resolution imagery, such as the one provided by the <span class="hlt">MODIS</span> instrument on-board TERRA and <span class="hlt">AQUA</span>, to assign dates of burning to scars larger than 500 ha in the Landsat based fire atlas. The procedure relies on the so-called (V,W) burned index that uses daily <span class="hlt">reflectance</span> obtained from the 1km <span class="hlt">MODIS</span> Level 1B calibrated radiance from bands 2 (NIR) and 20 (MIR). The algorithm detects persistent changes in the (V,W) burned index time series, within each Landsat burned scar. The day of maximum change is then identified by means of a discrimination index, together with thresholds from the (V,W) time series. A spatial filter</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016FrES...10...38M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016FrES...10...38M"><span id="translatedtitle">Air temperature field distribution estimations over a Chinese mega-city using <span class="hlt">MODIS</span> land surface temperature data: the case of Shanghai</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ma, Weichun; Zhou, Liguo; Zhang, Hao; Zhang, Yan; Dai, Xiaoyan</p> <p>2016-03-01</p> <p>The capability of obtaining spatially distributed air temperature data from remote sensing measurements is an improvement for many environmental applications focused on urban heat island, carbon emissions, climate change, etc. This paper is based on the <span class="hlt">MODIS</span>/Terra and <span class="hlt">Aqua</span> data utilized to study the effect of the urban atmospheric heat island in Shanghai, China. The correlation between retrieved <span class="hlt">MODIS</span> land surface temperature (LST) and air temperature measured at local weather stations was initially studied at different temporal and spatial scales. Secondly, the air temperature data with spatial resolutions of 250 m and 1 km were estimated from <span class="hlt">MODIS</span> LST data and in-situ measured air temperature. The results showed that there is a slightly higher correlation between air temperature and <span class="hlt">MODIS</span> LST at a 250m resolution in spring and autumn on an annual scale than observed at a 1 km resolution. Although the distribution pattern of the air temperature thermal field varies in different seasons, the urban heat island (UHI) in Shanghai is characterized by a distribution pattern of multiple centers, with the central urban area as the primary center and the built-up regions in each district as the subcenters. This study demonstrates the potential not only for estimating the distribution of the air temperature thermal field from <span class="hlt">MODIS</span> LST with 250 m resolution in spring and autumn in Shanghai, but also for providing scientific and effective methods for monitoring and studying UHI effect in a Chinese mega-city such as Shanghai.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23365013','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23365013"><span id="translatedtitle">Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal <span class="hlt">MODIS</span> data.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen</p> <p>2013-02-01</p> <p>The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and <span class="hlt">Aqua</span> moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on <span class="hlt">MODIS</span> land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from <span class="hlt">MODIS</span>-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, <span class="hlt">MODIS</span>-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only <span class="hlt">MODIS</span> data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3566407','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3566407"><span id="translatedtitle">Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal <span class="hlt">MODIS</span> data*</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen</p> <p>2013-01-01</p> <p>The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T a estimation from Terra and <span class="hlt">Aqua</span> moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T a based on <span class="hlt">MODIS</span> land surface temperature (LST) data. The verification results of maximum T a, minimum T a, GDD, and AGDD from <span class="hlt">MODIS</span>-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, <span class="hlt">MODIS</span>-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001–2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only <span class="hlt">MODIS</span> data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale. PMID:23365013</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/23365013','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/23365013"><span id="translatedtitle">Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal <span class="hlt">MODIS</span> data.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen</p> <p>2013-02-01</p> <p>The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and <span class="hlt">Aqua</span> moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on <span class="hlt">MODIS</span> land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from <span class="hlt">MODIS</span>-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, <span class="hlt">MODIS</span>-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only <span class="hlt">MODIS</span> data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale. PMID:23365013</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22399955','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22399955"><span id="translatedtitle">Discrepancy Between ASTER- and <span class="hlt">MODIS</span>- Derived Land Surface Temperatures: Terrain Effects.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Yuanbo; Noumi, Yousuke; Yamaguchi, Yasushi</p> <p>2009-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the Advanced Spaceborne Thermal Emission <span class="hlt">Reflection</span> Radiometer (ASTER) are onboard the same satellite platform NASA TERRA. Both <span class="hlt">MODIS</span> and ASTER offer routine retrieval of land surface temperatures (LSTs), and the ASTER- and <span class="hlt">MODIS</span>-retrieved LST products have been used worldwide. Because a large fraction of the earth surface consists of mountainous areas, variations in elevation, terrain slope and aspect angles can cause biases in the retrieved LSTs. However, terrain-induced effects are generally neglected in most satellite retrievals, which may generate discrepancy between ASTER and <span class="hlt">MODIS</span> LSTs. In this paper, we reported the terrain effects on the LST discrepancy with a case examination over a relief area at the Loess Plateau of China. Results showed that the terrain-induced effects were not major, but nevertheless important for the total LST discrepancy. A large local slope did not necessarily lead to a large LST discrepancy. The angle of emitted radiance was more important than the angle of local slope in generating the LST discrepancy. Specifically, the conventional terrain correction may be unsuitable for densely vegetated areas. The distribution of ASTER-to-<span class="hlt">MODIS</span> emissivity suggested that the terrain correction was included in the generalized split window (GSW) based approach used to rectify <span class="hlt">MODIS</span> LSTs. Further study should include the classification-induced uncertainty in emissivity for reliable use of satellite-retrieved LSTs over relief areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/22399955','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/22399955"><span id="translatedtitle">Discrepancy Between ASTER- and <span class="hlt">MODIS</span>- Derived Land Surface Temperatures: Terrain Effects.