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.

Phytoplankton Bloom Off Portugal

NASA Technical Reports Server (NTRS)

2002-01-01

Turquoise and greenish swirls marked the presence of a large phytoplankton bloom off the coast of Portugal on April 23, 2002. This true-color image was acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS), flying aboard NASA's Terra satellite. There are also several fires burning in northwest Spain, near the port city of A Coruna. Please note that the high-resolution scene provided here is 500 meters per pixel. For a copy of this scene at the sensor's fullest resolution, visit the MODIS Rapidfire site.

A Prototype MODI- SSM/I Snow Mapping Algorithm

NASA Technical Reports Server (NTRS)

Tait, Andrew B.; Barton, Jonathan S.; Hall, Dorothy K.

1999-01-01

Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

Radiometric characterization of hyperspectral imagers using multispectral sensors

NASA Astrophysics Data System (ADS)

McCorkel, Joel; Thome, Kurt; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

2009-08-01

The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these tests sites are not always successful due to weather and funding availability. Therefore, RSG has also employed automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor. This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (MODIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of MODIS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most bands as well as similar agreement between results that employ the different MODIS sensors as a reference.

MODIS on-orbit thermal emissive bands lifetime performance

NASA Astrophysics Data System (ADS)

Madhavan, Sriharsha; Wu, Aisheng; Chen, Na; Xiong, Xiaoxiong

2016-05-01

MODerate resolution Imaging Spectroradiometer (MODIS), 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 Aqua (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-MODIS currently functional beyond 15 years and the A-MODIS operating beyond 13 years respectively. The MODIS 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 MODIS 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.

MODIS On-Orbit Thermal Emissive Bands Lifetime Performance

NASA Technical Reports Server (NTRS)

Madhavan, Sriharsha; Xiong, Xiaoxiong

2016-01-01

MODerate resolution Imaging Spectroradiometer (MODIS), 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 Aqua (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-MODIS currently functional beyond 15 years and the A-MODIS operating beyond 13 years respectively. The MODIS sensor characteristics include a spectral coverage from 0.41 micron 14.4 micron, of which wavelengths ranging from 3.7 micron 14. 4 micron 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 MODIS 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.

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA

USGS Publications Warehouse

Boyte, Stephen; Wylie, Bruce K.; Rigge, Matthew B.; Dahal, Devendra

2018-01-01

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.

Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

USGS Publications Warehouse

Boken, Vijendra K.; Easson, Gregory L.; Rowland, James

2010-01-01

The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R 2. The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

Implementation of a near real-time burned area detection algorithm calibrated for VIIRS imagery

Treesearch

Brenna Schwert; Carl Albury; Jess Clark; Abigail Schaaf; Shawn Urbanski; Bryce Nordgren

2016-01-01

There is a need to implement methods for rapid burned area detection using a suitable replacement for Moderate Resolution Imaging Spectroradiometer (MODIS) imagery to meet future mapping and monitoring needs (Roy and Boschetti 2009, Tucker and Yager 2011). The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor onboard the Suomi-National Polar-orbiting Partnership...

Trend analysis of the aerosol optical depth from fusion of MISR and MODIS retrievals over China

NASA Astrophysics Data System (ADS)

Guo, Jing; Gu, Xingfa; Yu, Tao; Cheng, Tianhai; Chen, Hao

2014-03-01

Atmospheric aerosol plays an important role in the climate change though direct and indirect processes. In order to evaluate the effects of aerosols on climate, it is necessary to have a research on their spatial and temporal distributions. Satellite aerosol remote sensing is a developing technology that may provide good temporal sampling and superior spatial coverage to study aerosols. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) have provided aerosol observations since 2000, with large coverage and high accuracy. However, due to the complex surface, cloud contamination, and aerosol models used in the retrieving process, the uncertainties still exist in current satellite aerosol products. There are several observed differences in comparing the MISR and MODIS AOD data with the AERONET AOD. Combing multiple sensors could reduce uncertainties and improve observational accuracy. The validation results reveal that a better agreement between fusion AOD and AERONET AOD. The results confirm that the fusion AOD values are more accurate than single sensor. We have researched the trend analysis of the aerosol properties over China based on nine-year (2002-2010) fusion data. Compared with trend analysis in Jingjintang and Yangtze River Delta, the accuracy has increased by 5% and 3%, respectively. It is obvious that the increasing trend of the AOD occurred in Yangtze River Delta, where human activities may be the main source of the increasing AOD.

Sensor On-orbit Calibration and Characterization Using Spacecraft Maneuvers

NASA Technical Reports Server (NTRS)

Xiong, X.; Butler, Jim; Barnes, W. L.; Guenther, B.

2007-01-01

Spacecraft flight operations often require activities that involve different kinds of maneuvers for orbital adjustments (pitch, yaw, and roll). Different maneuvers, when properly planned and scheduled, can also be applied to support and/or to perform on-board sensor calibration and characterization. This paper uses MODIS (Moderate Resolution Imaging Spectroradiometer) as an example to illustrate applications of spacecraft maneuvers for Earth-observing sensors on-orbit calibration and characterization. MODIS is one of the key instruments for NASA's Earth Observing System (EOS) currently operated on-board the EOS Terra and Aqua spacecraft launched in December 1999 and May 2002, respectively. Since their launch, both Terra and Aqua spacecraft have made a number of maneuvers, specially the yaw and roll maneuvers, to support the MODIS on-orbit calibration and characterization. For both Terra and Aqua MODIS, near-monthly spacecraft roll maneuvers are executed for lunar observations. These maneuvers are carefully scheduled so that the lunar phase angles are nearly identical for each sensor's lunar observations. The lunar observations are used to track MODIS reflective solar bands (RSB) calibration stability and to inter-compare Terra and Aqua MODIS RSB calibration consistency. To date, two sets of yaw maneuvers (each consists of two series of 8 consecutive yaws) by the Terra spacecraft and one set by the Aqua spacecraft have been performed to validate MODIS solar diffuser (SD) bi-directional reflectance factor (BRF) and to derive SD screen transmission. Terra spacecraft pitch maneuvers, first made on March 26, 2003 and the second on April 14, 2003 (with the Moon in the spacecraft nadir view), have been applied to characterize MODIS thermal emissive bands (TEB) response versus scan angle (RVS). This is particularly important since the pre-launch TEB RSV measurements made by the sensor vendor were not successful. Terra MODIS TEB RVS obtained from pitch maneuvers have been used in the current LIB calibration algorithm. Lunq observations from pitch maneuvers also provided information to cross-calibrate MODIS with other sensors (MISR and ASTER) on the same platform. We will provide a summary of MODIS maneuver activities and their applications for MODIS calibration and characterization. The results and lessons learned discussed in this paper from MODIS maneuver activities will provide useful insights into future spacecraft and sensor operation.

Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors

USGS Publications Warehouse

Chander, Gyanesh; Mishra, N.; Helder, Dennis L.; Aaron, David; Choi, T.; Angal, A.; Xiong, X.

2010-01-01

Different applications and technology developments in Earth observations necessarily require different spectral coverage. Thus, even for the spectral bands designed to look at the same region of the electromagnetic spectrum, the relative spectral responses (RSR) of different sensors may be different. In this study, spectral band adjustment factors (SBAF) are derived using hyperspectral Earth Observing-1 (EO-1) Hyperion measurements to adjust for the spectral band differences between the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance measurements from 2000 to 2009 over the pseudo-invariant Libya 4 reference standard test site.

An Overview of Lunar Calibration and Characterization for the EOS Terra and Aqua MODIS

NASA Technical Reports Server (NTRS)

Xiong, X.; Salomonson, V. V.; Sun, J.; Chiang, K.; Xiong, S.; Humphries, S.; Barnes, W.; Guenther, B.

2004-01-01

The Moon can be used as a stable source for Earth-observing sensors on-orbit radiometric and spatial stability monitoring in the VIS and NIR spectral regions. It can also serve as a calibration transfer vehicle among multiple sensors. Nearly identical copies of the Moderate Resolution Imaging Spectroradiometer (MODE) have been operating on-board the NASA's Earth Observing System (EOS) Terra and Aqua satellites since their launches in December 1999 and May 2002, respectively. Terra and Aqua MODIS each make observations in 36 spectral bands covering the spectral range from 0.41 to 14.5 microns and are calibrated on-orbit by a set of on-board calibrations (OBCs) including: 1) a solar diffuser (SD), 2) a solar diffuser stability monitor (SDSM), 3) a blackbody (BB), and 4) a spectro-radiometric calibration assembly (SRCA). In addition to fully utilizing the OBCs, the Moon has been used extensively by both Terra and Aqua MODIS to support their on-orbit calibration and characterization. A 4 This paper provides an overview of applications of lunar calibration and characterization from the MODIS perspective, including monitoring radiometric calibration stability for the reflective solar bands (RSBs), tracking changes of the sensors response versus scan-angle (RVS), examining the sensors spatial performance , and characterizing optical leaks and electronic crosstalk among different spectral bands and detectors. On-orbit calibration consistency between the two MODIS instruments is also addressed. Based on the existing on-orbit time series of the Terra and Aqua MODIS lunar observations, the radiometric difference between the two sensors is less than +/-1% for the RSBs. This method provides a powerful means of performing calibration comparisons among Earth-observing sensors and assures consistent data and science products for the long-term studies of climate and environmental changes.

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.

Satellite and airborne IR sensor validation by an airborne interferometer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gumley, L.E.; Delst, P.F. van; Moeller, C.C.

1996-11-01

The validation of in-orbit longwave IR radiances from the GOES-8 Sounder and inflight longwave IR radiances from the MODIS Airborne Simulator (MAS) is described. The reference used is the airborne University of Wisconsin High Resolution Interferometer Sounder (HIS). The calibration of each sensor is described. Data collected during the Ocean Temperature Interferometric Survey (OTIS) experiment in January 1995 is used in the comparison between sensors. Detailed forward calculations of at-sensor radiance are used to account for the difference in GOES-8 and HIS altitude and viewing geometry. MAS radiances and spectrally averaged HIS radiances are compared directly. Differences between GOES-8 andmore » HIS brightness temperatures, and GOES-8 and MAS brightness temperatures, are found to be with 1.0 K for the majority of longwave channels examined. The same validation approach will be used for future sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). 11 refs., 2 figs., 4 tabs.« less

Intercomparison of Evapotranspiration Over the Savannah Volta Basin in West Africa Using Remote Sensing Data

PubMed Central

Opoku-Duah, S.; Donoghue, D.N.M.; Burt, T. P.

2008-01-01

This paper compares evapotranspiration estimates from two complementary satellite sensors – NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and ESA's ENVISAT Advanced Along-Track Scanning Radiometer (AATSR) over the savannah area of the Volta basin in West Africa. This was achieved through solving for evapotranspiration on the basis of the regional energy balance equation, which was computationally-driven by the Surface Energy Balance Algorithm for Land algorithm (SEBAL). The results showed that both sensors are potentially good sources of evapotranspiration estimates over large heterogeneous landscapes. The MODIS sensor measured daily evapotranspiration reasonably well with a strong spatial correlation (R2=0.71) with Landsat ETM+ but underperformed with deviations up to ∼2.0 mm day-1, when compared with local eddy correlation observations and the Penman-Monteith method mainly because of scale mismatch. The AATSR sensor produced much poorer correlations (R2=0.13) with Landsat ETM+ and conventional ET methods also because of differences in atmospheric correction and sensor calibration over land. PMID:27879847

Radiometric cross-calibration of the Terra MODIS and Landsat 7 ETM+ using an invariant desert site

USGS Publications Warehouse

Choi, T.; Angal, A.; Chander, G.; Xiong, X.

2008-01-01

A methodology for long-term radiometric cross-calibration between the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors was developed. The approach involves calibration of near-simultaneous surface observations between 2000 and 2007. Fifty-seven cloud-free image pairs were carefully selected over the Libyan desert for this study. The Libyan desert site (+28.55??, +23.39??), located in northern Africa, is a high reflectance site with high spatial, spectral, and temporal uniformity. Because the test site covers about 12 kmx13 km, accurate geometric preprocessing is required to match the footprint size between the two sensors to avoid uncertainties due to residual image misregistration. MODIS Level IB radiometrically corrected products were reprojected to the corresponding ETM+ image's Universal Transverse Mercator (UTM) grid projection. The 30 m pixels from the ETM+ images were aggregated to match the MODIS spatial resolution (250 m in Bands 1 and 2, or 500 m in Bands 3 to 7). The image data from both sensors were converted to absolute units of at-sensor radiance and top-ofatmosphere (TOA) reflectance for the spectrally matching band pairs. For each band pair, a set of fitted coefficients (slope and offset) is provided to quantify the relationships between the testing sensors. This work focuses on long-term stability and correlation of the Terra MODIS and L7 ETM+ sensors using absolute calibration results over the entire mission of the two sensors. Possible uncertainties are also discussed such as spectral differences in matching band pairs, solar zenith angle change during a collection, and differences in solar irradiance models.

An Overview of the Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) Data Products and Availability for Environmental Applications and Global Change Studies

NASA Technical Reports Server (NTRS)

Salomonson, V. 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 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 spacecraft, instrument, and data systems 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 (DAACs) or through Direct Broadcast (DB) stations. The EOS Aqua mission was launched successfully May 4,2002 with another MODIS on it. 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. Subsequently the Aqua MODIS observations will substantially add to the capabilities of the Terra MODIS for environmental applications and global change studies.

An Overview of the Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) Data Products Status and Availability for Environmental Applications and Global Change Studies

NASA Technical Reports Server (NTRS)

Salomonson, Vincent V.; Houser, Paul (Technical Monitor)

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. 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 spacecraft, instrument, and data systems 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 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 MODIS instrument on the EOS Aqua mission should also be expected to be in orbit and functioning in the Spring of 2002. The Aqua spacecraft will operate 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. Subsequently the Aqua MODIS observations will substantially add to the capabilities of the Terra MODIS for environmental applications and global change studies.

Cross comparison of the Collection 6 and Collection 6.1 Terra and Aqua MODIS Bands 1 and 2 using AVHRR N15 and N19

NASA Astrophysics Data System (ADS)

Chen, Xuexia; Wu, Aisheng; Xiong, Xiaoxiong J.; Chen, Na

2017-09-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key scientific instrument that was launched into Earth orbit by NASA in 1999 on board the Terra (EOS AM) satellite and in 2002 on board the Aqua (EOS PM) satellite. Terra and Aqua MODIS collect the entire Earth's images every 1 to 2 days in 36 spectral bands. MODIS band 1 (0.620- 0.670 μm) and band 2 (0.841-0.876 μm) have nadir spatial resolution of 250 m and their measurements are crucial to derive key land surface products. This study evaluates the performance of the Collection 6 (C6, and C6.1) L1B of both Terra and Aqua MODIS bands 1 and 2 using Simultaneous Nadir Overpass (SNO) data to compare with AVHRR/3 sensors. We examine the relative stability between Terra and Aqua MODIS in reference to NOAA N15 and N19 the Advanced Very High Resolution Radiometer (AVHRR/3). The comparisons for MODIS to AVHRR/3 are over a fifteenyear period from 2002 to 2017. Results from this study provide a quantitative assessment of Terra and Aqua MODIS band 1 and band 2 calibration stability and the relative differences through the NOAA N15 and N19 AVHRR/3 sensors.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

PubMed

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

PubMed Central

Lange, Maximilian; Rebmann, Corinna; Cuntz, Matthias; Doktor, Daniel

2017-01-01

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure. PMID:28800065

Using NASA's Interactive Visualization and Image Extraction Tool AppEEARS to Assess Differences between MODIS and VIIRS

NASA Astrophysics Data System (ADS)

Neeley, S.

2017-12-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi-NPP satellite is designed to provide data continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard NASA's Terra and Aqua satellites. VIIRS data products are generated in a similar format as MODIS using modified algorithms and aim to extend the data lifecycle of MODIS products, which are widely used in a variety of scientific disciplines. However, there are differences in the characteristics of the instruments that could influence decision making when conducting a study involving a combination of products from both sensors. Inter-sensor comparison studies between VIIRS and MODIS have highlighted some of the inconsistencies between the sensors, including calibrated radiances, pixel sizes, swath widths, and spectral response functions of the bands. These differences should be well-understood among the science community as these inconsistencies could potentially effect the results of time-series analyses or land change studies that rely on using VIIRS and MODIS data products in combination. An efficient method to identify and better understand differences between data products will allow for the science community to make informed decisions when conducting analyses using a combination of VIIRS and MODIS data products. NASA's Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) tool enables users to efficiently compare MODIS and VIIRS data products, including surface reflectance from 2012 to present. AppEEARS is a user-friendly image extraction tool used to order spatial and temporal data subsets, reproject data, and visualize output sample results before data download. AppEEARs allows users to compare MODIS and VIIRS data products by providing interactive visualizations and summary statistics of each dataset-either over a specific point or region of interest across a period of time. This tool enhances decision-making when using newly available VIIRS products combined with MODIS as it allows for data inconsistencies to be explored before the data is downloaded. Here, we demonstrate how AppEEARS enables users to perform comparisons across VIIRS and MODIS Surface Reflectance products and provide a detailed review of characteristic differences between the instruments.