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Yuanbo; Noumi, Yousuke; Yamaguchi, Yasushi</p> <p>2009-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the Advanced Spaceborne Thermal Emission <span class="hlt">Reflection</span> Radiometer (ASTER) are onboard the same satellite platform NASA TERRA. Both <span class="hlt">MODIS</span> and ASTER offer routine retrieval of land surface temperatures (LSTs), and the ASTER- and <span class="hlt">MODIS</span>-retrieved LST products have been used worldwide. Because a large fraction of the earth surface consists of mountainous areas, variations in elevation, terrain slope and aspect angles can cause biases in the retrieved LSTs. However, terrain-induced effects are generally neglected in most satellite retrievals, which may generate discrepancy between ASTER and <span class="hlt">MODIS</span> LSTs. In this paper, we reported the terrain effects on the LST discrepancy with a case examination over a relief area at the Loess Plateau of China. Results showed that the terrain-induced effects were not major, but nevertheless important for the total LST discrepancy. A large local slope did not necessarily lead to a large LST discrepancy. The angle of emitted radiance was more important than the angle of local slope in generating the LST discrepancy. Specifically, the conventional terrain correction may be unsuitable for densely vegetated areas. The distribution of ASTER-to-<span class="hlt">MODIS</span> emissivity suggested that the terrain correction was included in the generalized split window (GSW) based approach used to rectify <span class="hlt">MODIS</span> LSTs. Further study should include the classification-induced uncertainty in emissivity for reliable use of satellite-retrieved LSTs over relief areas. PMID:22399955</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090043024','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090043024"><span id="translatedtitle">The Transition of High-Resolution NASA <span class="hlt">MODIS</span> Sea Surface Temperatures into the WRF Environmental Modeling System</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.</p> <p>2009-01-01</p> <p>The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution <span class="hlt">MODIS</span> SSTs, SPoRT developed the composite product consisting of <span class="hlt">MODIS</span> SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the <span class="hlt">MODIS</span> SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. <span class="hlt">MODIS</span> composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA <span class="hlt">Aqua</span> and Terra polar orbiting satellites. The <span class="hlt">MODIS</span> SST product is output in gridded binary-1 (GRIB-1) data</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ThApC.tmp..247D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ThApC.tmp..247D"><span id="translatedtitle">Estimation of daily minimum land surface air temperature using <span class="hlt">MODIS</span> data in southern Iran</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza</p> <p>2016-10-01</p> <p>Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) onboard <span class="hlt">Aqua</span> and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference (RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons (RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.C51B0386H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.C51B0386H"><span id="translatedtitle">Enhancing a RADARSAT/ICESat Digital Elevation Model of West Antarctica Using <span class="hlt">MODIS</span> Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Haran, T. M.; Scambos, T. A.</p> <p>2007-12-01</p> <p>An image enhancement approach is used to develop a new digital elevation map of West Antarctica, combining multiple <span class="hlt">MODIS</span> images and both radar altimetry and ICESat laser altimetry Digital Elevation Model (DEM) data. The method combines the wide image coverage of <span class="hlt">MODIS</span>, and its high radiometric sensitivity (which equates to high sunward slope sensitivity), with the high precision and accuracy of ICESat and combined ICESat and radar altimetry DEMs. We calibrate brightness-to-slope relationships for several <span class="hlt">MODIS</span> images of the central West Antarctic using smoothed DEMs derived from both sources. Using the calibrations, we then created, first, a slope map of the ice sheet surface from the image data (regressing slope information from many images), and then integrated this absolute slope map to yield complete DEMs for the region. ICESat (as of September 2007) has acquired a series of eleven near-repeat tracks over the Antarctic during the period September 2003 to April 2007, covering the continent to 86 deg S. ICESat data are acquired as a series of spot elevations, averaging a ~60m diameter surface region every ~172m. However, ICESat track paths have spacings wide enough (2 km at 85 deg; 20 - 50 km at 75 deg) that some surface ice dynamical features (e.g. flowlines, undulations, ice rises) are missed by the track data used to construct the ICESat DEM. Radar altimetry can provide some of the missing data north of 81.5 deg, but only to a maximum resolution of about 5 km. A set of cloud-cleared <span class="hlt">MODIS</span> band 1 data from both the <span class="hlt">Aqua</span> and Terra platforms acquired during the 2003-2004 austral summer, used in generating the Mosaic of Antarctica, MOA, surface morphology image map, were used for the image enhancement. Past analyses of the slope-brightness relationship for <span class="hlt">MODIS</span> have shown ice surface slope precisions of +/- 0.00015. ICESat spot elevations have nominal precisions of ~5 cm under ideal conditions, although thin-cloud effects and mislocation errors can magnify these</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A14C..02H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A14C..02H"><span id="translatedtitle">Extending <span class="hlt">MODIS</span> Cloud Top and Infrared Phase Climate Records with VIIRS and CrIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heidinger, A. K.; Platnick, S. E.; Ackerman, S. A.; Holz, R.; Meyer, K.; Frey, R.; Wind, G.; Li, Y.; Botambekov, D.</p> <p>2015-12-01</p> <p>The <span class="hlt">MODIS</span> imagers on the NASA EOS Terra and <span class="hlt">Aqua</span> satellites have generated accurate and well-used cloud climate data records for 15 years. Both missions are expected to continue until the end of this decade and perhaps beyond. The Visible and Infrared Imaging Radiometer Suite (VIIRS) imagers on the Suomi-NPP (SNPP) mission (launched in October 2011) and future NOAA Joint Polar Satellite System (JPSS) platforms are the successors for imager-based cloud climate records from polar orbiting satellites after <span class="hlt">MODIS</span>. To ensure product continuity across a broad suite of EOS products, NASA has funded a SNPP science team to develop EOS-like algorithms that can be use with SNPP and JPSS observations, including two teams to work on cloud products. Cloud data record continuity between <span class="hlt">MODIS</span> and VIIRS is particularly challenging due to the lack of VIIRS CO2-slicing channels, which reduces information content for cloud detection and cloud-top property products, as well as down-stream cloud optical products that rely on both. Here we report on our approach to providing continuity specifically for the <span class="hlt">MODIS</span>/VIIRS cloud-top and infrared-derived thermodynamic phase products by combining elements of the NASA <span class="hlt">MODIS</span> science team (MOD) and the NOAA Algorithm Working Group (AWG) algorithms. The combined approach is referred to as the MODAWG processing package. In collaboration with the NASA Atmospheric SIPS located at the University of Wisconsin Space Science and Engineering Center, the MODAWG code has been exercised on one year of SNPP VIIRS data. In addition to cloud-top and phase, MODAWG provides a full suite of cloud products that are physically consistent with <span class="hlt">MODIS</span> and have a similar data format. Further, the SIPS has developed tools to allow use of Cross-track Infrared Sounder (CrIS) observations in the MODAWG processing that can ameliorate the loss of the CO2 absorption channels on VIIRS. Examples will be given that demonstrate the positive impact that the CrIS data can provide</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008655','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008655"><span id="translatedtitle">A Real-Time <span class="hlt">MODIS</span> Vegetation Composite for Land Surface Models and Short-Term Forecasting</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.</p> <p>2011-01-01</p> <p>The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor aboard the polar orbiting NASA <span class="hlt">Aqua</span> and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the <span class="hlt">MODIS</span> NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the <span class="hlt">MODIS</span> real-time GVF data. This presentation will describe the methodology used to develop the 1-km <span class="hlt">MODIS</span> NDVI composites and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/27409547','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/27409547"><span id="translatedtitle">Heart Rate and Energy Expenditure During <span class="hlt">Aqua</span> Dynamics.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Vickery, S R; Cureton, K J; Langstaff, J L</p> <p>1983-03-01</p> <p>In brief: The heart rate, oxygen uptake, and energy expenditure of three young women were measured during 20-minute low-gear, 30-minute middle-gear, and 60-minute high-gear <span class="hlt">aqua</span> dynamics workouts. All three workouts were moderate in intensity, eliciting average heart rates of 132 to 143 beats min(-1) (70% to 77% HR max), average oxygen uptakes of 1.2 to 1.3 liters min(-1) (51% to 57% VO2 max), and average energy expenditures of 5.9 to 6.5 kcals min(-1) The findings indicate that <span class="hlt">aqua</span> dynamics could be a beneficial conditioning program for people who have relatively low physical work capacity and enjoy swimming but cannot conveniently engage in lap swimming. PMID:27409547</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812228M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812228M"><span id="translatedtitle">Optical properties of aerosol contaminated cloud derived from <span class="hlt">MODIS</span> instrument</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mei, Linlu; Rozanov, Vladimir; Lelli, Luca; Vountas, Marco; Burrows, John P.</p> <p>2016-04-01</p> <p>The presence of absorbing aerosols above/within cloud can reduce the amount of up-welling radiation in visible (VIS) and short-wave infrared and darken the spectral <span class="hlt">reflectance</span> when compared with a spectrum of a clean cloud observed by satellite instruments (Jethva et al., 2013). Cloud properties retrieval for aerosol contaminated cases is a great challenge. Even small additional injection of aerosol particles into clouds in the cleanest regions of Earth's atmosphere will cause significant effect on those clouds and on climate forcing (Koren et al., 2014; Rosenfeld et al., 2014) because the micro-physical cloud process are non-linear with respect to the aerosol loading. The current cloud products like Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) ignoring the aerosol effect for the retrieval, which may cause significant error in the satellite-derived cloud properties. In this paper, a new cloud properties retrieval method, considering aerosol effect, based on the weighting-function (WF) method, is presented. The retrieval results shows that the WF retrieved cloud properties (e.g COT) agrees quite well with <span class="hlt">MODIS</span> COT product for relative clear atmosphere (AOT ≤ 0.4) while there is a large difference for large aerosol loading. The <span class="hlt">MODIS</span> COT product is underestimated for at least 2 - 3 times for AOT>0.4, and this underestimation increases with the increase of AOT.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1221490','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1221490"><span id="translatedtitle"><span class="hlt">Aqua</span>-vanadyl ion interaction with Nafion® membranes</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Vijayakumar, Murugesan; Govind, Niranjan; Li, Bin; Wei, Xiaoliang; Nie, Zimin; Thevuthasan, Suntharampillai; Sprenkle, Vince L.; Wang, Wei</p> <p>2015-03-23</p> <p>Lack of comprehensive understanding about the interactions between Nafion membrane and battery electrolytes prevents the straightforward tailoring of optimal materials for redox flow battery applications. In this work, we analyzed the interaction between <span class="hlt">aqua</span>-vanadyl cation and sulfonic sites within the pores of Nafion membranes using combined theoretical and experimental X-ray spectroscopic methods. Molecular level interactions, namely, solvent share and contact pair mechanisms are discussed based on Vanadium and Sulfur K-edge spectroscopic analysis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMNH51E1944S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMNH51E1944S"><span id="translatedtitle">Characterizing 13 Years of Surface Water Variability from <span class="hlt">MODIS</span>-based Near Real-Time Flood Mapping Products in the Indus River, Tonle Sap Lake, and Lake Chad.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Slayback, D. A.; Brakenridge, G. R.; Policelli, F. S.</p> <p>2015-12-01</p> <p>Driven by an increase in extreme weather events in a warming world, flooding appears to be increasing in many regions. Since 2012, we have been using the twice-daily near-global observations of the two <span class="hlt">MODIS</span> instruments to operate a near real-time flood mapping capability. Primarily intended to support disaster response efforts, our system generates daily near-global maps of flood water extent, at 250 m resolution. Although cloud cover is a challenge, the twice-daily coverage from the Terra and <span class="hlt">Aqua</span> satellites helps to capture most major events. We use the MOD44W product (the "<span class="hlt">MODIS</span> 250-m land-water mask") to differentiate "normal" water from flood water. Products from the system are freely available, and used by disaster response agencies and academic and industry researchers. An open question, however, is: how "normal" are recently observed floods? Destructive and — as reported by the press — record floods seem to be occurring more and more frequently. With the <span class="hlt">MODIS</span> archive going back to 1999 (Terra satellite) and 2002 (<span class="hlt">Aqua</span> satellite), we now have more than a decade of twice-daily near-global observations to begin answering this question. Although the 13 years of available twice-daily data (2002-2015) are not sufficient to fully characterize surface water normals (e.g., 100-year floods), we can start examining recent trends in surface water extent and flood frequency. To do so, we have back-processed our surface water product through mid-2002 (<span class="hlt">Aqua</span> launch) for a few regions, and have used this to evaluate the variability in surface water extent and flood frequency. These results will eventually feed back into an improved characterization of flood water in our near real-time flood product. Here we will present results on trends in surface water extent and flood frequency for a few regions, including the Indus in Pakistan, the Tonle Sap lake in Cambodia, and lake Chad in Africa.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A21C0141D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A21C0141D"><span id="translatedtitle">Vegetation Continuous Fields--Transitioning from <span class="hlt">MODIS</span> to VIIRS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>DiMiceli, C.; Townshend, J. R.; Sohlberg, R. A.; Kim, D. H.; Kelly, M.</p> <p>2015-12-01</p> <p>Measurements of fractional vegetation cover are critical for accurate and consistent monitoring of global deforestation rates. They also provide important parameters for land surface, climate and carbon models and vital background data for research into fire, hydrological and ecosystem processes. <span class="hlt">MODIS</span> Vegetation Continuous Fields (VCF) products provide four complementary layers of fractional cover: tree cover, non-tree vegetation, bare ground, and surface water. <span class="hlt">MODIS</span> VCF products are currently produced globally and annually at 250m resolution for 2000 to the present. Additionally, annual VCF products at 1/20° resolution derived from AVHRR and <span class="hlt">MODIS</span> Long-Term Data Records are in development to provide Earth System Data Records of fractional vegetation cover for 1982 to the present. In order to provide continuity of these valuable products, we are extending the VCF algorithms to create Suomi NPP/VIIRS VCF products. This presentation will highlight the first VIIRS fractional cover product: global percent tree cover at 1 km resolution. To create this product, phenological and physiological metrics were derived from each complete year of VIIRS 8-day surface <span class="hlt">reflectance</span> products. A supervised regression tree method was applied to the metrics, using training derived from Landsat data supplemented by high-resolution data from Ikonos, RapidEye and QuickBird. The regression tree model was then applied globally to produce fractional tree cover. In our presentation we will detail our methods for creating the VIIRS VCF product. We will compare the new VIIRS VCF product to our current <span class="hlt">MODIS</span> VCF products and demonstrate continuity between instruments. Finally, we will outline future VIIRS VCF development plans.