Spatio-Temporal Variations in the Associations between Hourly PM2.5 and Aerosol Optical Depth (AOD) from MODIS Sensors on Terra and Aqua*

PubMed Central

Kim, Minho; Zhang, Xingyou; Holt, James B.; Liu, Yang

2015-01-01

Recent studies have explored the relationship between aerosol optical depth (AOD) measurements by satellite sensors and concentrations of particulate matter with aerodynamic diameters less than 2.5 μm (PM2.5). However, relatively little is known about spatial and temporal patterns in this relationship across the contiguous United States. In this study, we investigated the relationship between US Environmental Protection Agency estimates of PM2.5 concentrations and Moderate Resolution Imaging Spectroradiometer (MODIS) AOD measurements provided by two NASA satellites (Terra and Aqua) across the contiguous United States during 2005. We found that the combined use of both satellite sensors provided more AOD coverage than the use of either satellite sensor alone, that the correlation between AOD measurements and PM2.5 concentrations varied substantially by geographic location, and that this correlation was stronger in the summer and fall than that in the winter and spring. PMID:26336576

Cross-calibration of the Terra MODIS, Landsat 7 ETM+ and EO-1 ALI sensors using near-simultaneous surface observation over the Railroad Valley Playa, Nevada, test site

USGS Publications Warehouse

Chander, G.; Angal, A.; Choi, T.; Meyer, D.J.; Xiong, X.; Teillet, P.M.

2007-01-01

A cross-calibration methodology has been developed using coincident image pairs from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS), the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Earth Observing EO-1 Advanced Land Imager (ALI) to verify the absolute radiometric calibration accuracy of these sensors with respect to each other. To quantify the effects due to different spectral responses, the Relative Spectral Responses (RSR) of these sensors were studied and compared by developing a set of "figures-of-merit." Seven cloud-free scenes collected over the Railroad Valley Playa, Nevada (RVPN), test site were used to conduct the cross-calibration study. This cross-calibration approach was based on image statistics from near-simultaneous observations made by different satellite sensors. Homogeneous regions of interest (ROI) were selected in the image pairs, and the mean target statistics were converted to absolute units of at-sensor reflectance. Using these reflectances, a set of cross-calibration equations were developed giving a relative gain and bias between the sensor pair.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Longwave Radiative Forcing of Saharan Dust Aerosols Estimated from MODIS, MISR and CERES Observations on Terra

NASA Technical Reports Server (NTRS)

Zhang, Jiang-Long; Christopher, Sundar A.

2003-01-01

Using observations from the Multi-angle Imaging Spectroradiometer (MISR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Clouds and the Earth's Radiant Energy System (CERES) instruments onboard the Terra satellite; we present a new technique for studying longwave (LW) radiative forcing of dust aerosols over the Saharan desert for cloud-free conditions. The monthly-mean LW forcing for September 2000 is 7 W/sq m and the LW forcing efficiency' (LW(sub eff)) is 15 W/sq m. Using radiative transfer calculations, we also show that the vertical distribution of aerosols and water vapor are critical to the understanding of dust aerosol forcing. Using well calibrated, spatially and temporally collocated data sets, we have combined the strengths of three sensors from the same satellite to quantify the LW radiative forcing, and show that dust aerosols have a "warming" effect over the Saharan desert that will counteract the shortwave "cooling effect" of aerosols.

Daily MODIS Data Trends of Hurricane-Induced Forest Impact and Early Recovery

NASA Technical Reports Server (NTRS)

Ramsey, Elijah, III; Spruce, Joseph; Rangoonwala, Amina; Suzuoki, Yukihiro; Smoot, James; Gasser, Jerry; Bannister, Terri

2011-01-01

We studied the use of daily satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors to assess wetland forest damage and recovery from Hurricane Katrina (29 August 2005 landfall). Processed MODIS daily vegetation index (VI) trends were consistent with previously determined impact and recovery patterns provided by the "snapshot" 25 m Landsat Thematic Mapper optical and RADARSAT-1 synthetic aperture radar satellite data. Phenological trends showed high 2004 and 2005 pre-hurricane temporal correspondence within bottomland hardwood forest communities, except during spring green-up, and temporal dissimilarity between these hardwoods and nearby cypress-tupelo swamp forests (Taxodium distichum [baldcypress] and Nyssa aquatica [water tupelo]). MODIS VI trend analyses established that one year after impact, cypress-tupelo and lightly impacted hardwood forests had recovered to near prehurricane conditions. In contrast, canopy recovery lagged in the moderately and severely damaged hardwood forests, possibly reflecting regeneration of pre-hurricane species and stand-level replacement by invasive trees.

Analysis of Summer 2002 Melt Extent on the Greenland Ice Sheet using MODIS and SSM/I Data

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Williams, Richard S., Jr.; Steffen, Konrad; Chien, Y. L.; Foster, James L.; Robinson, David A.; Riggs, George A.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0 degree isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 plus or minus 2.09 C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to approximately 2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland ice sheet.

Achieving sub-pixel geolocation accuracy in support of MODIS land science

USGS Publications Warehouse

Wolfe, R.E.; Nishihama, M.; Fleig, A.J.; Kuyper, J.A.; Roy, David P.; Storey, James C.; Patt, F.S.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was launched in December 1999 on the polar orbiting Terra spacecraft and since February 2000 has been acquiring daily global data in 36 spectral bands—29 with 1 km, five with 500 m, and two with 250 m nadir pixel dimensions. The Terra satellite has on-board exterior orientation (position and attitude) measurement systems designed to enable geolocation of MODIS data to approximately 150 m (1σ) at nadir. A global network of ground control points is being used to determine biases and trends in the sensor orientation. Biases have been removed by updating models of the spacecraft and instrument orientation in the MODIS geolocation software several times since launch and have improved the MODIS geolocation to approximately 50 m (1σ) at nadir. This paper overviews the geolocation approach, summarizes the first year of geolocation analysis, and overviews future work. The approach allows an operational characterization of the MODIS geolocation errors and enables individual MODIS observations to be geolocated to the sub-pixel accuracies required for terrestrial global change applications.

Analysis of Summer 2002 Melt Extent on the Greenland Ice Sheet using MODIS and SSM/I Data

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Williams, Richard S.; Steffen, Konrad; Chien, Janet Y. L.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0 deg. isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 +/- 2.09 C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to approx. 2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near- surface melt on the Greenland ice sheet.

Analysis of summer 2002 melt extent on the Greenland ice sheet using MODIS and SSM/I data

USGS Publications Warehouse

Hall, D.K.; Williams, R.S.; Steffen, K.; Chien, Janet Y.L.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0?? isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3??2.09??C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to ???2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland ice sheet.

Analysis of summer 2002 melt extent on the Greenland ice sheet using MODIS and SSM/I data

USGS Publications Warehouse

Hall, D. K.; Williams, R.S.; Steffen, K.; Chien, Janet Y.L.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0deg isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 plusmn 2.09 degC, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to ~2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland ice sheet.

Smog Obscures Chinese Coast

NASA Technical Reports Server (NTRS)

2002-01-01

Most of southeastern China has been covered by a thick greyish shroud of aerosol pollution over the last few weeks. The smog is so thick it is difficult to see the surface in some regions of this scene, acquired on January 7, 2002. The city of Hong Kong is the large brown cluster of pixels toward the lower lefthand corner of the image (indicated by the faint black box). The island of Taiwan, due east of mainland China, is also blanketed by the smog. This true-color image was captured by the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor, flying aboard NASA's Terra satellite. Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

MODIS Science Algorithms and Data Systems Lessons Learned

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Ridgway, Bill L.; Patt, Fred S.; Masuoka, Edward J.

2009-01-01

For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) 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 Aqua missions in less than a year. Many of the lessons learned from MODIS are already being applied to follow-on missions.

Comparison of Near-Surface Air Temperatures and MODIS Ice-Surface Temperatures at Summit, Greenland (2008-2013)

NASA Technical Reports Server (NTRS)

Shuman, Christopher A.; Hall, Dorothy K.; DiGirolamo, Nicolo E.; Mefford, Thomas K.; Schnaubelt, Michael J.

2014-01-01

We have investigated the stability of the MODerate resolution Imaging Spectroradiometer (MODIS) infrared-derived ice surface temperature (IST) data from Terra for use as a climate quality data record. The availability of climate quality air temperature data (TA) from a NOAA Global Monitoring Division observatory at Greenlands Summit station has enabled this high temporal resolution study of MODIS ISTs. During a 5 year period (July 2008 to August 2013), more than 2500 IST values were compared with 3-minute average TA values derived from the 1-minute data from NOAAs primary 2 m air temperature sensor. These data enabled an expected small offset between air and surface temperatures at this the ice sheet location to be investigated over multiple annual cycles.

eMODIS: A User-Friendly Data Source

USGS Publications Warehouse

Jenkerson, Calli B.; Maiersperger, Thomas; Schmidt, Gail

2010-01-01

The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'eMODIS' based on Moderate Resolution Imaging Spectroradiometer (MODIS) 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), MODIS is well suited for vegetation studies. For operational monitoring, however, the benefits of MODIS are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. eMODIS responds to a community-specific need for alternatively packaged MODIS data, addressing each of these factors for real-time monitoring and historical trend analysis. eMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Terra and Aqua satellites by combining MODIS Land Science Collection 5 Atmospherically Corrected Surface Reflectance production code and USGS EROS MODIS Direct Broadcast System (DBS) software to create surface reflectance and Normalized Difference Vegetation Index (NDVI) products. eMODIS 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. eMODIS composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see eMODIS Product Description below). For eMODIS products generated over the continental United States (eMODIS CONUS), the Terra (from 2000) and Aqua (from 2002) records are available and continue through present time. eMODIS CONUS also is generated in an expedited process that delivers a 7-day rolling composite, created daily with the most recent 7 days of acquisition, to users monitoring real-time vegetation conditions. eMODIS Alaska is not part of expedited processing, but does cover the Terra mission life (2000-present). A simple file transfer protocol (FTP) distribution site currently is enabled on the Internet for direct download of eMODIS products (ftp://emodisftp.cr.usgs.gov/eMODIS), with plans to expand into an interactive portal environment.

GEONEX: algorithm development and validation of Gross Primary Production from geostationary satellites

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Wang, W.; Ganguly, S.; Li, S.; Michaelis, A.; Higuchi, A.; Takenaka, H.; Nemani, R. R.

2017-12-01

New geostationary sensors such as the AHI (Advanced Himawari Imager on Himawari-8) and the ABI (Advanced Baseline Imager on GOES-16) have the potential to advance ecosystem modeling particularly of diurnally varying phenomenon through frequent observations. These sensors have similar channels as in MODIS (MODerate resolution Imaging Spectroradiometer), and allow us to utilize the knowledge and experience in MODIS data processing. Here, we developed sub-hourly Gross Primary Production (GPP) algorithm, leverating the MODIS 17 GPP algorithm. We run the model at 1-km resolution over Japan and Australia using geo-corrected AHI data. Solar radiation was directly calculated from AHI using a neural network technique. The other necessary climate data were derived from weather stations and other satellite data. The sub-hourly estimates of GPP were first compared with ground-measured GPP at various Fluxnet sites. We also compared the AHI GPP with MODIS 17 GPP, and analyzed the differences in spatial patterns and the effect of diurnal changes in climate forcing. The sub-hourly GPP products require massive storage and strong computational power. We use NEX (NASA Earth Exchange) facility to produce the GPP products. This GPP algorithm can be applied to other geostationary satellites including GOES-16 in future.

First Moderate Resolution Imaging Spectroradiometer (MODIS) Snow and Ice Workshop

NASA Technical Reports Server (NTRS)

Hall, Dorothy K. (Editor)

1995-01-01

This document is a compilation of summaries of talks presented at a 2-day workshop on Moderate Resolution maging Spectroradiometer (MODIS) snow and ice products. The objectives of the workshop were to: inform the snow and ce community of potential MODIS products, seek advice from the participants regarding the utility of the products, and letermine the needs for future post-launch MODIS snow and ice products. Four working groups were formed to discuss at-launch snow products, at-launch ice products, post-launch snow and ice products and utility of MODIS snow and ice products, respectively. Each working group presented recommendations at the conclusion of the workshop.

Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

NASA Technical Reports Server (NTRS)

Turpie, Kevin R.; Eplee, Robert E., Jr.; Franz, Bryan A.; Del Castillo, Carlos

2014-01-01

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

Impact of MODIS Sensor Calibration Updates on Greenland Ice Sheet Surface Reflectance and Albedo Trends

NASA Technical Reports Server (NTRS)

Casey, Kimberly A.; Polashenski, Chris M.; Chen, Justin; Tedesco, Marco

2017-01-01

We evaluate Greenland Ice Sheet (GrIS) surface reflectance and albedo trends using the newly released Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) products over the period 2001-2016. We find that the correction of MODIS sensor degradation provided in the new C6 data products reduces the magnitude of the surface reflectance and albedo decline trends obtained from previous MODIS data (i.e., Collection 5, C5). Collection 5 and 6 data product analysis over GrIS is characterized by surface (i.e., wet vs. dry) and elevation (i.e., 500-2000 m, 2000 m and greater) conditions over the summer season from 1 June to 31 August. Notably, the visible-wavelength declining reflectance trends identified in several bands of MODIS C5 data from previous studies are only slightly detected at reduced magnitude in the C6 versions over the dry snow area. Declining albedo in the wet snow and ice area remains over the MODIS record in the C6 product, albeit at a lower magnitude than obtained using C5 data. Further analyses of C6 spectral reflectance trends show both reflectance increases and decreases in select bands and regions, suggesting that several competing processes are contributing to Greenland Ice Sheet albedo change. Investigators using MODIS data for other ocean, atmosphere and/or land analyses are urged to consider similar re-examinations of trends previously established using C5 data.

Multitemporal cross-calibration of the Terra MODIS and Landsat 7 ETM+ reflective solar bands

USGS Publications Warehouse

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Chander, Gyanesh; Choi, Taeyoung

2013-01-01

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 (MODIS) 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 MODIS 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) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance 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 MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS 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 MODIS 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 MODIS 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 MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

Multitemporal Cross-Calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Changler, Gyanesh; Choi, Taeyoyung

2013-01-01

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 (MODIS) 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 MODIS 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) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance 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 MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS 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 MODIS 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 MODIS 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 MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data

USGS Publications Warehouse

Gu, Yingxin; Brown, Jesslyn F.; Miura, Tomoaki; van Leeuwen, Willem J.D.; Reed, Bradley C.

2010-01-01

This study introduces a new geographic framework, phenological classification, for the conterminous United States based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series data and a digital elevation model. The resulting pheno-class map is comprised of 40 pheno-classes, each having unique phenological and topographic characteristics. Cross-comparison of the pheno-classes with the 2001 National Land Cover Database indicates that the new map contains additional phenological and climate information. The pheno-class framework may be a suitable basis for the development of an Advanced Very High Resolution Radiometer (AVHRR)-MODIS NDVI translation algorithm and for various biogeographic studies.

The use of the Sonoran Desert as a pseudo-invariant site for optical sensor cross-calibration and long-term stability monitoring

USGS Publications Warehouse

Angal, A.; Chander, Gyanesh; Choi, Taeyoung; Wu, Aisheng; Xiong, Xiaoxiong

2010-01-01

The Sonoran Desert is a large, flat, pseudo-invariant site near the United States-Mexico border. It is one of the largest and hottest deserts in North America, with an area of 311,000 square km. This site is particularly suitable for calibration purposes because of its high spatial and spectral uniformity and reasonable temporal stability. This study uses measurements from four different sensors, Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), Aqua MODIS, and Landsat 5 (L5) Thematic Mapper (TM), to assess the suitability of this site for long-term stability monitoring and to evaluate the “radiometric calibration differences” between spectrally matching bands of all four sensors. In general, the drift in the top-of-atmosphere (TOA) reflectance of each sensor over a span of nine years is within the specified calibration uncertainties. Monthly precipitation measurements of the Sonoran Desert region were obtained from the Global Historical Climatology Network (GHCN), and their effects on the retrieved TOA reflectances were evaluated. To account for the combined uncertainties in the TOA reflectance due to the surface and atmospheric Bi-directional Reflectance Distribution Function (BRDF), a semi-empirical BRDF model has been adopted to monitor and reduce the impact of illumination geometry differences on the retrieved TOA reflectances. To evaluate calibration differences between the MODIS and Landsat sensors, correction for spectral response differences using a hyperspectral sensor is also demonstrated.

Satellite Ocean Biology: Past, Present, Future

NASA Technical Reports Server (NTRS)

McClain, Charles R.

2012-01-01

Since 1978 when the first satellite ocean color proof-of-concept sensor, the Nimbus-7 Coastal Zone Color Scanner, was launched, much progress has been made in refining the basic measurement concept and expanding the research applications of global satellite time series of biological and optical properties such as chlorophyll-a concentrations. The seminar will review the fundamentals of satellite ocean color measurements (sensor design considerations, on-orbit calibration, atmospheric corrections, and bio-optical algorithms), scientific results from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate resolution Imaging Spectroradiometer (MODIS) missions, and the goals of future NASA missions such as PACE, the Aerosol, Cloud, Ecology (ACE), and Geostationary Coastal and Air Pollution Events (GeoCAPE) missions.

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

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-daily coverage of the Earth's surface, MODIS provides comprehensive measurements that enable scientists and policy makers to better understand and effectively manage the natural resources on both regional and global scales. Terra, the first large multisensor EOS satellite, is operated in a 10:30 am (local equatorial crossing time, descending southwards) polar orbit. Aqua, the second multisensor EOS satellite is operated in a 1:30 pm (local equatorial crossing time, ascending northwards) polar orbit. With complementing morning and afternoon observations, the Terra and Aqua MODIS, together with other sensors housed on both satellites, have greatly improved our understanding of the dynamics of the global environmental system.

Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions

NASA Astrophysics Data System (ADS)

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

2018-05-01

In addition to the standard resolution product (10 km), the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) data release included a higher resolution (3 km). Other than accommodations for the two different resolutions, the 10 and 3 km Dark Target (DT) algorithms are basically the same. In this study, we perform global validation of the higher-resolution aerosol optical depth (AOD) over global land by comparing against AErosol RObotic NETwork (AERONET) measurements. The MODIS-AERONET collocated data sets consist of 161 410 high-confidence AOD pairs from 2000 to 2015 for Terra MODIS and 2003 to 2015 for Aqua MODIS. We find that 62.5 and 68.4 % of AODs retrieved from Terra MODIS and Aqua MODIS, respectively, fall within previously published expected error bounds of ±(0.05 + 0.2 × AOD), with a high correlation (R = 0.87). The scatter is not random, but exhibits a mean positive bias of ˜ 0.06 for Terra and ˜ 0.03 for Aqua. These biases for the 3 km product are approximately 0.03 larger than the biases found in similar validations of the 10 km product. The validation results for the 3 km product did not have a relationship to aerosol loading (i.e., true AOD), but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with Terra MODIS showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

Daily MODIS data trends of hurricane-induced forest impact and early recovery

USGS Publications Warehouse

Ramsey, Elijah W.; Spruce, Joseph; Rangoonwala, Amina; Suzuoki, Yukihiro; Smoot, James; Gasser, Jerry; Bannister, Terri

2011-01-01

We studied the use of daily satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors to assess wetland forest damage and recovery from Hurricane Katrina (29 August 2005 landfall). Processed MODIS daily vegetation index (VI) trends were consistent with previously determined impact and recovery patterns provided by the "snapshot" 25 m Landsat Thematic Mapper optical and RADARSAT-1 synthetic aperture radar satellite data. Phenological trends showed high 2004 and 2005 pre-hurricane temporal correspondence within bottomland hardwood forest communities, except during spring green-up, and temporal dissimilarity between these hardwoods and nearby cypress-tupelo swamp forests (Taxodium distichum [baldcypress] and Nyssa aquatica [water tupelo]). MODIS VI trend analyses established that one year after impact, cypress-tupelo and lightly impacted hardwood forests had recovered to near pre-hurricane conditions. In contrast, canopy recovery lagged in the moderately and severely damaged hardwood forests, possibly reflecting regeneration of pre-hurricane species and stand-level replacement by invasive trees.

Cloud and Aerosol Properties, Precipitable Water, and Profiles of Temperature and Water Vapor from MODIS

NASA Technical Reports Server (NTRS)

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.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an earth-viewing sensor that flies on the Earth Observing System (EOS) Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS 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. MODIS 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.

Adjustments to the MODIS Terra Radiometric Calibration and Polarization Sensitivity in the 2010 Reprocessing

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2011-01-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) 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 MODIS 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 MODIS Terra ocean color products are now in excellent agreement with those of SeaWiFS and MODIS Aqua, 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.

Infrared Retrievals of Ice Cloud Properties and Uncertainties with an Optimal Estimation Retrieval Method

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.

2014-12-01

We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.

Absolute Calibration of Optical Satellite Sensors Using Libya 4 Pseudo Invariant Calibration Site

NASA Technical Reports Server (NTRS)

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

2014-01-01

The objective of this paper is to report the improvements in an empirical absolute calibration model developed at South Dakota State University using Libya 4 (+28.55 deg, +23.39 deg) pseudo invariant calibration site (PICS). The approach was based on use of the Terra MODIS as the radiometer to develop an absolute calibration model for the spectral channels covered by this instrument from visible to shortwave infrared. Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm, was used to extend the model to cover visible and near-infrared regions. A simple Bidirectional Reflectance Distribution function (BRDF) model was generated using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations over Libya 4 and the resulting model was validated with nadir data acquired from satellite sensors such as Aqua MODIS and Landsat 7 (L7) Enhanced Thematic Mapper (ETM+). The improvements in the absolute calibration model to account for the BRDF due to off-nadir measurements and annual variations in the atmosphere are summarized. BRDF models due to off-nadir viewing angles have been derived using the measurements from EO-1 Hyperion. In addition to L7 ETM+, measurements from other sensors such as Aqua MODIS, UK-2 Disaster Monitoring Constellation (DMC), ENVISAT Medium Resolution Imaging Spectrometer (MERIS) and Operational Land Imager (OLI) onboard Landsat 8 (L8), which was launched in February 2013, were employed to validate the model. These satellite sensors differ in terms of the width of their spectral bandpasses, overpass time, off-nadir-viewing capabilities, spatial resolution and temporal revisit time, etc. The results demonstrate that the proposed empirical calibration model has accuracy of the order of 3% with an uncertainty of about 2% for the sensors used in the study.

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: Part III. Using Combined PCA to Compare Spatiotemporal Variability of MODIS, MISR and OMI Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Satellite measurements of global aerosol properties are very useful in constraining aerosol parameterization in climate models. The reliability of different data sets in representing global and regional aerosol variability becomes an essential question. In this study, we present the results of a comparison using combined principal component analysis (CPCA), applied to monthly mean, mapped (Level 3) aerosol optical depth (AOD) product from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Ozone Monitoring Instrument (OMI). This technique effectively finds the common space-time variability in the multiple data sets by decomposing the combined AOD field. The results suggest that all of the sensors capture the globally important aerosol regimes, including dust, biomass burning, pollution, and mixed aerosol types. Nonetheless, differences are also noted. Specifically, compared with MISR and OMI, MODIS variability is significantly higher over South America, India, and the Sahel. MODIS deep blue AOD has a lower seasonal variability in North Africa, accompanied by a decreasing trend that is not found in either MISR or OMI AOD data. The narrow swath of MISR results in an underestimation of dust variability over the Taklamakan Desert. The MISR AOD data also exhibit overall lower variability in South America and the Sahel. OMI does not capture the Russian wild fire in 2010 nor the phase shift in biomass burning over East South America compared to Central South America, likely due to cloud contamination and the OMI row anomaly. OMI also indicates a much stronger (boreal) winter peak in South Africa compared with MODIS and MISR.

The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products

NASA Technical Reports Server (NTRS)

Huang, Dong; Yang, Wenze; Tan, Bin; Rautiainen, Miina; Zhang, Ping; Hu, Jiannan; Shabanov, Nikolay V.; Linder, Sune; Knyazikhin, Yuri; Myneni, Ranga B.

2006-01-01

The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.

MODIS Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003

NASA Technical Reports Server (NTRS)

Fargion, Giulietta S.; McClain, Charles R.

2003-01-01

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 (MODIS) on the Earth Observing System (EOS) Terra platform (similar evaluations of MODIS/Aqua 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.

Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites

USGS Publications Warehouse

Chander, G.; Xiong, X.(J.); Choi, T.(J.); Angal, A.

2010-01-01

The ability to detect and quantify changes in the Earth's environment depends on sensors that can provide calibrated, consistent measurements of the Earth's surface features through time. A critical step in this process is to put image data from different sensors onto a common radiometric scale. This work focuses on monitoring the long-term on-orbit calibration stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using the Committee on Earth Observation Satellites (CEOS) reference standard pseudo-invariant test sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5). These sites have been frequently used as radiometric targets because of their relatively stable surface conditions temporally. This study was performed using all cloud-free calibrated images from the Terra MODIS and the L7 ETM+ sensors, acquired from launch to December 2008. Homogeneous regions of interest (ROI) were selected in the calibrated images and the mean target statistics were derived from sensor measurements in terms of top-of-atmosphere (TOA) reflectance. For each band pair, a set of fitted coefficients (slope and offset) is provided to monitor the long-term stability over very stable pseudo-invariant test sites. The average percent differences in intercept from the long-term trends obtained from the ETM + TOA reflectance estimates relative to the MODIS for all the CEOS reference standard test sites range from 2.5% to 15%. This gives an estimate of the collective differences due to the Relative Spectral Response (RSR) characteristics of each sensor, bi-directional reflectance distribution function (BRDF), spectral signature of the ground target, and atmospheric composition. The lifetime TOA reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.4% per year in its TOA reflectance over the CEOS reference standard test sites.

Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data

PubMed Central

Scharlemann, Jörn P. W.; Benz, David; Hay, Simon I.; Purse, Bethan V.; Tatem, Andrew J.; Wint, G. R. William; Rogers, David J.

2008-01-01

Background Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling. PMID:18183289

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data.

PubMed

Scharlemann, Jörn P W; Benz, David; Hay, Simon I; Purse, Bethan V; Tatem, Andrew J; Wint, G R William; Rogers, David J

2008-01-09

Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.

Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

NASA Astrophysics Data System (ADS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-04-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOS-Chem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-01-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Utility of BRDF Models for Estimating Optimal View Angles in Classification of Remotely Sensed Images

NASA Technical Reports Server (NTRS)

Valdez, P. F.; Donohoe, G. W.

1997-01-01

Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.

Harmonizing Landsat and Sentinel-2 Reflectances for Better Land Monitoring

NASA Technical Reports Server (NTRS)

Masek, Jeffrey; Vermote, Eric; Franch, Belen; Roger, Jean-Claude; Skakun, Sergii; Claverie, Martin; Dungan, Jennifer

2016-01-01

When combined, Landsat and ESA Sentinel-2 observations can provide 2-4 day coverage for the global land area. A collaboration among NASA GSFC (Goddard Space Flight Center), University of Maryland, and NASA Ames has developed a processing chain to create seamless, "harmonized" reflectance products using standardized atmospheric correction, BRDF (Bidirectional Reflectance Distribution Function) adjustment, spectral bandpass adjustment, and gridding algorithms. These products point the way to a "30-m MODIS (Moderate Resolution Imaging Spectroradiometer)" capability for agricultural and ecosystem monitoring by leveraging international sensors.

Estimating Morning Change in Land Surface Temperature from MODIS Day/Night Observations: Applications for Surface Energy Balance Modeling.

PubMed

Hain, Christopher R; Anderson, Martha C

2017-10-16

Observations of land surface temperature (LST) are crucial for the monitoring of surface energy fluxes from satellite. Methods that require high temporal resolution LST observations (e.g., from geostationary orbit) can be difficult to apply globally because several geostationary sensors are required to attain near-global coverage (60°N to 60°S). While these LST observations are available from polar-orbiting sensors, providing global coverage at higher spatial resolutions, the temporal sampling (twice daily observations) can pose significant limitations. For example, the Atmosphere Land Exchange Inverse (ALEXI) surface energy balance model, used for monitoring evapotranspiration and drought, requires an observation of the morning change in LST - a quantity not directly observable from polar-orbiting sensors. Therefore, we have developed and evaluated a data-mining approach to estimate the mid-morning rise in LST from a single sensor (2 observations per day) of LST from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Aqua platform. In general, the data-mining approach produced estimates with low relative error (5 to 10%) and statistically significant correlations when compared against geostationary observations. This approach will facilitate global, near real-time applications of ALEXI at higher spatial and temporal coverage from a single sensor than currently achievable with current geostationary datasets.

Can MODIS detect trends in aerosol optical depth over land?

NASA Astrophysics Data System (ADS)

Fan, Xuehua; Xia, Xiang'ao; Chen, Hongbin

2018-02-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Aqua satellite has been collecting valuable data about the Earth system for more than 14 years, and one of the benefits of this is that it has made it possible to detect the long-term variation in aerosol loading across the globe. However, the long-term aerosol optical depth (AOD) trends derived from MODIS need careful validation and assessment, especially over land. Using AOD products with at least 70 months' worth of measurements collected during 2002-15 at 53 Aerosol Robotic Network (AERONET) sites over land, Mann-Kendall (MK) trends in AOD were derived and taken as the ground truth data for evaluating the corresponding results from MODIS onboard Aqua. The results showed that the AERONET AOD trends over all sites in Europe and North America, as well as most sites in Africa and Asia, can be reproduced by MODIS/Aqua. However, disagreement in AOD trends between MODIS and AERONET was found at a few sites in Australia and South America. The AOD trends calculated from AERONET instantaneous data at the MODIS overpass times were consistent with those from AERONET daily data, which suggests that the AOD trends derived from satellite measurements of 1-2 overpasses may be representative of those from daily measurements.

Scientific impact of MODIS C5 calibration degradation and C6+ improvements

NASA Astrophysics Data System (ADS)

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.

2014-12-01

The Collection 6 (C6) MODIS (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) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångström exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance 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 MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra-Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (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 the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1-B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.;

Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Cho, H.; Choi, M.

2013-12-01

Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

Validation and understanding of Moderate Resolution Imaging Spectroradiometer aerosol products (C5) using ground-based measurements from the handheld Sun photometer network in China

Treesearch

Zhanqing Li; Feng Niu; Kwon-Ho Lee; Jinyuan Xin; Wei Min Hao; Bryce L. Nordgren; Yuesi Wang; Pucai Wang

2007-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) currently provides the most extensive aerosol retrievals on a global basis, but validation is limited to a small number of ground stations. This study presents a comprehensive evaluation of Collection 4 and 5 MODIS aerosol products using ground measurements from the Chinese Sun Hazemeter Network (CSHNET). The...

Variations of Global Terrestrial Primary Production Observed by Moderate Resolution Imaging Spectroradiometer (MODIS) From 2000 to 2005

NASA Astrophysics Data System (ADS)

Zhao, M.; Running, S.; Heinsch, F. A.

2006-12-01

Since the first Earth Observing System (EOS) satellite Terra was launched in December 1999 and Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra began to provide data in February 2000, we have had six-year MODIS global 1-km terrestrial Gross and Net Primary Production (GPP &NPP) datasets. In this article, we present the variations (seasonality and inter-annual variability) of global GPP/NPP from the latest improved Collection 4.8 (C4.8) MODIS datasets for the past six-year (2000 - 2005), as well as improvements of the algorithm, validations of GPP and NPP. Validation results show that the C4.8 data have higher accuracy and quality than the previous version. Analyses of the variations in GPP/NPP show that GPP not only can reflect strong seasonality of photosynthesis activities by plants in mid- and high-latitude, but importantly, can reveal enhanced growth of Amazon rainforests during dry season, consistent with the reports by Huete et al. (2006) on GRL. Spatially, plants over mid- and high-latitude (north to 22.5°N) are the major contributor of global GPP seasonality. Inter-annual variability of MODIS NPP for 2000 - 2005 reveals the negative effects of major droughts on carbon sequestration at the regional and continental scales. A striking phenomenon is that the severe drought in 2005 over Amazon reduced NPP, indicating water availability becomes the dominant limiting factor rather than solar radiation under normal conditions. GMAO and NCEP driven global total NPPs have the similar interannual anomalies, and they generally follow the inverted CO2 growth rate anomaly with correlation of 0.85 and 0.91, respectively, which are higher than the correlation of 0.7 found by Nemani et al. (2003) on Science. Though there are only 6 years of MODIS data, results show that global NPP decreased from 2000 to 2005, and spatially most decreased NPP areas are in tropic and south hemisphere.

Radiometric Characterization of Hyperspectral Imagers using Multispectral Sensors

NASA Technical Reports Server (NTRS)

McCorkel, Joel; Kurt, Thome; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

2009-01-01

The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these test sites are not always successful due to weather and funding availability. Therefore, RSG has also automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor, This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral a imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (M0DIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of M0DlS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most brands as well as similar agreement between results that employ the different MODIS sensors as a reference.

Evaluation on Radiometric Capability of Chinese Optical Satellite Sensors.