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70156397','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70156397"><span id="translatedtitle">Land cover mapping of Greater Mesoamerica using <span class="hlt">MODIS</span> data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Giri, Chandra; Jenkins, Clinton N.</p> <p>2005-01-01</p> <p>A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>, 500 m resolution) satellite data. Daily surface <span class="hlt">reflectance</span> <span class="hlt">MODIS</span> data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of <span class="hlt">MODIS</span>- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, <span class="hlt">MODIS</span> 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSM.A51A..03S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSM.A51A..03S"><span id="translatedtitle">A basin-wide assessment of the GOES and <span class="hlt">MODIS</span> active fire products for the Brazilian Amazon</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schroeder, W.; Csiszar, I.; Prins, E.; Schmidt, C.; Setzer, A.; Longo, K.; Freitas, S.; Morisette, J.; Brunner, J.</p> <p>2007-05-01</p> <p>This LBE-ECO Phase III study is designed to assess the performance of active fire products which have been used to delineate the fire dynamics in the Brazilian Amazon basin and which are routinely used to feed biomass burning emissions models for the region. The initial analyses are focused primarily on the creation of a validated long term (1995-present) record for the WF-ABBA active fire product using GOES East geostationary satellite data. Active fire masks were produced for 285 ASTER and ETM+ scenes distributed across the Brazilian Amazon representing our ground truth for the validation of the WF-ABBA. For comparison purposes we also included the <span class="hlt">MODIS</span>/Terra "Thermal Anomalies" (MOD14) data in our analyses. Approximately 14,500 fire pixels were analyzed for the GOES data and 7,300 fire pixels were analyzed for the <span class="hlt">MODIS</span> data. We found that at the 50% detection probability mark (p<0.001), the GOES fire product requires four times more active fire area than it is necessary for <span class="hlt">MODIS</span> to achieve the same probability of detection. However, the higher observation frequency of GOES resulted in less than 40% omission error compared to 80% with <span class="hlt">MODIS</span>. Basin-wide commission errors for <span class="hlt">MODIS</span> and GOES were approximately 15 and 17%, respectively. Commission errors were higher over areas of active deforestation due to the high thermal contrast between the deforested sites and the adjacent green forests which can cause multiple false detections. Burnt area estimates were also produced based on ETM+ data to assess the average burnt area size associated with the coarse resolution active fire data above. For this application over 2,700 burn scar polygons were digitized representing all major biomass burning regions across the Brazilian Amazon. Burn scar polygons were then intersected with the <span class="hlt">MODIS</span>/Terra and <span class="hlt">Aqua</span> active fire data. 50% of all polygons containing active fires in the <span class="hlt">MODIS</span> imagery showed a burnt area size larger than 300ha. Burnt areas of less than 100ha in size</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.5827W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.5827W"><span id="translatedtitle">Retrieval of ice cloud properties using an optimal estimation algorithm and <span class="hlt">MODIS</span> infrared observations: 2. Retrieval evaluation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Wind, Gala; Yang, Ping</p> <p>2016-05-01</p> <p>An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) observations is assessed in comparison with the operational retrieval products from <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with <span class="hlt">Aqua</span>. The results show that OE-IR cloud optical thickness (τ) and effective radius (reff) retrievals perform best for ice clouds having 0.5 < τ < 7 and reff < 50 µm. For global ice clouds, the averaged retrieval uncertainties of τ and reff are 19% and 33%, respectively. For optically thick ice clouds with τ larger than 10, however, the τ and reff retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48 km. Relatively large h uncertainty (e.g., > 1 km) occurs for τ < 0.5. Analysis of 1 month of the OE-IR retrievals shows large τ and reff uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent τ and h retrievals. However, obvious differences between the OE-IR and the <span class="hlt">MODIS</span> Collection 6 reff are found.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130013083','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130013083"><span id="translatedtitle">Examining Lake Michigan Spring Euphotic Depth (Zeu) Anomalies: Utilizing 10 Years of <span class="hlt">MODIS-Aqua</span> Data at 4 Kilometer Resolution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Acker, James G.</p> <p>2013-01-01</p> <p>Examination of ten years of euphotic depth anomalies in Lake Michigan during the months of March-June indicates the following: The well-known and frequently observed occurrence of a turbidity feature in the southern part of Lake Michigan during the spring season has become less common during the period 2003-2012. Overall, the clarity of Lake Michigan water in the southern end of the lake appears to have increased spring season over the period 2003-2012. Euphotic depth can be used as a primary indicator of changes in Lake Michigan lacustrine optics, and for other large lakes. Unique events, such as the heavy rains in June 2008, can have a distinct signature in the euphotic depth anomaly distribution in Lake Michigan.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110020816','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110020816"><span id="translatedtitle"><span class="hlt">MODIS</span> Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level VNIR/SWIR Radiometric Uncertainties</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, S.; Wind, G.; Xiong, X.</p> <p>2011-01-01</p> <p>Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) retrievals of optical thickness and effective particle radius for liquid water and ice phase clouds employ a well-known VNIR/ SWIR solar <span class="hlt">reflectance</span> technique. For this type of algorithm, we evaluate the quantitative uncertainty in simultaneous retrievals of these two cloud parameters to pixel-level radiometric calibration estimates and other fundamental (and tractable) error sources.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120002317&hterms=radiometric&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dradiometric','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120002317&hterms=radiometric&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dradiometric"><span id="translatedtitle"><span class="hlt">MODIS</span> Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level Radiometric Error Estimates</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Wind, Galina; Xiong, Xiaoxiong</p> <p>2011-01-01</p> <p><span class="hlt">MODIS</span> retrievals of cloud optical thickness and effective particle radius employ a well-known VNIR/SWIR solar <span class="hlt">reflectance</span> technique. For this type of algorithm, we evaluate the uncertainty in simultaneous retrievals of these two parameters to pixel-level (scene-dependent) radiometric error estimates as well as other tractable error sources.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=286118','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=286118"><span id="translatedtitle">Monitoring NEON terrestrial sites phenology with daily <span class="hlt">MODIS</span> BRDF/albedo product and landsat data</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Bidirectional <span class="hlt">Reflectance</span> Distribution Function (BRDF) and albedo products (MCD43) have already been in production for more than a decade. The standard product makes use of a linear “kernel-driven” RossThick-LiSparse Reciprocal (RTLSR) BRDF m...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A21D0897X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A21D0897X"><span id="translatedtitle">An Enhanced Smoke Detection Using <span class="hlt">MODIS</span> Measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xie, Y.; Qu, J.; Xiong, X.; Hao, X.; Wang, W.; Wang, L.