PubMed

Yang, Aixia; Zhong, Bo; Wu, Shanlong; Liu, Qinhuo

2017-01-22

The radiometric capability of on-orbit sensors should be updated on time due to changes induced by space environmental factors and instrument aging. Some sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS), have onboard calibrators, which enable real-time calibration. However, most Chinese remote sensing satellite sensors lack onboard calibrators. Their radiometric calibrations have been updated once a year based on a vicarious calibration procedure, which has affected the applications of the data. Therefore, a full evaluation of the sensors' radiometric capabilities is essential before quantitative applications can be made. In this study, a comprehensive procedure for evaluating the radiometric capability of several Chinese optical satellite sensors is proposed. In this procedure, long-term radiometric stability and radiometric accuracy are the two major indicators for radiometric evaluation. The radiometric temporal stability is analyzed by the tendency of long-term top-of-atmosphere (TOA) reflectance variation; the radiometric accuracy is determined by comparison with the TOA reflectance from MODIS after spectrally matching. Three Chinese sensors including the Charge-Coupled Device (CCD) camera onboard Huan Jing 1 satellite (HJ-1), as well as the Visible and Infrared Radiometer (VIRR) and Medium-Resolution Spectral Imager (MERSI) onboard the Feng Yun 3 satellite (FY-3) are evaluated in reflective bands based on this procedure. The results are reasonable, and thus can provide reliable reference for the sensors' application, and as such will promote the development of Chinese satellite data.

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.

Sun glint requirement for the remote detection of surface oil films

NASA Astrophysics Data System (ADS)

Sun, Shaojie; Hu, Chuanmin

2016-01-01

Natural oil slicks in the western Gulf of Mexico are used to determine the sun glint threshold required for optical remote sensing of oil films. The threshold is determined using the same-day image pairs collected by Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (MODIST), MODIS Aqua (MODISA), and Visible Infrared Imaging Radiometer Suite (VIIRS) (N = 2297 images) over the same oil slick locations where at least one of the sensors captures the oil slicks. For each sensor, statistics of sun glint strengths, represented by the normalized glint reflectance (LGN, sr-1), when oil slicks can and cannot be observed are generated. The LGN threshold for oil film detections is determined to be 10-5-10-6 sr-1 for MODIST and MODISA, and 10-6-10-7 sr-1 for VIIRS. Below these thresholds, no oil films can be detected, while above these thresholds, oil films can always be detected except near the critical-angle zone where oil slicks reverse their contrast against the background water.

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.

Assessment of MODIS On-Orbit Calibration Using a Deep Convective Cloud Technique

NASA Technical Reports Server (NTRS)

Mu, Qiaozhen; Wu, Aisheng; Chang, Tiejun; Angal, Amit; Link, Daniel; Xiong, Xiaoxiong; Doelling, David R.; Bhatt, Rajendra

2016-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) sensors onboard Terra and Aqua satellites are calibrated on-orbit with a solar diffuser (SD) for the reflective solar bands (RSB). The MODIS sensors are operating beyond their designed lifetime and hence present a major challenge to maintain the calibration accuracy. The degradation of the onboard SD is tracked by a solar diffuser stability monitor (SDSM) over a wavelength range from 0.41 to 0.94 micrometers. Therefore, any degradation of the SD beyond 0.94 micrometers cannot be captured by the SDSM. The uncharacterized degradation at wavelengths beyond this limit could adversely affect the Level 1B (L1B) product. To reduce the calibration uncertainties caused by the SD degradation, invariant Earth-scene targets are used to monitor and calibrate the MODIS L1B product. The use of deep convective clouds (DCCs) is one such method and particularly significant for the short-wave infrared (SWIR) bands in assessing their long-term calibration stability. In this study, we use the DCC technique to assess the performance of the Terra and Aqua MODIS Collection-6 L1B for RSB 1 3- 7, and 26, with spectral coverage from 0.47 to 2.13 micrometers. Results show relatively stable trends in Terra and Aqua MODIS reflectance for most bands. Careful attention needs to be paid to Aqua band 1, Terra bands 3 and 26 as their trends are larger than 1% during the study time period. We check the feasibility of using the DCC technique to assess the stability in MODIS bands 17-19. The assessment test on response versus scan angle (RVS) calibration shows substantial trend difference for Aqua band 1between different angles of incidence (AOIs). The DCC technique can be used to improve the RVS calibration in the future.

Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes

NASA Astrophysics Data System (ADS)

Sayer, Andrew M.; Hsu, N. Christina; Bettenhausen, Corey; Holz, Robert E.; Lee, Jaehwa; Quinn, Greg; Veglio, Paolo

2017-04-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) is being used to continue the record of Earth Science observations and data products produced routinely from National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. However, the absolute calibration of VIIRS's reflected solar bands is thought to be biased, leading to offsets in derived data products such as aerosol optical depth (AOD) as compared to when similar algorithms are applied to different sensors. This study presents a cross-calibration of these VIIRS bands against MODIS Aqua over dark water scenes, finding corrections to the NASA VIIRS Level 1 (version 2) reflectances between approximately +1 and -7 % (dependent on band) are needed to bring the two into alignment (after accounting for expected differences resulting from different band spectral response functions), and indications of relative trending of up to ˜ 0.35 % per year in some bands. The derived calibration gain corrections are also applied to the VIIRS reflectance and then used in an AOD retrieval, and they are shown to decrease the bias and total error in AOD across the mid-visible spectral region compared to the standard VIIRS NASA reflectance calibration. The resulting AOD bias characteristics are similar to those of NASA MODIS AOD data products, which is encouraging in terms of multi-sensor data continuity.

Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda.

PubMed

Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E

2014-12-15

In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions.

Cross-Calibration between ASTER and MODIS Visible to Near-Infrared Bands for Improvement of ASTER Radiometric Calibration

PubMed Central

Tsuchida, Satoshi; Thome, Kurtis

2017-01-01

Radiometric cross-calibration between the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) has been partially used to derive the ASTER radiometric calibration coefficient (RCC) curve as a function of date on visible to near-infrared bands. However, cross-calibration is not sufficiently accurate, since the effects of the differences in the sensor’s spectral and spatial responses are not fully mitigated. The present study attempts to evaluate radiometric consistency across two sensors using an improved cross-calibration algorithm to address the spectral and spatial effects and derive cross-calibration-based RCCs, which increases the ASTER calibration accuracy. Overall, radiances measured with ASTER bands 1 and 2 are on averages 3.9% and 3.6% greater than the ones measured on the same scene with their MODIS counterparts and ASTER band 3N (nadir) is 0.6% smaller than its MODIS counterpart in current radiance/reflectance products. The percentage root mean squared errors (%RMSEs) between the radiances of two sensors are 3.7, 4.2, and 2.3 for ASTER band 1, 2, and 3N, respectively, which are slightly greater or smaller than the required ASTER radiometric calibration accuracy (4%). The uncertainty of the cross-calibration is analyzed by elaborating the error budget table to evaluate the International System of Units (SI)-traceability of the results. The use of the derived RCCs will allow further reduction of errors in ASTER radiometric calibration and subsequently improve interoperability across sensors for synergistic applications. PMID:28777329

The Use of MODIS NDVI Data for Characterizing Cropland Across the Great Lakes Basin

EPA Science Inventory

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides new opportunities for characterizing land-cover (LC) to support monitoring and assessment studies at watershed, regional and global scales. This research evaluated the potential for using the MODIS Normalized Diff...

Accessing and Understanding MODIS Data

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Jenkerson, Calli B.; Jodha, Siri

2003-01-01

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. Aqua, the second satellite from the series of EOS constellation, was launched in May 2002. Both satellites carry the MODerate resolution Imaging Spectroradiometer (MODIS) instrument. MODIS 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 MODIS sensors present new challenges to remote sensing scientists due to specialized production level, data format, and map projection. MODIS data are distributed as calibrated radiances and as higher level products such as: surface reflectance, 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. MODIS 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.

Evaluation of radiative fluxes over the north Indian Ocean

NASA Astrophysics Data System (ADS)

Ramesh Kumar, M. R.; Pinker, Rachel T.; Mathew, Simi; Venkatesan, R.; Chen, W.

2018-05-01

Radiative fluxes are a key component of the surface heat budget of the oceans. Yet, observations over oceanic region are sparse due to the complexity of radiation measurements; moreover, certain oceanic regions are substantially under-sampled, such as the north Indian Ocean. The National Institute of Ocean Technology, Chennai, India, under its Ocean Observation Program has deployed an Ocean Moored Network for the Northern Indian Ocean (OMNI) both in the Arabian Sea and the Bay of Bengal. These buoys are equipped with sensors to measure radiation and rainfall, in addition to other basic meteorological parameters. They are also equipped with sensors to measure sub-surface currents, temperature, and conductivity from the surface up to a depth of 500 m. Observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the National Aeronautics and Space Administration (NASA) AQUA and TERRA satellites have been used to infer surface radiation over the north Indian Ocean. In this study, we focus only on the shortwave (SW↓) fluxes. The evaluations of the MODIS-based SW↓ fluxes against the RAMA observing network have shown a very good agreement between them, and therefore, we use the MODIS-derived fluxes as a reference for the evaluation of the OMNI observations. In an early deployment of the OMNI buoys, the radiation sensors were placed at 2 m above the sea surface; subsequently, the height of the sensors was raised to 3 m. In this study, we show that there was a substantial improvement in the agreement between the buoy observations and the satellite estimates, once the sensors were raised to higher levels. The correlation coefficient increased from 0.87 to 0.93, and both the bias and standard deviations decreased substantially.

Producing Global Science Products for the Moderate Resolution Imaging Spectroradiometer (MODIS) in MODAPS

NASA Technical Reports Server (NTRS)

Masuoka, Edward J.; Tilmes, Curt A.; Ye, Gang; Devine, Neal; Smith, David E. (Technical Monitor)

2000-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) was launched on NASA's EOS-Terra spacecraft December 1999. With 36 spectral bands covering the visible, near wave and short wave infrared. MODIS produces over 40 global science data products, including sea surface temperature, ocean color, cloud properties, vegetation indices land surface temperature and land cover change. The MODIS Data Processing System (MODAPS) produces 400 GB/day of global MODIS science products from calibrated radiances generated in the Earth Observing System Data and Information System (EOSDIS). The science products are shipped to the EOSDIS for archiving and distribution to the public. An additional 200 GB of products are shipped each day to MODIS team members for quality assurance and validation of their products. In the sections that follow, we will describe the architecture of the MODAPS, identify processing bottlenecks encountered in scaling MODAPS from 50 GB/day backup system to a 400 GB/day production system and discuss how these were handled.

Super Typhoon Halong off Taiwan

NASA Technical Reports Server (NTRS)

2002-01-01

On July 14, 2002, Super Typhoon Halong was east of Taiwan (left edge) in the western Pacific Ocean. At the time this image was taken the storm was a Category 4 hurricane, with maximum sustained winds of 115 knots (132 miles per hour), but as recently as July 12, winds were at 135 knots (155 miles per hour). Halong has moved northwards and pounded Okinawa, Japan, with heavy rain and high winds, just days after tropical Storm Chataan hit the country, creating flooding and killing several people. The storm is expected to be a continuing threat on Monday and Tuesday. This image was acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite on July 14, 2002. Please note that the high-resolution scene provided here is 500 meters per pixel. For a copy of the scene at the sensor's fullest resolution, visit the MODIS Rapid Response Image Gallery. Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

Argentina from MODIS

NASA Technical Reports Server (NTRS)

2002-01-01

This Moderate-resolution Imaging Spectroradiometer (MODIS) 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, MODIS Land Group, NASA GSFC)

Earth-observing satellite intercomparison using the Radiometric Calibration Test Site at Railroad Valley

NASA Astrophysics Data System (ADS)

Czapla-Myers, Jeffrey; McCorkel, Joel; Anderson, Nikolaus; Biggar, Stuart

2018-01-01

This paper describes the current ground-based calibration results of Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi National Polar orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS), and Sentinel-2A Multispectral Instrument (MSI), using an automated suite of instruments located at Railroad Valley, Nevada, USA. The period of this study is 2012 to 2016 for MODIS, VIIRS, and ETM+, 2013 to 2016 for OLI, and 2015 to 2016 for MSI. The current results show that all sensors agree with the Radiometric Calibration Test Site (RadCaTS) to within ±5% in the solar-reflective regime, except for one band on VIIRS that is within ±6%. In the case of ETM+ and OLI, the agreement is within ±3%, and, in the case of MODIS, the agreement is within ±3.5%. MSI agrees with RadCaTS to within ±4.5% in all applicable bands.

A SOAP Web Service for accessing MODIS land product subsets

DOE Office of Scientific and Technical Information (OSTI.GOV)

SanthanaVannan, Suresh K; Cook, Robert B; Pan, Jerry Yun

2011-01-01

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 (MODIS) sensor on board NASA s Terra and Aqua 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 MODIS data make it difficult for users wanting to extract small but valuable amounts of information from the MODIS record. Tomore » 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 MODIS land products using Simple Object Access Protocol (SOAP). The ORNL DAAC MODIS 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 MODIS 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 MODIS land parameters for real time data integration into models, decision support tools or connect to workflow software. Information regarding the MODIS SOAP subsetting Web service is available on the World Wide Web (WWW) at http://daac.ornl.gov/modiswebservice.« less

Evaluation on Radiometric Capability of Chinese Optical Satellite Sensors

PubMed Central

Yang, Aixia; Zhong, Bo; Wu, Shanlong; Liu, Qinhuo

2017-01-01

The radiometric capability of on-orbit sensors should be updated on time due to changes induced by space environmental factors and instrument aging. Some sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS), have onboard calibrators, which enable real-time calibration. However, most Chinese remote sensing satellite sensors lack onboard calibrators. Their radiometric calibrations have been updated once a year based on a vicarious calibration procedure, which has affected the applications of the data. Therefore, a full evaluation of the sensors’ radiometric capabilities is essential before quantitative applications can be made. In this study, a comprehensive procedure for evaluating the radiometric capability of several Chinese optical satellite sensors is proposed. In this procedure, long-term radiometric stability and radiometric accuracy are the two major indicators for radiometric evaluation. The radiometric temporal stability is analyzed by the tendency of long-term top-of-atmosphere (TOA) reflectance variation; the radiometric accuracy is determined by comparison with the TOA reflectance from MODIS after spectrally matching. Three Chinese sensors including the Charge-Coupled Device (CCD) camera onboard Huan Jing 1 satellite (HJ-1), as well as the Visible and Infrared Radiometer (VIRR) and Medium-Resolution Spectral Imager (MERSI) onboard the Feng Yun 3 satellite (FY-3) are evaluated in reflective bands based on this procedure. The results are reasonable, and thus can provide reliable reference for the sensors’ application, and as such will promote the development of Chinese satellite data. PMID:28117745

Applications of spectral band adjustment factors (SBAF) for cross-calibration

USGS Publications Warehouse

Chander, Gyanesh

2013-01-01

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface acquired from multiple spaceborne imaging sensors. However, an integrated global observation framework requires an understanding of how land surface processes are seen differently by various sensors. This is particularly true for sensors acquiring data in spectral bands whose relative spectral responses (RSRs) are not similar and thus may produce different results while observing the same target. The intrinsic offsets between two sensors caused by RSR mismatches can be compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of the two sensors. The motivation of this work comes from the need to compensate the spectral response differences of multispectral sensors in order to provide a more accurate cross-calibration between the sensors. In this paper, radiometric cross-calibration of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors was performed using near-simultaneous observations over the Libya 4 pseudoinvariant calibration site in the visible and near-infrared spectral range. The RSR differences of the analogous ETM+ and MODIS spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) reflectances between the two sensors over their lifetimes. The average percent differences in the long-term trends ranged from $-$5% to $+$6%. The RSR compensated ETM+ TOA reflectance (ETM+$^{ast}$) measurements were then found to agree with MODIS TOA reflectance to within 5% for all bands when Earth Observing-1 Hy- erion hyperspectral data were used to produce the SBAFs. These differences were later reduced to within 1% for all bands (except band 2) by using Environmental Satellite Scanning Imaging Absorption Spectrometer for Atmospheric Cartography hyperspectral data to produce the SBAFs.

Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations

USGS Publications Warehouse

Chander, Gyanesh; Angal, Amit; Choi, Taeyoung; Xiong, Xiaoxiong

2013-01-01

The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites. The results indicate that the TOA reflectance measurements for ALI agree with those of ETM+ and MODIS to within 5% after the application of SBAF.

AOD trends during 2001-2010 from observations and model simulations

NASA Astrophysics Data System (ADS)

Pozzer, A.; de Meij, A.; Yoon, J.; Tost, H.; Georgoulias, A. K.; Astitha, M.

2015-05-01

The aerosol optical depth (AOD) trend between 2001 and 2010 is estimated globally and regionally from observations and results from simulations with the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model. Although interannual variability is applied only to anthropogenic and biomass-burning emissions, the model is able to quantitatively reproduce the AOD trends as observed by the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor, while some discrepancies are found when compared to MISR (Multi-angle Imaging SpectroRadiometer) and SeaWIFS (Sea-viewing Wide Field-of-view Sensor) observations. Thanks to an additional simulation without any change in emissions, it is shown that decreasing AOD trends over the US and Europe are due to the decrease in the emissions, while over the Sahara Desert and the Middle East region, the meteorological changes play a major role. Over Southeast Asia, both meteorology and emissions changes are equally important in defining AOD trends. Additionally, decomposing the regional AOD trends into individual aerosol components reveals that the soluble components are the most dominant contributors to the total AOD, as their influence on the total AOD is enhanced by the aerosol water content.

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

NASA Technical Reports Server (NTRS)

King, M. D.

2003-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

Global Aerosol Remote Sensing from MODIS

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Martins, Jose V.; Lau, William K. M. (Technical Monitor)

2002-01-01

The physical characteristics, composition, abundance, spatial distribution and dynamics of global aerosols are still very poorly known, and new data from satellite sensors have long been awaited to improve current understanding and to give a boost to the effort in future climate predictions. The derivation of aerosol parameters from the MODerate resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Earth Observing System (EOS) Terra and Aqua polar-orbiting satellites ushers in a new era in aerosol remote sensing from space. 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 (level 2) from MODIS daytime data. The MODIS aerosol algorithm employs different approaches to retrieve parameters over land and ocean surfaces, because of the inherent differences in the solar spectral radiance interaction with these 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 micron over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. To ensure the quality of these parameters, a substantial part of the Terra-MODIS aerosol products were validated globally and regionally, based on cross correlation with corresponding parameters derived from ground-based measurements from AERONET (AErosol RObotic NETwork) sun photometers. Similar validation efforts are planned for the Aqua-MODIS aerosol products. The MODIS level 2 aerosol products are operationally aggregated to generate global daily, eight-day (weekly), and monthly products at one-degree spatial resolution (level 3). MODIS aerosol data are used for the detailed study of local, regional, and global aerosol concentration, distribution, and temporal dynamics, as well as for radiative forcing calculations. We show several examples of these results and comparisons with model output.

On-Orbit Noise Characterization for MODIS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Xiong, X.; Xie, X.; Angal, A.

2008-01-01

Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) has operated successfully on-board the NASA Earth Observing System (EOS) Terra and EOS Aqua spacecraft. MODIS is a passive cross-track scanning radiometer that makes observations in 36 spectral bands with spectral wavelengths from visible (VIS) to long-wave infrared. MODIS bands 1-19 and 26 are the reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers. They are calibrated on-orbit using an on-board solar diffuser (SD) and a SD stability monitor (SDSM) system. For MODIS RSB, the level 1B calibration algorithm produces top of the atmosphere reflectance factors and radiances for every pixel of the Earth view. The sensor radiometric calibration accuracy, specified at each spectral band's typical scene radiance, is 2% for the RSB reflectance factors and 5% for the RSB radiances. Also specified at the typical scene radiance is the detector signal-to-noise ratio (SNR), a key sensor performance parameter that directly impacts its radiometric calibration accuracy and stability, as well as the image quality. This paper describes an on-orbit SNR characterization approach developed to evaluate and track MODIS RSB detector performance. In order to perform on-orbit SNR characterization, MODIS RSB detector responses to the solar illumination reflected from the SD panel must be corrected for factors due to variations of the solar angles and the SD bi-directional reflectance factor. This approach enables RSB SNR characterization to be performed at different response levels for each detector. On-orbit results show that both Terra and Aqua MODIS RSB detectors have performed well since launch. Except for a few noisy or inoperable detectors which were identified pre-launch, most RSB detectors continue to meet the SNR design requirements and are able to maintain satisfactory short-term stability. A comparison of on-orbit noise characterization results with results derived from pre-launch calibration and characterization are also provided.

On-Orbit Lunar Modulation Transfer Function Measurements for the Moderate Resolution Imaging Spectroradiometer

NASA Technical Reports Server (NTRS)

Choi, Taeyong; Xiong, Xiaoxiong; Wang, Zhipeng

2013-01-01

Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability.

MODIS tasselled cap: land cover characteristics expressed through transformed MODIS data

Treesearch

S. E. Lobser; W. B. Cohen

2007-01-01

The tasselled cap concept is extended to Moderate Resolution Imaging Spectroradiometer (MODIS) Nadir BRDF-Adjusted Reflectance (NBAR, MOD43) data. The transformation is based on a rigid rotation of principal component axes (PCAs) derived from a global sample spanning one full year of NBAR 16-day composites. To provide a standard for MODIS tasselled cap axes, we...

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico.

PubMed

Jarchow, Christopher J; Didan, Kamel; Barreto-Muñoz, Armando; Nagler, Pamela L; Glenn, Edward P

2018-05-13

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000⁻2011), 8 (2013⁻2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013⁻2016) to MODIS EVI (2000⁻2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R² = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R² = 0.27) and riparian vegetation (R² = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R² = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area.

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.

Inter-Comparison of MODIS and VIIRS Vegetation Indices Using One-Year Global Data

NASA Astrophysics Data System (ADS)

Miura, T.; Muratsuchi, J.; Obata, K.; Kato, A.; Vargas, M.; Huete, A. R.

2016-12-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor series of the Joint Polar Satellite System program is slated to continue the highly calibrated data stream initiated with the Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. A number of geophysical products are being/to be produced from VIIRS data, including the "Top-of-the-Atmosphere (TOA)" Normalized Difference Vegetation Index (NDVI), "Top-of-Canopy (TOC)" Enhanced Vegetation Index (EVI), and TOC NDVI. In this study, we cross-compared vegetation indices (VIs) from the first VIIRS sensor aboard the Suomi National Polar-orbiting Partnership satellite with the Aqua MODIS counterparts using one-year global data. This study was aimed at developing a thorough understanding of radiometric compatibility between the two VI datasets across globe, seasons, a range of viewing angle, and land cover types. VIIRS and MODIS VI data of January-December 2015 were obtained at monthly intervals when their orbital tracks coincided. These data were projected and spatially-aggregated into a .0036-degree grid while screening for cloud and aerosol contaminations using their respective quality flags. VIIRS-MODIS observation pairs with near-identical sun-target-view angles were extracted from each of these monthly image pairs for cross-comparison. The four VIs of TOA NDVI, TOC NDVI, TOC EVI, and TOC EVI2 (a two-band version of the EVI) were analyzed. Between MODIS and VIIRS, TOA NDVI, TOC NDVI, and TOC EVI2 had very small overall mean differences (MD) of .014, .013, and .013 VI units, respectively, whereas TOC EVI had a slightly larger overall MD of 0.023 EVI units attributed to the disparate blue bands of the two sensors. These systematic differences were consistent across the one-year period. With respect to sun-target-viewing geometry, MDs were also consistent across the view zenith angle range, but always lower for forward- than backward-viewing geometry. MDs showed large land cover dependencies for TOA NDVI and TOC NDVI, varying 10 folds from .002 for forests to .02 for sparsely-vegetated areas. They were consistent across land cover types for TOC EVI and TOC EVI2. Future studies should address the impact of sun-target-view geometry on corss-sensor VI comparisons.

Noise Characterization and Performance of MODIS Thermal Emissive Bands

NASA Technical Reports Server (NTRS)

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

2016-01-01

The MODerate-resolution Imaging Spectroradiometer (MODIS) is a premier Earth-observing sensor of the early 21st century, flying onboard the Terra (T) and Aqua (A) spacecraft. Both instruments far exceeded their six-year design life and continue to operate satisfactorily for more than 15 and 13 years, respectively. The MODIS instrument is designed to make observations at nearly a 100% duty cycle covering the entire Earth in less than two days. The MODIS sensor characteristics include a spectral coverage from 0.41micrometers to 14.4 micrometers, of which those wavelengths ranging from 3.7 micrometers to 14.4 micrometers cover the thermal infrared region which is interspaced in 16 thermal emissive bands (TEBs). Each of the TEB contains ten detectors which record samples at a spatial resolution of 1 km. In order to ensure a high level of accuracy for the TEB-measured top-of-atmosphere radiances, an onboard blackbody (BB) is used as the calibration source. This paper reports the noise characterization and performance of the TEB on various counts. First, the stability of the onboard BB is evaluated to understand the effectiveness of the calibration source. Next, key noise metrics such as the noise equivalent temperature difference and the noise equivalent dn difference (NEdN) for the various TEBs are determined from multiple temperature sources. These sources include the nominally controlled BB temperature of 290 K for T-MODIS and 285 K for A-MODIS, as well as a BB warm up-cool down cycle that is performed over a temperature range from roughly 270 to 315 K. The space-view port that measures the background signal serves as a viable cold temperature source for measuring noise. In addition, a well characterized Earth-view target, the Dome Concordia site located in the Antarctic plateau, is used for characterizing the stability of the sensor, indirectly providing a measure of the NEdN. Based on this rigorous characterization, a list of the noisy and inoperable detectors for the TEB for both instruments is reported to provide the science user communities quality control of the MODIS Level 1B calibrated product.

Comparison of Coincident Multiangle Imaging Spectroradiometer and Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depths over Land and Ocean Scenes Containing Aerosol Robotic Network Sites

NASA Technical Reports Server (NTRS)

Abdou, Wedad A.; Diner, David J.; Martonchik, John V.; Bruegge, Carol J.; Kahn, Ralph A.; Gaitley, Barbara J.; Crean, Kathleen A.; Remer, Lorraine A.; Holben, Brent

2005-01-01

The Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), launched on 18 December 1999 aboard the Terra spacecraft, are making global observations of top-of-atmosphere (TOA) radiances. Aerosol optical depths and particle properties are independently retrieved from these radiances using methodologies and algorithms that make use of the instruments corresponding designs. This paper compares instantaneous optical depths retrieved from simultaneous and collocated radiances measured by the two instruments at locations containing sites within the Aerosol Robotic Network (AERONET). A set of 318 MISR and MODIS images, obtained during the months of March, June, and September 2002 at 62 AERONET sites, were used in this study. The results show that over land, MODIS aerosol optical depths at 470 and 660 nm are larger than those retrieved from MISR by about 35% and 10% on average, respectively, when all land surface types are included in the regression. The differences decrease when coastal and desert areas are excluded. For optical depths retrieved over ocean, MISR is on average about 0.1 and 0.05 higher than MODIS in the 470 and 660 nm bands, respectively. Part of this difference is due to radiometric calibration and is reduced to about 0.01 and 0.03 when recently derived band-to-band adjustments in the MISR radiometry are incorporated. Comparisons with AERONET data show similar patterns.

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-10-01

To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-07-01

To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångstrom Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ∼ 0.025), while reducing the differences between AE. We characterize algorithm retrievibility through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

NASA Technical Reports Server (NTRS)

Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne

2004-01-01

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

Global Characterization of Tropospheric Noise for InSAR Analysis Using MODIS Data

NASA Astrophysics Data System (ADS)

Yun, S.; Hensley, S.; Chaubell, M.; Fielding, E. J.; Pan, L.; Rosen, P. A.

2013-12-01

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 (MODIS) sensors mounted on Terra and Aqua 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 MODIS data were retrieved from OSCAR (Online Services for Correcting Atmosphere in Radar) server. MODIS 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).

The Normalization of Surface Anisotropy Effects Present in SEVIRI Reflectances by Using the MODIS BRDF Method

NASA Technical Reports Server (NTRS)

Proud, Simon Richard; Zhang, Qingling; Schaaf, Crystal; Fensholt, Rasmus; Rasmussen, Mads Olander; Shisanya, Chris; Mutero, Wycliffe; Mbow, Cheikh; Anyamba, Assaf; Pak, Ed;

Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development.

PubMed

Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N

2012-06-01

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance 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 MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS 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.

Remote Sensing of Aerosol and Aerosol Radiative Forcing of Climate from EOS Terra MODIS Instrument

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2000-01-01

The recent launch of EOS-Terra into polar orbit has begun to revolutionize remote sensing of aerosol and their effect on climate. Terra has five instruments, two of them,Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectro-Radiometer (MISR) are designed to monitor global aerosol in two different complementary ways. Here we shall discuss the use of the multispectral measurements of MODIS to derive: (1) the global distribution of aerosol load (and optical thickness) over ocean and land; (2) to measure the impact of aerosol on reflection of sunlight to space; and (3) to measure the ability of aerosol to absorb solar radiation. These measurements have direct applications on the understanding of the effect of aerosol on climate, the ability to predict climate change, and on the monitoring of dust episodes and man-made pollution. Principles of remote sensing of aerosol from MODIS will be discussed and first examples of measurements from MODIS will be provided.

Moderate Resolution Imaging Spectroradiometer (MODIS) MOD21 Land Surface Temperature and Emissivity Algorithm Theoretical Basis Document

NASA Technical Reports Server (NTRS)

Hulley, G.; Malakar, N.; Hughes, T.; Islam, T.; Hook, S.

2016-01-01

This document outlines the theory and methodology for generating the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 daily daytime and nighttime 1-km land surface temperature (LST) and emissivity product using the Temperature Emissivity Separation (TES) algorithm. The MODIS-TES (MOD21_L2) product, will include the LST and emissivity for three MODIS thermal infrared (TIR) bands 29, 31, and 32, and will be generated for data from the NASA-EOS AM and PM platforms. This is version 1.0 of the ATBD and the goal is maintain a 'living' version of this document with changes made when necessary. The current standard baseline MODIS LST products (MOD11*) are derived from the generalized split-window (SW) algorithm (Wan and Dozier 1996), which produces a 1-km LST product and two classification-based emissivities for bands 31 and 32; and a physics-based day/night algorithm (Wan and Li 1997), which produces a 5-km (C4) and 6-km (C5) LST product and emissivity for seven MODIS bands: 20, 22, 23, 29, 31-33.

A Marine Boundary Layer Water Vapor Climatology Derived from Microwave and Near-Infrared Imagery

NASA Astrophysics Data System (ADS)

Millan Valle, L. F.; Lebsock, M. D.; Teixeira, J.

2017-12-01

The synergy of the collocated Advanced Microwave Scanning Radiometer (AMSR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global estimates of partial marine planetary boundary layer water vapor. AMSR microwave radiometry provides the total column water vapor, while MODIS near-infrared imagery provides the water vapor above the cloud layers. The difference between the two gives the vapor between the surface and the cloud top, which may be interpreted as the boundary layer water vapor. Comparisons against radiosondes, and GPS-Radio occultation data demonstrate the robustness of these boundary layer water vapor estimates. We exploit the 14 years of AMSR-MODIS synergy to investigate the spatial, seasonal, and inter-annual variations of the boundary layer water vapor. Last, it is shown that the measured AMSR-MODIS partial boundary layer water vapor can be generally prescribed using sea surface temperature, cloud top pressure and the lifting condensation level. The multi-sensor nature of the analysis demonstrates that there exists more information on boundary layer water vapor structure in the satellite observing system than is commonly assumed when considering the capabilities of single instruments. 2017 California Institute of Technology. U.S. Government sponsorship acknowledged.

The Observed Behavior of the Bias in MODIS-retrieved Cloud Droplet Effective Radius through MISR-MODIS Data Fusion

NASA Astrophysics Data System (ADS)

Fu, D.; Di Girolamo, L.; Liang, L.; Zhao, G.

2017-12-01

Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude (Liang et al., 2015). Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud-top height and the spatial variability of the radiance field, sun-view geometry, and the driving meteorology had from reanalysis data. Our results show interesting relationships in Re bias behavior with these observed properties, revealing that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in MODIS-retrieved Re bias.

A web-based subsetting service for regional scale MODIS land products

DOE Office of Scientific and Technical Information (OSTI.GOV)

SanthanaVannan, Suresh K; Cook, Robert B; Holladay, Susan K

2009-12-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor has provided valuable information on various aspects of the Earth System since March 2000. The spectral, spatial, and temporal characteristics of MODIS products have made them an important data source for analyzing key science questions relating to Earth System processes at regional, continental, and global scales. The size of the MODIS product and native HDF-EOS format are not optimal for use in field investigations at individual sites (100 - 100 km or smaller). In order to make MODIS data readily accessible for field investigations, the NASA-funded Distributed Active Archive Center (DAAC) for Biogeochemicalmore » Dynamics at Oak Ridge National Laboratory (ORNL) has developed an online system that provides MODIS land products in an easy-to-use format and in file sizes more appropriate to field research. This system provides MODIS land products data in a nonproprietary comma delimited ASCII format and in GIS compatible formats (GeoTIFF and ASCII grid). Web-based visualization tools are also available as part of this system and these tools provide a quick snapshot of the data. Quality control tools and a multitude of data delivery options are available to meet the demands of various user communities. This paper describes the important features and design goals for the system, particularly in the context of data archive and distribution for regional scale analysis. The paper also discusses the ways in which data from this system can be used for validation, data intercomparison, and modeling efforts.« less

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2011-01-01

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua 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 MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, 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 MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS 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.

MODIS Atmospheric Data Handler

NASA Technical Reports Server (NTRS)

Anantharaj, Valentine; Fitzpatrick, Patrick

2008-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) 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.

Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?

Treesearch

Yulong Zhang; Conghe Song; Lawrence E. Band; Ge Sun; Junxiang Li

2017-01-01

Accurately monitoring global vegetation dynamics with modern remote sensing is critical for understanding the functions and processes of the biosphere and its interactions with the planetary climate. The MODerate resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) product has been a primary data source for this purpose. To date, theMODIS teamhad released...