</p> <p>2005-12-01</p> <p>Smoke emitted from wildfire fires or prescribed fires is one of the major pollutions that pose a risk to human health and affect the air quality significantly. The remote sensing technique has been demonstrated as an efficient approach for detecting and tracing smoke plume. As a mixture pollutant, smoke does not have stable spectral signature because of diversified component mixing levels in different situation, but it has some particular characteristics different from others such as cloud, soil, water and so on. In earlier studies, we have already developed a multi-threshold algorithm to detect smoke in the eastern United States by combining both <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands and thermal emissive bands measurements. In order to apply out approach to global scale, we have enhanced the smoke detection algorithm by taking the land surface type into account. Smoke pixels will be output as well as the confidence in the quality of product in final result. In addition, smoke detection is also helpful to fire detection. With current fire detection algorithm, some small and cool fires can not be detected. However, understanding the features and spread direction of smoke can provide us a potential way to identify these fires.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9827E..0VW','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9827E..0VW"><span id="translatedtitle">Estimating terra <span class="hlt">MODIS</span> polarization effect using ocean data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wald, Andrew; Brinkmann, Jake; Wu, Aisheng; Xiong, Jack</p> <p>2016-05-01</p> <p>Terra <span class="hlt">MODIS</span> has been known since pre-launch to have polarization sensitivity, particularly in shortest-wavelength bands 8 and 9. On-orbit <span class="hlt">reflectance</span> trending of pseudo-invariant sites show a variation in <span class="hlt">reflectance</span> as a function of band and scan mirror angle of incidence consistent with time-dependent polarization effects from the rotating doublesided scan mirror. The <span class="hlt">MODIS</span> Characterization Support Team [MCST] estimates the Mueller matrix trending from this variation as observed from a single desert site, but this effect is not included in Collection 6 [C6] calibration. Here we extend the MCST's current polarization sensitivity monitoring to two ocean sites distributed over latitude to help estimate the uncertainties in the derived Mueller matrix. The Mueller matrix elements derived for polarization-sensitive Band 8 for a given site are found to be fairly insensitive to surface brdf modeling. The site-to-site variation is a measure of the uncertainty in the Mueller estimation. Results for band 8 show that the polarization correction reduces mirror-side striping by up to 50% and reduces the instrument polarization effect on <span class="hlt">reflectance</span> time series of an ocean target.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140012662','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140012662"><span id="translatedtitle">Retrieval of Aerosol Optical Properties under Thin Cirrus from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lee, Jaehwa; Hsu, Nai-Yung Christina; Bettenhausen, Corey; Sayer, Andrew Mark.</p> <p>2014-01-01</p> <p>Retrieval of aerosol optical properties using shortwave bands from passive satellite sensors, such as <span class="hlt">MODIS</span>, is typically limited to cloud-free areas. However, if the clouds are thin enough (i.e. thin cirrus) such that the satellite-observed <span class="hlt">reflectance</span> contains signals under the cirrus layer, and if the optical properties of this cirrus layer are known, the TOA <span class="hlt">reflectance</span> can be corrected for the cirrus layer to be used for retrieving aerosol optical properties. To this end, we first correct the TOA <span class="hlt">reflectances</span> in the aerosol bands (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 micron for ocean algorithm and 0.412, 0.47, and 0.65 micron for deep blue algorithm) for the effects of thin cirrus using 1.38 micron <span class="hlt">reflectance</span> and conversion factors that convert cirrus <span class="hlt">reflectance</span> in 1.38 micron band to those in aerosol bands. It was found that the conversion factors can be calculated by using relationships between <span class="hlt">reflectances</span> in 1.38 micron band and minimum <span class="hlt">reflectances</span> in the aerosol bands (Gao et al., 2002). Refer to the example in the figure. Then, the cirrus-corrected <span class="hlt">reflectance</span> can be calculated by subtracting the cirrus <span class="hlt">reflectance</span> from the TOA <span class="hlt">reflectance</span> in the optically thin case. A sensitivity study suggested that cloudy-sky TOA <span class="hlt">reflectances</span> can be calculated with small errors in the form of simple linear addition of cirrus-only <span class="hlt">reflectances</span> and clear-sky <span class="hlt">reflectances</span>. In this study, we correct the cirrus signals up to TOA <span class="hlt">reflectance</span> at 1.38 micron of 0.05 where the simple linear addition is valid without extensive radiative transfer simulations. When each scene passes the set of tests shown in the flowchart, the scene is corrected for cirrus contamination and passed into aerosol retrieval algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AtmRe.181...29K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AtmRe.181...29K"><span id="translatedtitle">Long-term (2002-2014) evolution and trend in Collection 5.1 Level-2 aerosol products derived from the <span class="hlt">MODIS</span> and MISR sensors over the Chinese Yangtze River Delta</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kang, Na; Kumar, K. Raghavendra; Hu, Kang; Yu, Xingna; Yin, Yan</p> <p>2016-11-01</p> <p>The present study aims to investigate spatio-temporal evolution and trend in the aerosol optical properties (aerosol optical depth, AOD; Ångström exponent, AE), qualitatively identify different types and origin of aerosols over an urban city, Nanjing in the Yangtze River Delta, East China. For this purpose, the Collection 5.1 Level-2 data obtained from the Moderate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor onboard Terra and <span class="hlt">Aqua</span> satellites and the Multi-angle Imaging Spectroradiometer (MISR) instrument for the period between 2002 and 2014 have been analyzed. An inter-comparison and validation of AOD were performed against the AOD measurements obtained from the ground-based Aerosol Robotic Network (AERONET) sunphotometer. The <span class="hlt">MODIS</span> AOD550 exhibited wide spatial and temporal distributions over East China, while MISR AOD555 was consistently lower than that of Terra and <span class="hlt">Aqua</span> AOD550 values. The temporal variations (monthly and seasonal mean) of <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span>) and MISR AOD values exhibited a similar pattern. The seasonal mean AOD550 (AE470-660) was found to be maximum with 0.97 ± 0.48 during summer (1.16 ± 0.33 in summer) and a minimum of 0.61 ± 0.28 during the winter season (0.80 ± 0.28 in spring). The annual mean Terra AOD550 at Nanjing showed a strong decreasing trend (- 0.70% year- 1), while the <span class="hlt">Aqua</span> exhibited a slight increasing trend (+ 0.01 year- 1) during the study period. Seasonal air mass back-trajectories obtained from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model were also computed to infer on the transport component over the study region. Different aerosol types were identified via the relationship between AOD550 and fine mode fraction, which reveals that the biomass burning/urban-industrial type aerosols (desert dust) are abundant over the region in summer (spring), apart from the mixed aerosol type.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=19990113161&hterms=science+report&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dscience%2Breport','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=19990113161&hterms=science+report&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dscience%2Breport"><span id="translatedtitle"><span class="hlt">MODIS</span> Science Team Member Semi-annual Report</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Vermote, Eric; ElSaleous, Nazmi; Fisher, Paul; Karakos, Damianos; Ray, James; Vermeulen, Anne</p> <p>1998-01-01</p> <p>This paper presents a semi-annual report of the MODerate resolution imaging Spectroradiometer (<span class="hlt">MODIS</span>) Science Team Members. The most important activities undertaken during this reporting period are the following: 1) Versions 2.1 and 2.2 surface <span class="hlt">reflectance</span> L2/L3 DAAC/SDST delivery; 2) Version 2.0 1km and 250m VI product delivery (assist Arizona); 3) Version 2.1 surface <span class="hlt">reflectance</span> L2 testing; 4) Land Synthetic data set generator improvements; 5) QA; 6) Surface <span class="hlt">reflectance</span> error budget generation (SWAMP request); 7) SCF Hardware; 8) Aerosol transport modeling; 9) Aerosol optical depth retrieval from AVHRR data; 10) Aerosol characteristics retrieval from SeaWIFS/AVHRR fusioned data; 11) Validation activities; 12) Aerosol climatology; and 13) 6S code. The report includes summaries of the topics above.