Assessment of MODIS NDVI time series data products for detecting forest defoliation by gypsy moth outbreaks

Treesearch

Joseph P. Spruce; Steven Sader; Robert E. Ryan; James Smoot; Philip Kuper; al. et.

2011-01-01

This paper discusses an assessment of Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data products for detecting forest defoliation from European gypsy moth (Lymantria dispar). This paper describes an effort to aid the United States Department of Agriculture (USDA) Forest Service in developing and assessing MODIS-based gypsy moth defoliation...

Cyclone Hudah As Seen By MODIS

NASA Technical Reports Server (NTRS)

2002-01-01

Tropical Cyclone Hudah was one of most powerful storms ever seen in the Indian Ocean. This image from the Moderate-resolution Imaging Spectroradiometer (MODIS) aboard Terra was taken on March 29, 2000. The structure of the eye of the storm is brought out by MODIS' 250-meter resolution. Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison

Near Real-Time Monitoring of Forest Disturbance: A Multi-Sensor Remote Sensing Approach and Assessment Framework

NASA Astrophysics Data System (ADS)

Tang, Xiaojing

Fast and accurate monitoring of tropical forest disturbance is essential for understanding current patterns of deforestation as well as helping eliminate illegal logging. This dissertation explores the use of data from different satellites for near real-time monitoring of forest disturbance in tropical forests, including: development of new monitoring methods; development of new assessment methods; and assessment of the performance and operational readiness of existing methods. Current methods for accuracy assessment of remote sensing products do not address the priority of near real-time monitoring of detecting disturbance events as early as possible. I introduce a new assessment framework for near real-time products that focuses on the timing and the minimum detectable size of disturbance events. The new framework reveals the relationship between change detection accuracy and the time needed to identify events. In regions that are frequently cloudy, near real-time monitoring using data from a single sensor is difficult. This study extends the work by Xin et al. (2013) and develops a new time series method (Fusion2) based on fusion of Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) data. Results of three test sites in the Amazon Basin show that Fusion2 can detect 44.4% of the forest disturbance within 13 clear observations (82 days) after the initial disturbance. The smallest event detected by Fusion2 is 6.5 ha. Also, Fusion2 detects disturbance faster and has less commission error than more conventional methods. In a comparison of coarse resolution sensors, MODIS Terra and Aqua combined provides faster and more accurate detection of disturbance events than VIIRS (Visible Infrared Imaging Radiometer Suite) and MODIS single sensor data. The performance of near real-time monitoring using VIIRS is slightly worse than MODIS Terra but significantly better than MODIS Aqua. New monitoring methods developed in this dissertation provide forest protection organizations the capacity to monitor illegal logging events promptly. In the future, combining two Landsat and two Sentinel-2 satellites will provide global coverage at 30 m resolution every 4 days, and routine monitoring may be possible at high resolution. The methods and assessment framework developed in this dissertation are adaptable to newly available datasets.

Data systems trade studies for a next generation sensor

NASA Astrophysics Data System (ADS)

Masuoka, Edward J.; Fleig, Albert J.

1997-01-01

Processing system designers must make substantial changes to accommodate current and anticipated improvements in remote sensing instruments.Increases in the spectral, radiometric and geometric resolution lead to data rates, processing loads and storage volumes which far exceed the ability of most current computer systems. To accommodate user expectations, the data must be processed and made available quickly in a convenient and easy to use form. This paper describes design trade-offs made in developing the processing system for the moderate resolution imaging spectroradiometer, MODIS, which will fly on the Earth Observing System's, AM-1 spacecraft to be launched in 1998. MODIS will have an average continuous date rate of 6.2 Mbps and require processing at 6.5 GFLOPS to produce 600GB of output products per day. Specific trade-offs occur in the areas of science software portability and usability of science products versus overall system performance and throughput.

An assessment of African test sites in the context of a global network of quality-assured reference standards

USGS Publications Warehouse

Chander, G.; Xiong, X.; Angal, A.; Choi, T.

2009-01-01

The Committee on Earth Observation Satellites (CEOS) Infrared and Visible Optical Sensors (IVOS) subgroup members established a set of CEOS-endorsed globally distributed reference standard test sites for the postlaunch calibration of space-based optical imaging sensors. This paper discusses the top five African pseudo-invariant sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5) that were identified by the IVOS subgroup. This paper focuses on monitoring the long-term radiometric stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using near-simultaneous and cloud-free image pairs acquired from launch to December 2008 over the five African desert sites. Residual errors and coefficients of determination were also generated to support the quality assessment of the calibration differences between the two sensors. An effort was also made to evaluate the relative stability of these sites for long-term monitoring of the optical sensors. ??2009 IEEE.

MODIS technical report series. Volume 3: MODIS airborne simulator level 1B data user's guide

NASA Technical Reports Server (NTRS)

Gumley, Liam E.; Hubanks, Paul A.; Masuoka, Edward J.

1994-01-01

The purpose of this document is to describe the characteristics of moderate resolution imaging spectroradiometer (MODIS) airborne simulator level 1B data, the calibration and geolocation methods used in processing, the structure and format of the level 1B data files, and methods for accessing the data. The MODIS airborne simulator is a scanning spectrometer which flies on a NASA ER-2 and provides spectral information similar to that which will be provided by the MODIS.

Global Performance of a Fast Parameterization Scheme for Estimating Surface Solar Radiation from MODIS data

NASA Astrophysics Data System (ADS)

Tang, W.; Yang, K.; Sun, Z.; Qin, J.; Niu, X.

2016-12-01

A fast parameterization scheme named SUNFLUX is used in this study to estimate instantaneous surface solar radiation (SSR) based on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard both Terra and Aqua platforms. The scheme mainly takes into account the absorption and scattering processes due to clouds, aerosols and gas in the atmosphere. The estimated instantaneous SSR is evaluated against surface observations obtained from seven stations of the Surface Radiation Budget Network (SURFRAD), four stations in the North China Plain (NCP) and 40 stations of the Baseline Surface Radiation Network (BSRN). The statistical results for evaluation against these three datasets show that the relative root-mean-square error (RMSE) values of SUNFLUX are less than 15%, 16% and 17%, respectively. Daily SSR is derived through temporal upscaling from the MODIS-based instantaneous SSR estimates, and is validated against surface observations. The relative RMSE values for daily SSR estimates are about 16% at the seven SURFRAD stations, four NCP stations, 40 BSRN stations and 90 China Meteorological Administration (CMA) radiation stations.

Vegetation canopy structure from NASA EOS multiangle imaging

USDA-ARS?s Scientific Manuscript database

We used red band bidirectional reflectance data from the NASA Multiangle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS) mapped onto a 250 m grid in a multiangle approach to obtain estimates of woody plant fractional cover and crown height through adjus...

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico

PubMed Central

Jarchow, Christopher J.; Didan, Kamel; Barreto-Muñoz, Armando; Glenn, Edward P.

2018-01-01

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area. PMID:29757265

An Overview of SIMBIOS Program Activities and Accomplishments. Chapter 1

NASA Technical Reports Server (NTRS)

Fargion, Giulietta S.; McClain, Charles R.

2003-01-01

The SIMBIOS Program was conceived in 1994 as a result of a NASA management review of the agency's strategy for monitoring the bio-optical properties of the global ocean through space-based ocean color remote sensing. At that time, the NASA ocean color flight manifest included two data buy missions, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Earth Observing System (EOS) Color, and three sensors, two Moderate Resolution Imaging Spectroradiometers (MODIS) and the Multi-angle Imaging Spectro-Radiometer (MISR), scheduled for flight on the EOS-Terra and EOS-Aqua satellites. The review led to a decision that the international assemblage of ocean color satellite systems provided ample redundancy to assure continuous global coverage, with no need for the EOS Color mission. At the same time, it was noted that non-trivial technical difficulties attended the challenge (and opportunity) of combining ocean color data from this array of independent satellite systems to form consistent and accurate global bio-optical time series products. Thus, it was announced at the October 1994 EOS Interdisciplinary Working Group meeting that some of the resources budgeted for EOS Color should be redirected into an intercalibration and validation program (McClain et al., 2002).

Global Ocean Phytoplankton

NASA Technical Reports Server (NTRS)

Franz, B. A.; Behrenfeld, M. J.; Siegel, D. A.; Werdell, P. J.

2014-01-01

Marine phytoplankton are responsible for roughly half the net primary production (NPP) on Earth, fixing atmospheric CO2 into food that fuels global ocean ecosystems and drives the ocean's biogeochemical cycles. Phytoplankton growth is highly sensitive to variations in ocean physical properties, such as upper ocean stratification and light availability within this mixed layer. Satellite ocean color sensors, such as the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; McClain 2009) and Moderate Resolution Imaging Spectroradiometer (MODIS; Esaias 1998), provide observations of sufficient frequency and geographic coverage to globally monitor physically-driven changes in phytoplankton distributions. In practice, ocean color sensors retrieve the spectral distribution of visible solar radiation reflected upward from beneath the ocean surface, which can then be related to changes in the photosynthetic phytoplankton pigment, chlorophyll- a (Chla; measured in mg m-3). Here, global Chla data for 2013 are evaluated within the context of the 16-year continuous record provided through the combined observations of SeaWiFS (1997-2010) and MODIS on Aqua (MODISA; 2002-present). Ocean color measurements from the recently launched Visible and Infrared Imaging Radiometer Suite (VIIRS; 2011-present) are also considered, but results suggest that the temporal calibration of the VIIRS sensor is not yet sufficiently stable for quantitative global change studies. All MODISA (version 2013.1), SeaWiFS (version 2010.0), and VIIRS (version 2013.1) data presented here were produced by NASA using consistent Chla algorithms.

Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo

EPA Science Inventory

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Qual...

Northern Gulf of Mexico estuarine coloured dissolved organic matter derived from MODIS data

EPA Science Inventory

Coloured dissolved organic matter (CDOM) is relevant for water quality management and may become an important measure to complement future water quality assessment programmes. An approach to derive CDOM using the Moderate Resolution Imaging Spectroradiometer (MODIS) was developed...

Monitoring Agricultural Cropping Patterns in the Great Lakes Basin Using MODIS-NDVI Time Series Data

EPA Science Inventory

This research examined changes in agricultural cropping patterns across the Great Lakes Basin (GLB) using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data. Specific research objectives were to characterize the distribut...

Investigating warming trends and spatial patterns of Land Surface Temperatures over the Greater Los Angeles Area using new MODIS and VIIRS LST products

NASA Astrophysics Data System (ADS)

Malakar, N. K.; Hulley, G. C.

2016-12-01

The Los Angeles (LA) metropolitan area is one of the fastest growing urban centers in the United States, and home to roughly 18 million people. Understanding the trends and impacts of warming temperatures in urban environments is an increasingly important issue in our changing climate. We used thermal infrared data from Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors to retrieve Land Surface Temperature using a new Temperature Emissivity Separation algorithm adapted for these sensors. We analyzed day and night LST retrievals to study the warming trends of LST for the greater LA region from 2002-2015. The average warming trend over LA for summer days and nights over this period for MODIS Aqua data was 1.1 °C per decade, while a more rapid warming is observed for the years 2012-2016 for both MODIS and VIIRS observations. We have also found that inland LA regions are warming more rapidly than the other regions. We further investigate the underlying cause of the warming by looking into the physical factors such as changes in net radiation, cloud cover, and evapotranspiration. The results will help to understand how indicators of climate change are evolving in the beginning of the 21st century, and how they compare with global climate model projections. Identification of potential impacts, and underlying causes of warming trends in various LA regions will help decision makers to develop policies to help mitigate the effects of rising temperatures.

Scheduling Observations of Celestial Objects for Earth Observing Sensor Calibration

NASA Technical Reports Server (NTRS)

Wilson, Truman; Xiong, Xiaoxiong

2016-01-01

Radiometric calibration of Earth-observing satellite sensors is critical for tracking on-orbit gain changes through- out the satellite's mission. The Moon, being a stable, well-characterized radiometric target, has been used effectively for tracking the relative gain changes of the reflective solar bands for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board EOS AM-1 (Terra) and PM-1 (Aqua). The Moon is viewed through the MODIS space-view port, and the relative phase of the Moon is restricted to within 0.5 degrees of a chosen target phase to increase the accuracy of the calibration. These geometric restrictions require spacecraft maneuvers in order to bring space-view port into proper alignment with the position of the Moon when the phase requirement is met. In this paper, we describe a versatile tool for scheduling such maneuvers based on the required geometry and lunar phase restrictions for a general spacecraft bound instrument. The results of the scheduling tool have been verified using lunar images from Aqua and Terra MODIS after a scheduled roll maneuver was performed. This tool has also been tested for the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Advanced Technology Microwave Sounder on-board the Suomi-NPP spacecraft. As an extension of this work, we have also developed a tool for scheduling views of bright stars. These stars provide another well-characterized radiometric source that can be used for sensor calibration. This tool has been implemented to determine the times in which a chosen star can be viewed by the high gain stages of the day/night band for the VIIRS instrument.

An Overview of the Earth Observing System MODIS Instrument Performance, Data Systems Performance, and Data Products Status and Availability

NASA Technical Reports Server (NTRS)

Salomonson, Vincent V.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) 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 MODIS data products, several are new and represent powerful and exciting capabilities. The remainder of the MODIS 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 MODIS instrument on the EOS Aqua mission should also be expected to be in orbit and functioning in the Spring of 2002.

Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

NASA Astrophysics Data System (ADS)

Patadia, Falguni; Levy, Robert C.; Mattoo, Shana

2018-06-01

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in window regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are similar, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

Evaluation of the MODIS Albedo Product over a Heterogeneous Agricultural Area

NASA Technical Reports Server (NTRS)

Sobrino, Jose Antonio; Franch, B.; Oltra-Carrio, R.; Vermote, E. F.; Fedele, E.

2013-01-01

In this article, the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF)/Albedo product (MCD43) is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction (EODIX) project campaign, which was developed in Barrax (Spain) in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal (RTLSR) (which corresponds to the MODIS BRDF algorithm) and the RossThick-Maignan-LiSparse-Reciprocal (RTLSR-HS), were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor. During the campaign, airborne images were retrieved with different view zenith angles along the principal and orthogonal planes. Comparing the results of applying the models to the airborne data with ground measurements, we obtained a root mean square error (RMSE) of 0.018 with both RTLSR and RTLSR-HS models. The evaluation of the MODIS BRDF/Albedo product (MCD43) was performed by comparing satellite images with AHS estimations. The results reported an RMSE of 0.04 with both models. Additionally, taking advantage of a homogeneous barley pixel, we compared in situ albedo data to satellite albedo data. In this case, the MODIS albedo estimation was (0.210 +/- 0.003), while the in situ measurement was (0.204 +/- 0.003). This result shows good agreement in regard to a homogeneous pixel.

First Complete Day from MODIS

NASA Technical Reports Server (NTRS)

2002-01-01

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 (MODIS) aboard NASA's Terra spacecraft. MODIS 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, MODIS 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, MODIS Atmosphere Team, NASA GSFC

Sea Ice Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.

2003-01-01

Global sea ice products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) on board both the Terra and Aqua 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 MODIS 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 MODIS 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 MODIS in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and the MODIS on the Aqua satellite, it may be possible to develop a relationship between MODIS-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 MODIS IST measurements.

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring.

PubMed

Skakun, Sergii; Justice, Christopher O; Vermote, Eric; Roger, Jean-Claude

2018-01-01

The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration's (NASA) Terra and Aqua remote sensing satellites. The VIIRS will eventually replace MODIS for both land science and applications and add to the coarse-resolution, long term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provide critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties related the transitioning from using MODIS to VIIRS-based NDVI's. In particular, we compare NDVI's derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily Climate Modelling Grid (CMG) images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red - NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, NDVI uncertainties were 0.014, 0.029 and 0.056 respectively for the 500 m product and 0.013, 0.016 and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for applications with an uncertainty of less than 0.02 to 0.05, depending on the scale of spatial aggregation, which is typically the uncertainty of the individual dataset.

A Review of Selected MODIS Algorithms, Data Products, and Applications

EPA Science Inventory

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments designed as part of NASA’s Earth Observing System (EOS) to provide long-term global observation of the Earth’s land, ocean, and atmospheric properties (Asrar and Dokken, 1993). The developmen...

Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data

NASA Astrophysics Data System (ADS)

Bibi, Humera; Alam, Khan; Chishtie, Farrukh; Bibi, Samina; Shahid, Imran; Blaschke, Thomas

2015-06-01

This study provides an intercomparison of aerosol optical depth (AOD) retrievals from satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), Ozone Monitoring Instrument (OMI), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) instrumentation over Karachi, Lahore, Jaipur, and Kanpur between 2007 and 2013, with validation against AOD observations from the ground-based Aerosol Robotic Network (AERONET). Both MODIS Deep Blue (MODISDB) and MODIS Standard (MODISSTD) products were compared with the AERONET products. The MODISSTD-AERONET comparisons revealed a high degree of correlation for the four investigated sites at Karachi, Lahore, Jaipur, and Kanpur, the MODISDB-AERONET comparisons revealed even better correlations, and the MISR-AERONET comparisons also indicated strong correlations, as did the OMI-AERONET comparisons, while the CALIPSO-AERONET comparisons revealed only poor correlations due to the limited number of data points available. We also computed figures for root mean square error (RMSE), mean absolute error (MAE) and root mean bias (RMB). Using AERONET data to validate MODISSTD, MODISDB, MISR, OMI, and CALIPSO data revealed that MODISSTD data was more accurate over vegetated locations than over un-vegetated locations, while MISR data was more accurate over areas close to the ocean than over other areas. The MISR instrument performed better than the other instruments over Karachi and Kanpur, while the MODISSTD AOD retrievals were better than those from the other instruments over Lahore and Jaipur. We also computed the expected error bounds (EEBs) for both MODIS retrievals and found that MODISSTD consistently outperformed MODISDB in all of the investigated areas. High AOD values were observed by the MODISSTD, MODISDB, MISR, and OMI instruments during the summer months (April-August); these ranged from 0.32 to 0.78, possibly due to human activity and biomass burning. In contrast, high AOD values were observed by the CALIPSO instrument between September and December, due to high concentrations of smoke and soot aerosols. The variable monthly AOD figures obtained with different sensors indicate overestimation by MODISSTD, MODISDB, OMI, and CALIPSO instruments over Karachi, Lahore, Jaipur and Kanpur, relative to the AERONET data, but underestimation by the MISR instrument.

EOS Terra Validation Program

NASA Technical Reports Server (NTRS)

Starr, David

2000-01-01

The EOS Terra mission will be launched in July 1999. This mission has great relevance to the atmospheric radiation community and global change issues. Terra instruments include Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Clouds and Earth's Radiant Energy System (CERES), Multi-Angle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Measurements of Pollution in the Troposphere (MOPITT). In addition to the fundamental radiance data sets, numerous global science data products will be generated, including various Earth radiation budget, cloud and aerosol parameters, as well as land surface, terrestrial ecology, ocean color, and atmospheric chemistry parameters. Significant investments have been made in on-board calibration to ensure the quality of the radiance observations. A key component of the Terra mission is the validation of the science data products. This is essential for a mission focused on global change issues and the underlying processes. The Terra algorithms have been subject to extensive pre-launch testing with field data whenever possible. Intensive efforts will be made to validate the Terra data products after launch. These include validation of instrument calibration (vicarious calibration) experiments, instrument and cross-platform comparisons, routine collection of high quality correlative data from ground-based networks, such as AERONET, and intensive sites, such as the SGP ARM site, as well as a variety field experiments, cruises, etc. Airborne simulator instruments have been developed for the field experiment and underflight activities including the MODIS Airborne Simulator (MAS) AirMISR, MASTER (MODIS-ASTER), and MOPITT-A. All are integrated on the NASA ER-2 though low altitude platforms are more typically used for MASTER. MATR is an additional sensor used for MOPITT algorithm development and validation. The intensive validation activities planned for the first year of the Terra mission will be described with emphasis on derived geophysical parameters of most relevance to the atmospheric radiation community.

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

MODIS Views North Pole

NASA Technical Reports Server (NTRS)

2002-01-01

This true-color image over the North Pole was acquired by the MODerate-resolution Imaging Spectroradiometer (MODIS), flying aboard the Terra spacecraft, on May 5, 2000. The scene was received and processed by Norway's MODIS Direct Broadcast data receiving station, located in Svalbard, within seconds of photons hitting the sensor's detectors. (Click for more details about MODIS Direct Broadcast data.) In this image, the sea ice appears white and areas of open water, or recently refrozen sea surface, appear black. The irregular whitish shapes toward the bottom of the image are clouds, which are often difficult to distinguish from the white Arctic surface. Notice the considerable number of cracks, or 'leads,' in the ice that appear as dark networks of lines. Throughout the region within the Arctic Circle leads are continually opening and closing due to the direction and intensity of shifting wind and ocean currents. Leads are particularly common during the summer, when temperatures are higher and the ice is thinner. In this image, each pixel is one square kilometer. Such true-color views of the North Pole are quite rare, as most of the time much of the region within the Arctic Circle is cloaked in clouds. Image by Allen Lunsford, NASA GSFC Direct Readout Laboratory; Data courtesy Tromso receiving station, Svalbard, Norway

Towards identification of relevant variables in the observed aerosol optical depth bias between MODIS and AERONET observations

NASA Astrophysics Data System (ADS)

Malakar, N. K.; Lary, D. J.; Gencaga, D.; Albayrak, A.; Wei, J.

2013-08-01

Measurements made by satellite remote sensing, Moderate Resolution Imaging Spectroradiometer (MODIS), 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 reflectivity at the various measured wavelengths, etc. Specifically, we performed analysis for remote sensing Aqua-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.

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 both Terra and Aqua. In certain situations, this combined analysis of Terra- and Aqua-MODIS data offers an insight into the diurnal cycle of aerosol loading.

Cloud vortices

NASA Image and Video Library

2015-11-02

Cloud vortices off Heard Island, south Indian Ocean. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image of sea ice off Heard Island on Nov 2, 2015 at 5:02 AM EST (09:20 UTC). Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team

MODIS. Volume 1: MODIS level 1A software baseline requirements

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Fleig, Albert; Ardanuy, Philip; Goff, Thomas; Carpenter, Lloyd; Solomon, Carl; Storey, James

1994-01-01

This document describes the level 1A software requirements for the moderate resolution imaging spectroradiometer (MODIS) 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; MODIS log; and product generation system (PGS). Implementation constraints and requirements for adapting the software to the physical environment are also included.

Comparative Analysis of Daytime Fire Detection Algorithms, Using AVHRR Data for the 1995 Fire Season in Canda: Perspective for MODIS

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Y. J.; Fraser, R. H.; Jin, J.-Z.; Park, W. M.; Lau, William K. M. (Technical Monitor)

2001-01-01

Two fixed-threshold Canada Centre for Remote Sensing and European Space Agency (CCRS and ESA) and three contextual GIGLIO, International Geosphere and Biosphere Project, and Moderate Resolution Imaging Spectroradiometer (GIGLIO, IGBP, and MODIS) algorithms were used for fire detection with Advanced Very High Resolution Radiometer (AVHRR) data acquired over Canada during the 1995 fire season. The CCRS algorithm was developed for the boreal ecosystem, while the other four are for global application. The MODIS algorithm, although developed specifically for use with the MODIS sensor data, was applied to AVHRR in this study for comparative purposes. Fire detection accuracy assessment for the algorithms was based on comparisons with available 1995 burned area ground survey maps covering five Canadian provinces. Overall accuracy estimations in terms of omission (CCRS=46%, ESA=81%, GIGLIO=75%, IGBP=51%, MODIS=81%) and commission (CCRS=0.35%, ESA=0.08%, GIGLIO=0.56%, IGBP=0.75%, MODIS=0.08%) errors over forested areas revealed large differences in performance between the algorithms, with no relevance to type (fixed-threshold or contextual). CCRS performed best in detecting real forest fires, with the least omission error, while ESA and MODIS produced the highest omission error, probably because of their relatively high threshold values designed for global application. The commission error values appear small because the area of pixels falsely identified by each algorithm was expressed as a ratio of the vast unburned forest area. More detailed study shows that most commission errors in all the algorithms were incurred in nonforest agricultural areas, especially on days with very high surface temperatures. The advantage of the high thresholds in ESA and MODIS was that they incurred the least commission errors.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia.

PubMed

Dorji, Passang; Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit.

Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from MODIS Satellite Data and Ecosystem Modeling

EPA Science Inventory

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Pr...

Sub-Pixel Mapping of Tree Canopy, Impervious Surfaces, and Cropland in the Laurentian Great Lakes Basin Using MODIS Time-Series Data

EPA Science Inventory

This research examined sub-pixel land-cover classification performance for tree canopy, impervious surface, and cropland in the Laurentian Great Lakes Basin (GLB) using both timeseries MODIS (MOderate Resolution Imaging Spectroradiometer) NDVI (Normalized Difference Vegetation In...

Monitoring NEON terrestrial sites phenology with daily MODIS BRDF/albedo product and landsat data

USDA-ARS?s Scientific Manuscript database

The MODerate resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance 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...

LINKING IN SITU TIME SERIES FOREST CANOPY LAI AND PHENOLOGY METRICS WITH MODIS AND LANDSAT NDVI AND LAI PRODUCTS

EPA Science Inventory

The subject of this presentation is forest vegetation dynamics as observed by the TERRA spacecraft's Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper, and complimentary in situ time series measurements of forest canopy metrics related to Leaf Area...

MODIS Snow and Ice Production

NASA Technical Reports Server (NTRS)

Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)

2002-01-01

Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.

2010-01-01

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Suomi NPP VIIRS active fire product status

NASA Astrophysics Data System (ADS)

Ellicott, E. A.; Csiszar, I. A.; Schroeder, W.; Giglio, L.; Wind, B.; Justice, C. O.

2012-12-01

We provide an overview of the evaluation and development of the Active Fires product derived from the Visible Infrared Imager Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite during the first year of on-orbit data. Results from the initial evaluation of the standard SNPP Active Fires product, generated by the SNPP Interface Data Processing System (IDPS), supported the stabilization of the VIIRS Sensor Data Record (SDR) product. This activity focused in particular on the processing of the dual-gain 4 micron VIIRS M13 radiometric measurements into 750m aggregated data, which are fundamental for active fire detection. Following the VIIRS SDR product's Beta maturity status in April 2012, correlative analysis between VIIRS and near-simultaneous fire detections from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Aqua satellite confirmed the expected relative detection rates driven primarily by sensor differences. The VIIRS Active Fires Product Development and Validation Team also developed a science code that is based on the latest MODIS Collection 6 algorithm and provides a full spatially explicit fire mask to replace the sparse array output of fire locations from a MODIS Collection 4 equivalent algorithm in the current IDPS product. The Algorithm Development Library (ADL) was used to support the planning for the transition of the science code into IDPS operations in the future. Product evaluation and user outreach was facilitated by a product website that provided end user access to fire data in user-friendly format over North America as well as examples of VIIRS-MODIS comparisons. The VIIRS fire team also developed an experimental product based on 375m VIIRS Imagery band measurements and provided high quality imagery of major fire events in US. By August 2012 the IDPS product achieved Beta maturity, with some known and documented shortfalls related to the processing of incorrect SDR input data and to apparent algorithm deficiencies in select observing and environmental conditions.

Radioactive Quality Evaluation and Cross Validation of Data from the HJ-1A/B Satellites' CCD Sensors

PubMed Central

Zhang, Xin; Zhao, Xiang; Liu, Guodong; Kang, Qian; Wu, Donghai

2013-01-01

Data from multiple sensors are frequently used in Earth science to gain a more complete understanding of spatial information changes. Higher quality and mutual consistency are prerequisites when multiple sensors are jointly used. The HJ-1A/B satellites successfully launched on 6 September 2008. There are four charge-coupled device (CCD) sensors with uniform spatial resolutions and spectral range onboard the HJ-A/B satellites. Whether these data are keeping consistency is a major issue before they are used. This research aims to evaluate the data consistency and radioactive quality from the four CCDs. First, images of urban, desert, lake and ocean are chosen as the objects of evaluation. Second, objective evaluation variables, such as mean, variance and angular second moment, are used to identify image performance. Finally, a cross validation method are used to ensure the correlation of the data from the four HJ-1A/B CCDs and that which is gathered from the moderate resolution imaging spectro-radiometer (MODIS). The results show that the image quality of HJ-1A/B CCDs is stable, and the digital number distribution of CCD data is relatively low. In cross validation with MODIS, the root mean square errors of bands 1, 2 and 3 range from 0.055 to 0.065, and for band 4 it is 0.101. The data from HJ-1A/B CCD have better consistency. PMID:23881127

Radioactive quality evaluation and cross validation of data from the HJ-1A/B satellites' CCD sensors.

PubMed

Zhang, Xin; Zhao, Xiang; Liu, Guodong; Kang, Qian; Wu, Donghai

2013-07-05

Data from multiple sensors are frequently used in Earth science to gain a more complete understanding of spatial information changes. Higher quality and mutual consistency are prerequisites when multiple sensors are jointly used. The HJ-1A/B satellites successfully launched on 6 September 2008. There are four charge-coupled device (CCD) sensors with uniform spatial resolutions and spectral range onboard the HJ-A/B satellites. Whether these data are keeping consistency is a major issue before they are used. This research aims to evaluate the data consistency and radioactive quality from the four CCDs. First, images of urban, desert, lake and ocean are chosen as the objects of evaluation. Second, objective evaluation variables, such as mean, variance and angular second moment, are used to identify image performance. Finally, a cross validation method are used to ensure the correlation of the data from the four HJ-1A/B CCDs and that which is gathered from the moderate resolution imaging spectro-radiometer (MODIS). The results show that the image quality of HJ-1A/B CCDs is stable, and the digital number distribution of CCD data is relatively low. In cross validation with MODIS, the root mean square errors of bands 1, 2 and 3 range from 0.055 to 0.065, and for band 4 it is 0.101. The data from HJ-1A/B CCD have better consistency.

Analysis of the Electronic Crosstalk Effect in Terra MODIS Long-Wave Infrared Photovoltaic Bands Using Lunar Images

NASA Technical Reports Server (NTRS)

Wilson, Truman; Wu, Aisheng; Wang, Zhipeng; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key sensors among the suite of remote sensing instruments on board the Earth Observing System Terra and Aqua spacecrafts. For each MODIS spectral band, the sensor degradation has been measured using a set of on-board calibrators. MODIS also uses lunar observations from nearly monthly spacecraft maneuvers, which bring the Moon into view through the space-view port, helping to characterize the scan mirror degradation at a different angles of incidence. Throughout the Terra mission, contamination of the long-wave infrared photovoltaic band (LWIR PV, bands 27-30) signals has been observed in the form of electronic crosstalk, where signal from each of the detectors among the LWIR PV bands can leak to the other detectors, producing a false signal contribution. This contamination has had a noticeable effect on the MODIS science products since 2010 for band 27, and since 2012 for bands 28 and 29. Images of the Moon have been used effectively for determining the contaminating bands, and have also been used to derive correction coefficients for the crosstalk contamination. In this paper, we introduce an updated technique for characterizing the crosstalk contamination among the LWIR PV bands using data from lunar calibration events. This approach takes into account both the in-band and out-of-band contribution to the signal contamination for each detector in bands 27-30, which is not considered in previous works. The crosstalk coefficients can be derived for each lunar calibration event, providing the time dependence of the crosstalk contamination. Application of these coefficients to Earth-view image data results in a significant reduction in image contamination and a correction of the scene radiance for bands 27- 30. Also, this correction shows a significant improvement to certain threshold tests in the MODIS Level-2 Cloud Mask. In this paper, we will detail the methodology used to identify and correct the crosstalk contamination for the LWIR PV bands in Terra MODIS. The derived time-dependent crosstalk coefficients will also be discussed. Finally, the impact of the correction on the downstream data products will be analyzed.

How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yongxiang

2014-01-01

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

Modis Collection 6 Shortwave-Derived Cloud Phase Classification Algorithm and Comparisons with CALIOP

NASA Technical Reports Server (NTRS)

Marchant, Benjamin; Platnick, Steven; Meyer, Kerry; Arnold, George Thomas; Riedi, Jerome

2016-01-01

Cloud thermodynamic phase (e.g., ice, liquid) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

Assessment of NPP VIIRS Albedo Over Heterogeneous Crop Land in Northern China

NASA Astrophysics Data System (ADS)

Wu, Xiaodan; Wen, Jianguang; Xiao, Qing; Yu, Yunyue; You, Dongqin; Hueni, Andreas

2017-12-01

In this paper, the accuracy of Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) land surface albedo, which is derived from the direct estimation algorithm, was assessed using ground-based albedo observations from a wireless sensor network over a heterogeneous cropland in the Huailai station, northern China. Data from six nodes spanning 2013-2014 over vegetation, bare soil, and mixed terrain surfaces were utilized to provide ground reference at VIIRS pixel scale. The performance of VIIRS albedo was also compared with Global LAnd Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) albedos (Collection 5 and 6). The results indicate that the current granular VIIRS albedo has a high accuracy with a root-mean-square error of 0.02 for typical land covers. They are significantly correlated with ground references indicated by a correlation coefficient (R) of 0.73. The VIIRS albedo shows distinct advantages to GLASS and MODIS albedos over bare soil and mixed-cover surfaces, while it is inferior to the other two products over vegetated surfaces. Furthermore, its time continuity and the ability to capture the abrupt change of surface albedo are better than that of GLASS and MODIS albedo.

Downscaling of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.

2010-12-01

High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image downscaling has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform downscaling of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for downscaling problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the downscaled 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.

Estimation of fire emissions from satellite-based measurements

NASA Astrophysics Data System (ADS)

Ichoku, C. M.; Kaufman, Y. J.