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AdSpR..58..890A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AdSpR..58..890A"><span id="translatedtitle">Feasibility of anomaly occurrence in aerosols time series obtained from <span class="hlt">MODIS</span> satellite images during hazardous earthquakes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Akhoondzadeh, Mehdi; Jahani Chehrebargh, Fatemeh</p> <p>2016-09-01</p> <p>Earthquake is one of the most devastating natural disasters that its prediction has not materialized comprehensive. Remote sensing data can be used to access information which is closely related to an earthquake. The unusual variations of lithosphere, atmosphere and ionosphere parameters before the main earthquakes are considered as earthquake precursors. To date the different precursors have been proposed. This paper examines one of the parameters which can be derived from satellite imagery. The mentioned parameter is Aerosol Optical Depth (AOD) that this article reviews its relationship with earthquake. Aerosol parameter can be achieved through various methods such as AERONET ground stations or using satellite images via algorithms such as the DDV (Dark Dense Vegetation), Deep Blue Algorithm and SYNTAM (SYNergy of Terra and <span class="hlt">Aqua</span> <span class="hlt">Modis</span>). In this paper, by analyzing AOD's time series (derived from <span class="hlt">MODIS</span> sensor on the TERRA platform) for 16 major earthquakes, seismic anomalies were observed before and after earthquakes. Before large earthquakes, rate of AOD increases due to the pre-seismic changes before the strong earthquake, which produces gaseous molecules and therefore AOD increases. Also because of aftershocks after the earthquake there is a significant change in AOD due to gaseous molecules and dust. These behaviors suggest that there is a close relationship between earthquakes and the unusual AOD variations. Therefore the unusual AOD variations around the time of earthquakes can be introduced as an earthquake precursor.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.A23A0263M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.A23A0263M"><span id="translatedtitle"><span class="hlt">MODIS</span> aerosol product at 3 km spatial resolution for urban and air quality studies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mattoo, S.; Remer, L. A.; Levy, R. C.; Holben, B. N.; Smirnov, A.</p> <p>2008-12-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard the Terra and <span class="hlt">Aqua</span> satellites has been producing an aerosol product since early 2000. The original product reports aerosol optical depth and a variety of other aerosol parameters at a spatial resolution of 10 km over both land and ocean. The 10 km product is actually constructed from 500 m pixels, which permits a strict selection process to choose the "best" or "cleanest" pixels in each 10 km square for use in the aerosol retrieval. Thus, the original 10 km product provides a useful product, accurate in many applications. However, the 10 km product can miss narrow aerosol plumes and the spatial variability associated with urban air pollution. The <span class="hlt">MODIS</span> aerosol team will be introducing a finer resolution aerosol product over land regions in the next release of the product (Collection 6). The new product will be produced at 3 km resolution. It is based on the same procedures as the original product and benefits from the same spatial variability criteria for finding and masking cloudy pixels. The 3 km product does capture the higher spatial variability associated with individual aerosol plumes. However, it is noisier than the 10 km product. Both products will be available operationally in Collection 6. The new 3km product offers new synergistic possibilities with PM2.5 monitoring networks, AERONET and various air quality models such as CMAQ.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120003919&hterms=Absorption&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DAbsorption','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120003919&hterms=Absorption&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DAbsorption"><span id="translatedtitle">Reduction of Aerosol Absorption in Beijing Since 2007 from <span class="hlt">MODIS</span> and AERONET</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.; Tanre, D.; Dubovik, O.; Goloub, P.; Chen, H.-B.; Sinyuk, A.; Wang, Y.; Korkin, S.</p> <p>2011-01-01</p> <p>An analysis of the time series of <span class="hlt">MODIS</span>-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The <span class="hlt">MODIS</span> data from both the Terra and <span class="hlt">Aqua</span> satellites were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10-20% in the prior period, the bias mostly disappears after mid- 2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Angstrom exponent. At the same time, it shows an increasing trend in the single scattering albedo, by 0.02 in 9 years. As MAIAC was using the same aerosol model for the entire 2000-2010 period, the decrease in AOT bias after 2007 can be explained only by a corresponding decrease of aerosol absorption caused by a reduction in local black carbon emissions. The observed changes correlate in time with the Chinese government's broad measures to improve air quality in Beijing during preparations for the Summer Olympics of 2008.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011241','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011241"><span id="translatedtitle">Reduction of Aerosol Absorption in Beijing Since 2007 from <span class="hlt">MODIS</span> and AERONET</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.; Tanre, D.; Dubovik, O.; Goloub, P.; Chen, H.-B.; Sinyuk, A.; Wang, Y.; Korkin, S.</p> <p>2011-01-01</p> <p>An analysis of the time series of <span class="hlt">MODIS</span>-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The <span class="hlt">MODIS</span> data from both the Terra and <span class="hlt">Aqua</span> satellites were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10-20% in the prior period, the bias mostly disappears after mid-2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Angstrom exponent. At the same time, it shows an increasing trend in the single scattering albedo, by approx.0.02 in 9 years. As MAIAC was using the same aerosol model for the entire 2000-2010 period, the decrease in AOT bias after 2007 can be explained only by a corresponding decrease of aerosol absorption caused by a reduction in local black carbon emissions. The observed changes correlate in time with the Chinese government's broad measures to improve air quality in Beijing during preparations for the Summer Olympics of 2008.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020067746&hterms=System+offset&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSystem%2Boffset','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020067746&hterms=System+offset&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSystem%2Boffset"><span id="translatedtitle">An Overview of the Earth Observing System <span class="hlt">MODIS</span> Instrument and Associated Data Systems Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, Vincent V.; Barnes, William; Xiong, Jack; Kempler, Steve; Masuoka, Ed</p> <p>2002-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. Now a little over 2 years from that time, the instrument continues to produce good data and products for land, oceans, and atmospheres studies are reaching or achieved maturity for science and applications studies. All subsystems of the instrument are performing as expected: the signal-to-noise (S/N) performance meets or exceeds specifications, band-to-band registration meets specifications, geodetic registration of observations is nearing 50 meters (one sigma) and the spectral bands are located where they were intended to be pre-launch and attendant gains and offsets are stable to date. Some problems with electronic noise, optical leaks, etc. have been identified and solutions to compensate or eliminate these effects have been successful. The data systems have produced a complete year or more for all data products extending from November 2000. Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAAC's). The <span class="hlt">MODIS</span> instrument on the EOS <span class="hlt">Aqua</span> mission should also be expected to be in orbit and functioning in the Spring of 2002.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011GeoRL..3810803L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011GeoRL..3810803L"><span id="translatedtitle">Reduction of aerosol absorption in Beijing since 2007 from <span class="hlt">MODIS</span> and AERONET</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lyapustin, A.; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.; Tanré, D.; Dubovik, O.; Goloub, P.; Chen, H.-B.; Sinyuk, A.; Wang, Y.; Korkin, S.</p> <p>2011-05-01</p> <p>An analysis of the time series of <span class="hlt">MODIS</span>-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The <span class="hlt">MODIS</span> data from both the Terra and <span class="hlt">Aqua</span> satellites were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10-20% in the prior period, the bias mostly disappears after mid-2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Ångström exponent. At the same time, it shows an increasing trend in the single scattering albedo, by ˜0.02 in 9 years. As MAIAC was using the same aerosol model for the entire 2000-2010 period, the decrease in AOT bias after 2007 can be explained only by a corresponding decrease of aerosol absorption caused by a reduction in local black carbon emissions. The observed changes correlate in time with the Chinese government's broad measures to improve air quality in Beijing during preparations for the Summer Olympics of 2008.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130014370','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130014370"><span id="translatedtitle">Assess Calibration Consistency of <span class="hlt">MODIS</span> and AVHRR Thermal Infrared Bands Using SNO Observations Corrected for Atmospheric Effects</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wu, Aisheng; Xie, Yong; Xiong, Xiaoxiong; Chu, I-Wen</p> <p>2012-01-01</p> <p>Monitoring environmental changes from space requires extremely well-calibrated observations to achieve the necessary high accuracy and stability. The calibration differences between the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the Advanced Very High Resolution Radiometer (AVHRR) thermal bands provide a valuable quality assessment of the instrument performance. This letter compares the calibration differences between the <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and NOAA-18 AVHRR bands at 11.0 and 12.0 /Lm using simultaneous nadir overpass observations obtained in nearly parallel orbits. Impacts due to the relative spectral-response differences between the two sensors are estimated by MODTRAN simulations with real-time atmospheric profiles of temperature, water vapor, atmospheric pressure and ozone, and surface skin temperatures. Results show that the temperature difference after the removal of atmospheric impacts is within 0.30 K (or 0.40% in radiance) across the effective calibration range (or the 1l.0 l'm band/channel. For the 12.0 pm band, the differences are OAO K (or 0.50%) at the typical radiance and up to 0.70 K (or 0.90%) close to the maximum radiance, indicating an excellent calibration consistency between <span class="hlt">MODIS</span> and AVHRR for both bands.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940009246','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940009246"><span id="translatedtitle"><span class="hlt">Modis</span>-N airborne simulator</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cech, Steven D.</p> <p>1992-01-01</p> <p>All required work associated with the above referenced contract has been successfully completed at this time. The <span class="hlt">Modis</span>-N Airborne Simulator has been developed from existing AB184 Wildfire spectrometer parts as well as new detector arrays, optical components, and associated mechanical and electrical hardware. The various instrument components have been integrated into an operational system which has undergone extensive laboratory calibration and testing. The instrument has been delivered to NASA Ames where it will be installed on the NASA ER-2. The following paragraphs detail the specific tasks performed during the contract effort, the results obtained during the integration and testing of the instrument, and the conclusions which can be drawn from this effort.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006363','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006363"><span id="translatedtitle">Predicting Clear-Sky <span class="hlt">Reflectance</span> Over Snow/Ice in Polar Regions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick</p> <p>2015-01-01</p> <p>Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and <span class="hlt">Aqua</span> Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and <span class="hlt">reflectance</span> rho for a given location and time. Snow albedo and <span class="hlt">reflectance</span> patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface <span class="hlt">reflectance</span> models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=19950057640&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dspectrometer%2Bresolution','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=19950057640&hterms=spectrometer+resolution&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dspectrometer%2Bresolution"><span id="translatedtitle">Remote sensing of cloud, aerosol and water vapor properties from the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, M. D.</p> <p>1992-01-01</p> <p>The Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) is an Earth-viewing sensor being developed as a facility instrument for the Earth Observing System (EOS) to be launched in the late 1990s. <span class="hlt">MODIS</span> consists of two separate instruments that scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, Sun-synchronous, platform at an altitude of 705 km. Of primary interest for studies of atmospheric physics is the <span class="hlt">MODIS</span>-N (nadir) instrument which will provide images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resoulutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean and atmosperhic processes. The intent of this lecture is to describe the current status of <span class="hlt">MODIS</span>-N and its companion instrument <span class="hlt">MODIS</span>-T (tilt), a tiltable cross-track scanning radiometer with 32 uniformly spaced channels between 0.410 and 0.875 micrometers, and to describe the physical principles behind the development of <span class="hlt">MODIS</span> for the remote sensing of atmospheric properties. Primary emphasis will be placed on the main atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles form spectral-<span class="hlt">reflection</span> and thermal-emission measurements. In addition to cloud and aerosol properties, <span class="hlt">MODIS</span>-N will be utilized for the determination of the total precipitable water vapor over land and atmospheric stability. The physical principles behind the determination of each of these atmospheric products will be described herein.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ACP....13.6065P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ACP....13.6065P"><span id="translatedtitle">Characterisation of dust aerosols in the infrared from IASI and comparison with PARASOL, <span class="hlt">MODIS</span>, MISR, CALIOP, and AERONET observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peyridieu, S.; Chédin, A.; Capelle, V.; Tsamalis, C.; Pierangelo, C.; Armante, R.; Crevoisier, C.; Crépeau, L.; Siméon, M.; Ducos, F.; Scott, N. A.</p> <p>2013-06-01</p> <p>Infrared Atmospheric Sounder Interferometer (IASI) observations covering the period from July 2007 to December 2011 are interpreted in terms of monthly mean, 1°×1°, 10 μm dust Aerosol Optical Depth (AOD), mean altitude and coarse mode effective radius. The geographical study area includes the northern tropical Atlantic and the northwest Arabian Sea, both characterised by strong, regular dust events. The method developed relies on the construction of Look-Up-Tables computed for a large selection of atmospheric situations and observing conditions. At a regional scale, a good agreement is found between IASI-retrieved 10 μm AOD and total visible optical depth at 550 nm from either the Moderate resolution Imaging Spectroradiometer (<span class="hlt">MODIS/Aqua</span> or Terra), or the Multi-angle Imaging SpectroRadiometer (MISR), or the Polarization and Anisotropy of <span class="hlt">Reflectances</span> for Atmospheric Science coupled with Observations from a Lidar (PARASOL). Taking into account the ratio existing between infrared and visible AODs, the diversity between the different 550 nm AODs is similar to the difference between these and the IASI AODs. The infrared AOD to visible AOD ratio, partly <span class="hlt">reflecting</span> the varying distribution of the dust layer between the dust coarse mode particles seen by IASI, and the fine mode seen by the other instruments, is found to vary with the region observed with values close to already published values. Comparisons between the climatologies of the 10 μm IASI AOD and of the PARASOL non-spherical coarse mode AOD at 865 nm, both expected to be representative of the dust coarse mode, lead to conclusions differing according to the region considered. These differences are discussed in the light of the <span class="hlt">MODIS</span> Angström exponent (865-550 nm). At local scale, around six Aerosol Robotic Network (AERONET) sites, close or far from the dust sources, a similar satisfactory agreement is found between IASI and the visible AODs and the differences between these products are shown and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ACPD...1223093P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ACPD...1223093P"><span id="translatedtitle">Characterization of dust aerosols in the infrared from IASI and comparison with PARASOL, <span class="hlt">MODIS</span>, MISR, CALIOP, and AERONET observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peyridieu, S.; Chédin, A.; Capelle, V.; Tsamalis, C.; Pierangelo, C.; Armante, R.; Crevoisier, C.; Crépeau, L.; Siméon, M.; Ducos, F.; Scott, N. A.</p> <p>2012-09-01</p> <p>Infrared Atmospheric Sounder Interferometer (IASI) observations covering the period from July 2007 to December 2011 are interpreted in terms of monthly mean, 1°×1°, 10 μm dust Aerosol Optical Depth (AOD), mean altitude and coarse mode effective radius. The geographical study area includes the northern tropical Atlantic and the north-west Arabian Sea, both characterized by strong, regular dust events. The method developed relies on the construction of Look-Up-Tables computed for a large selection of atmospheric situations and observing conditions. At regional scale, a good agreement is found between IASI-retrieved 10 μm AOD and total visible optical depth at 550 nm from either the Moderate resolution Imaging Spectroradiometer (<span class="hlt">MODIS/Aqua</span> or Terra), or the Multi-angle Imaging SpectroRadiometer (MISR), or the Polarization and Anisotropy of <span class="hlt">Reflectances</span> for Atmospheric Science coupled with Observations from a Lidar (PARASOL). Taking into account the ratio existing between infrared and visible AODs, the diversity between the different 550 nm AODs is similar to the difference between these and the IASI AODs. The infrared AOD to visible AOD ratio, partly <span class="hlt">reflecting</span> the varying distribution of the dust layer between the dust coarse mode particles seen by IASI, and the fine mode seen by the other instruments, is found to vary with the region observed with values close to already published values. Comparisons between the climatologies of the 10 μm IASI AOD and of the PARASOL non-spherical coarse mode AOD at 865 nm, both expected to be representative of the dust coarse mode, lead to conclusions differing according to the region considered. These differences are discussed in the light of the <span class="hlt">MODIS</span> Angström exponent (865-550 nm). At local scale, around six Aerosol Robotic Network (AERONET) sites, close or far from the dust sources, a similar satisfactory agreement is found between IASI and the visible AODs and the differences between these products are shown and analysed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..52...65J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..52...65J"><span id="translatedtitle">A comprehensive assessment of the correlations between field crop yields and commonly used <span class="hlt">MODIS</span> products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Johnson, David M.</p> <p>2016-10-01</p> <p>An exploratory assessment was undertaken to determine the correlation strength and optimal timing of several commonly used Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) composited imagery products against crop yields for 10 globally significant agricultural commodities. The crops analyzed included barley, canola, corn, cotton, potatoes, rice, sorghum, soybeans, sugarbeets, and wheat. The <span class="hlt">MODIS</span> data investigated included the Normalized Difference Vegetation Index (NDVI), Fraction of Photosynthetically Active Radiation (FPAR), Leaf Area Index (LAI), and Gross Primary Production (GPP), in addition to daytime Land Surface Temperature (DLST) and nighttime LST (NLST). The imagery utilized all had 8-day time intervals, but NDVI had a 250 m spatial resolution while the other products were 1000 m. These <span class="hlt">MODIS</span> datasets were also assessed from both the Terra and <span class="hlt">Aqua</span> satellites, with their differing overpass times, to document any differences. A follow-on analysis, using the Terra 250 m NDVI data as a benchmark, looked at the yield prediction utility of NDVI at two spatial scales (250 m vs. 1000 m), two time precisions (8-day vs. 16-day), and also assessed the Enhanced Vegetation Index (EVI, at 250 m, 16-day). The analyses spanned the major farming areas of the United States (US) from the summers of 2008-2013 and used annual county-level average crop yield data from the US Department of Agriculture as a basis. All crops, except rice, showed at least some positive correlations to each of the vegetation related indices in the middle of the growing season, with NDVI performing slightly better than FPAR. LAI was somewhat less strongly correlated and GPP weak overall. Conversely, some of the crops, particularly canola, corn, and soybeans, also showed negative correlations to DLST mid-summer. NLST, however, was never correlated to crop yield, regardless of the crop or seasonal timing. Differences between the Terra and <span class="hlt">Aqua</span> results were found to be minimal. The 1000 m</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110013319','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110013319"><span id="translatedtitle">Quantitative Evaluation of <span class="hlt">MODIS</span> Fire Radiative Power Measurement for Global Smoke Emissions Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Ellison, Luke</p> <p>2011-01-01</p> <p>Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the <span class="hlt">MODIS</span> sensors aboard the polar orbiting Terra and <span class="hlt">Aqua</span> satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has steadily gained increasing recognition as an important parameter for facilitating the development of various scientific studies and applications relating to the quantitative characterization of biomass burning and their emissions. To establish the scientific integrity of the FRP as a stable quantity that can be measured consistently across a variety of sensors and platforms, with the potential of being utilized to develop a unified long-term climate data record of fire activity and impacts, it needs to be thoroughly evaluated, calibrated, and validated. Therefore, we are conducting a detailed analysis of the FRP products from <span class="hlt">MODIS</span> to evaluate the uncertainties associated with them, such as those due to the effects of satellite variable observation geometry and other factors, in order to establish their error budget for use in diverse scientific research and applications. In this presentation, we will show recent results of the <span class="hlt">MODIS</span> FRP uncertainty analysis and error mitigation solutions, and demonstrate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JVGR..311...60C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JVGR..311...60C"><span id="translatedtitle">The 2006 lava dome eruption o