2004-12-01

Biomass burning is a worldwide phenomenon affecting many vegetated parts of the globe regularly. Fires emit large quantities of aerosol and trace gases into the atmosphere, thus influencing the atmospheric chemistry and climate. Traditional methods of fire emissions estimation achieved only limited success, because they were based on peripheral information such as rainfall patterns, vegetation types and changes, agricultural practices, and surface ozone concentrations. During the last several years, rapid developments in satellite remote sensing has allowed more direct estimation of smoke emissions using remotely-sensed fire data. However, current methods use fire pixel counts or burned areas, thereby depending on the accuracy of independent estimations of the biomass fuel loadings, combustion efficiency, and emission factors. With the enhanced radiometric range of its 4-micron fire channel, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, which flies aboard both of the Earth Observing System (EOS) Terra and Aqua Satellites, is able to measure the rate of release of fire radiative energy (FRE) in MJ/s (something that older sensors could not do). MODIS also measures aerosol distribution. Taking advantage of these new resources, we have developed a procedure combining MODIS fire and aerosol products to derive FRE-based smoke emission coefficients (Ce in kg/MJ) for different regions of the globe. These coefficients are simply used to multiply FRE from MODIS to derive the emitted smoke aerosol mass. Results from this novel methodology are very encouraging. For instance, it was found that the smoke total particulate mass emission coefficient for the Brazilian Cerrado ecosystem (approximately 0.022 kg/MJ) is about twice the value for North America or Australia, but about 50 percent lower than the value for Zambia in southern Africa.

Estimation of Fire Emissions from Satellite-Based Measurements

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram J.

2004-01-01

Biomass burning is a worldwide phenomenon affecting many vegetated parts of the globe regularly. Fires emit large quantities of aerosol and trace gases into the atmosphere, thus influencing the atmospheric chemistry and climate. Traditional methods of fire emissions estimation achieved only limited success, because they were based on peripheral information such as rainfall patterns, vegetation types and changes, agricultural practices, and surface ozone concentrations. During the last several years, rapid developments in satellite remote sensing has allowed more direct estimation of smoke emissions using remotely-sensed fire data. However, current methods use fire pixel counts or burned areas, thereby depending on the accuracy of independent estimations of the biomass fuel loadings, combustion efficiency, and emission factors. With the enhanced radiometric range of its 4-micron fire channel, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, which flies aboard both of the Earth Observing System EOS) Terra and Aqua Satellites, is able to measure the rate of release of fire radiative energy (FRE) in MJ/s (something that older sensors could not do). MODIS also measures aerosol distribution. Taking advantage of these new resources, we have developed a procedure combining MODIS fire and aerosol products to derive FRE-based smoke emission coefficients (C(e), in kg/MJ) for different regions of the globe. These coefficients are simply used to multiply FRE from MODIS to derive the emitted smoke aerosol mass. Results from this novel methodology are very encouraging. For instance, it was found that the smoke total particulate mass emission coefficient for the Brazilian Cerrado ecosystem (approximately 0.022 kg/MJ) is about twice the value for North America, Western Europe, or Australia, but about 50% lower than the value for southern Africa.

Characterization of the Sonoran desert as a radiometric calibration target for Earth observing sensors

USGS Publications Warehouse

Angal, Amit; Chander, Gyanesh; Xiong, Xiaoxiong; Choi, Tae-young; Wu, Aisheng

2011-01-01

To provide highly accurate quantitative measurements of the Earth's surface, a comprehensive calibration and validation of the satellite sensors is required. The NASA Moderate Resolution Imaging Spectroradiometer (MODIS) Characterization Support Team, in collaboration with United States Geological Survey, Earth Resources Observation and Science Center, has previously demonstrated the use of African desert sites to monitor the long-term calibration stability of Terra MODIS and Landsat 7 (L7) Enhanced Thematic Mapper plus (ETM+). The current study focuses on evaluating the suitability of the Sonoran Desert test site for post-launch long-term radiometric calibration as well as cross-calibration purposes. Due to the lack of historical and on-going in situ ground measurements, the Sonoran Desert is not usually used for absolute calibration. An in-depth evaluation (spatial, temporal, and spectral stability) of this site using well calibrated L7 ETM+ measurements and local climatology data has been performed. The Sonoran Desert site produced spatial variability of about 3 to 5% in the reflective solar regions, and the temporal variations of the site after correction for view-geometry impacts were generally around 3%. The results demonstrate that, barring the impacts due to occasional precipitation, the Sonoran Desert site can be effectively used for cross-calibration and long-term stability monitoring of satellite sensors, thus, providing a good test site in the western hemisphere.

Operationalizing a Research Sensor: MODIS to VIIRS

NASA Astrophysics Data System (ADS)

Grant, K. D.; Miller, S. W.; Puschell, J.

2012-12-01

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 (MODIS) 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). MODIS 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. MODIS has flown on the EOS Terra satellite since 1999 and on the EOS Aqua satellite since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of MODIS-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to MODIS for the next-generation polar-orbiting environmental satellites, the Visible/Infrared Imager Radiometer Suite (VIIRS). VIIRS combines the demonstrated high value spectral coverage and radiometric accuracy of MODIS with the legacy spectral bands and radiometric accuracy of the Advanced Very High Resolution Radiometer (AVHRR) and the high spatial resolution (0.75 km) of the Operational Linescan System (OLS). Except for MODIS bands designed for deriving vertical temperature and humidity structure in the atmosphere, VIIRS uses identical or very similar bands from MODIS that have the most interest and usefulness to operational customers in NOAA, the USAF and the USN. The development of VIIRS and JPSS reaps the benefit of investments in MODIS and the NASA EOS and the early development of operational algorithms by NOAA and DoD using MODIS data. This presentation will cover the different aspects of transitioning a research system into an operational system. These aspects include: (1) sensor (hardware & software) operationalization, (2) system performance operational factors, (3) science changes to algorithms reflecting the operational performance factors, and (4) the operationalization and incorporation of the science into a fully 24 x 7 production system, tasked with meeting stringent operational needs. Benefits of early operationalization are discussed along with suggested areas for improvement in this process that could benefit future work such as operationalizing Earth Science Decadal Survey missions.

Application of NASA Giovanni to Coastal Zone Remote Sensing Research

NASA Technical Reports Server (NTRS)

Acker, James; Leptoukh, Gregory; Kempler, Steven; Berrick, Stephen; Rui, Hualan; Shen, Suhung

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) provides rapid access to, and enables effective utilization of, remotely-sensed data that are applicable to investigations of coastal environmental processes. Data sets in Giovanni include precipitation data from the Tropical Rainfall Measuring Mission (TRMM), particularly useful for coastal storm investigations; ocean color radiometry data from the Sea-viewing Wide Field-of-view Sensor (SeaWIFS) and Moderate Resolution Imaging Spectroradiometer (MODIS), useful for water quality evaluation, phytoplankton blooms, and terrestrial-marine interactions; and atmospheric data from MODIS and the Advanced Infrared Sounder (AIRS), providing the capability to characterize atmospheric variables. Giovanni provides a simple interface allowing discovery and analysis of environmental data sets with accompanying graphic visualizations. Examples of Giovanni investigations of the coastal zone include hurricane and storm impacts, hydrologically-induced phytoplankton blooms, chlorophyll trend analysis, and dust storm characterization. New and near-future capabilities of Giovanni will be described.

Application of NASA Giovanni to Coastal Zone Remote Sensing Search

NASA Technical Reports Server (NTRS)

Acker, James; Leptoukh, Gregory; Kempler, Steven; Berrick, Stephen; Rui, Hualan; Shen, Suhung

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) provides rapid access to, and enables effective utilization of, remotely-sensed data that are applicable to investigations of coastal environmental processes. Data sets in Giovanni include precipitation data from the Tropical Rainfall Measuring Mission (TRMM), particularly useful for coastal storm investigations; ocean color radiometry data from the Sea-viewing Wide Field-of-view Sensor (SeaWIFS) and Moderate Resolution Imaging Spectroradiometer (MODIS), useful for water quality evaluation, phytoplankton blooms, and terrestrial-marine interactions; and atmospheric data from MODIS and the Advanced Infrared Sounder (AIRS), providing the capability to characterize atmospheric variables. Giovanni provides a simple interface allowing discovery and analysis of environmental data sets with accompanying graphic visualizations. Examples of Giovanni investigations of the coastal zone include hurricane and storm impacts, hydrologically-induced phytoplankton blooms, chlorophyll trend analysis, and dust storm characterization. New and near-future capabilities of Giovanni will be described.

Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data

Treesearch

Jessica Robin; Ralph Dubayah; Elena Sparrow; Elissa Levine

2008-01-01

This work evaluates whether continuity between Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) is achievable for monitoring phenological changes in Alaska. This work also evaluates whether NDVI can detect changes in start of the growing season (SOS) in this region....

The Blue Marble

NASA Technical Reports Server (NTRS)

2002-01-01

This spectacular Moderate Resolution Imaging Spectroradiometer (MODIS) 'blue marble' image is based on the most detailed collection of true-color imagery of the entire Earth to date. Using a collection of satellite-based observations, scientists and visualizers stitched together months of observations of the land surface, oceans, sea ice, and clouds into a seamless, true-color mosaic of every square kilometer (.386 square mile) of our planet. Most of the information contained in this image came from MODIS, illustrating MODIS' outstanding capacity to act as an integrated tool for observing a variety of terrestrial, oceanic, and atmospheric features of the Earth. The land and coastal ocean portions of this image is based on surface observations collected from June through September 2001 and combined, or composited, every eight days to compensate for clouds that might block the satellite's view on any single day. Global ocean color (or chlorophyll) data was used to simulate the ocean surface. MODIS doesn't measure 3-D features of the Earth, so the surface observations were draped over topographic data provided by the U.S. Geological Survey EROS Data Center. MODIS observations of polar sea ice were combined with observations of Antarctica made by the National Oceanic and Atmospheric Administration's AVHRR sensor-the Advanced Very High Resolution Radiometer. The cloud image is a composite of two days of MODIS imagery collected in visible light wavelengths and a third day of thermal infra-red imagery over the poles. A large collection of imagery based on the blue marble in a variety of sizes and formats, including animations and the full (1 km) resolution imagery, is available at the Blue Marble page. Image by Reto Stockli, Render by Robert Simmon. Based on data from the MODIS Science Team

Unmanned aerial system nadir reflectance and MODIS nadir BRDF-adjusted surface reflectances intercompared over Greenland

NASA Astrophysics Data System (ADS)

Faulkner Burkhart, John; Kylling, Arve; Schaaf, Crystal B.; Wang, Zhuosen; Bogren, Wiley; Storvold, Rune; Solbø, Stian; Pedersen, Christina A.; Gerland, Sebastian

2017-07-01

Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo (MCD43) algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS). The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300-920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR) products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms.

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Foster, James L.

2009-01-01

Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

Multi-sensor data processing method for improved satellite retrievals

NASA Astrophysics Data System (ADS)

Fan, Xingwang

2017-04-01

Satellite remote sensing has provided massive data that improve the overall accuracy and extend the time series of environmental studies. In reflective solar bands, satellite data are related to land surface properties via radiative transfer (RT) equations. These equations generally include sensor-related (calibration coefficients), atmosphere-related (aerosol optical thickness) and surface-related (surface reflectance) parameters. It is an ill-posed problem to solve three parameters with only one RT equation. Even if there are two RT equations (dual-sensor data), the problem is still unsolvable. However, a robust solution can be obtained when any two parameters are known. If surface and atmosphere are known, sensor intercalibration can be performed. For example, the Advanced Very High Resolution Radiometer (AVHRR) was calibrated to the MODerate-resolution Imaging Spectroradiometer (MODIS) in Fan and Liu (2014) [Fan, X., and Liu, Y. (2014). Quantifying the relationship between intersensor images in solar reflective bands: Implications for intercalibration. IEEE Transactions on Geoscience and Remote Sensing, 52(12), 7727-7737.]. If sensor and surface are known, atmospheric data can be retrieved. For example, aerosol data were retrieved using tandem TERRA and AQUA MODIS images in Fan and Liu (2016a) [Fan, X., and Liu, Y. (2016a). Exploiting TERRA-AQUA MODIS relationship in the reflective solar bands for aerosol retrieval. Remote Sensing, 8(12), 996.]. If sensor and atmosphere are known, data consistency can be obtained. For example, Normalized Difference Vegetation Index (NDVI) data were intercalibrated among coarse-resolution sensors in Fan and Liu (2016b) [Fan, X., and Liu, Y. (2016b). A global study of NDVI difference among moderate-resolution satellite sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 121, 177-191.], and among fine-resolution sensors in Fan and Liu (2017) [Fan, X., and Liu, Y. (2017). A generalized model for intersensor NDVI calibration and its comparison with regression approaches. IEEE Transactions on Geoscience and Remote Sensing, 55(3), doi: 10.1109/TGRS.2016.2635802.]. These studies demonstrate the success of multi-sensor data and novel methods in the research domain of geoscience. These data will benefit remote sensing of terrestrial parameters in decadal timescales, such as soil salinity content in Fan et al. (2016) [Fan, X., Weng, Y., and Tao, J. (2016). Towards decadal soil salinity mapping using Landsat time series data. International Journal of Applied Earth Observation and Geoinformation, 52, 32-41.].

Estimating optically-thin cirrus cloud induced cold bias on infrared radiometric satellite sea surface temperature retrieval in the tropics

NASA Astrophysics Data System (ADS)

Marquis, Jared Wayne

Passive longwave infrared radiometric satellite-based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically-thin cirrus (OTC) clouds (cloud optical depth ≤ 0.3; COD). Level 2 split-window SST retrievals over tropical oceans (30° S - 30° N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, mounted on the independent NASA CALIPSO satellite. OTC are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level-2 data, representing over 99% of all contaminating cirrus found. This results in cold-biased SST retrievals using either split- (MODIS, AVHRR and VIIRS) or triple-window (AVHRR and VIIRS only) retrieval methods. SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5 km thick OTC cloud placed incrementally from 10.0 - 18.0 km above mean sea level for cloud optical depths (COD) between 0.0 - 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud top height and COD (assuming them consistent across each platform) integrated within each corresponding modeled cold bias matrix. Split-window relative OTC cold biases, for any single observation, range from 0.40° - 0.49° C for the three sensors, with an absolute (bulk mean) bias between 0.10° - 0.13° C. Triple-window retrievals are more resilient, ranging from 0.03° - 0.04° C relative and 0.11° - 0.16° C absolute. Cold biases are constant across the Pacific and Indian Ocean domains. Absolute bias is smaller over the Atlantic, but relative bias is larger due to different cloud properties indicating that this issue persists globally.

Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.

USGS Publications Warehouse

Brown, Jesslyn F.; Miura, T.; Wardlow, B.; Gu, Yingxin

2011-01-01

Droughts occur repeatedly in the United States resulting in billions of dollars of damage. Monitoring and reporting on drought conditions is a necessary function of government agencies at multiple levels. A team of Federal and university partners developed a drought decision- support tool with higher spatial resolution relative to traditional climate-based drought maps. The Vegetation Drought Response Index (VegDRI) indicates general canopy vegetation condition assimilation of climate, satellite, and biophysical data via geospatial modeling. In VegDRI, complementary drought-related data are merged to provide a comprehensive, detailed representation of drought stress on vegetation. Time-series data from daily polar-orbiting earth observing systems [Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS)] providing global measurements of land surface conditions are ingested into VegDRI. Inter-sensor compatibility is required to extend multi-sensor data records; thus, translations were developed using overlapping observations to create consistent, long-term data time series. 

Characterizing error distributions for MISR and MODIS optical depth data

NASA Astrophysics Data System (ADS)

Paradise, S.; Braverman, A.; Kahn, R.; Wilson, B.

2008-12-01

The Multi-angle Imaging SpectroRadiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's EOS satellites collect massive, long term data records on aerosol amounts and particle properties. MISR and MODIS have different but complementary sampling characteristics. In order to realize maximum scientific benefit from these data, the nature of their error distributions must be quantified and understood so that discrepancies between them can be rectified and their information combined in the most beneficial way. By 'error' we mean all sources of discrepancies between the true value of the quantity of interest and the measured value, including instrument measurement errors, artifacts of retrieval algorithms, and differential spatial and temporal sampling characteristics. Previously in [Paradise et al., Fall AGU 2007: A12A-05] we presented a unified, global analysis and comparison of MISR and MODIS measurement biases and variances over lives of the missions. We used AErosol RObotic NETwork (AERONET) data as ground truth and evaluated MISR and MODIS optical depth distributions relative to AERONET using simple linear regression. However, AERONET data are themselves instrumental measurements subject to sources of uncertainty. In this talk, we discuss results from an improved analysis of MISR and MODIS error distributions that uses errors-in-variables regression, accounting for uncertainties in both the dependent and independent variables. We demonstrate on optical depth data, but the method is generally applicable to other aerosol properties as well.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

PubMed Central

Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product

NASA Technical Reports Server (NTRS)

Vermote, Eric; Justice, Chris; Claverie, Martin; Franch, Belen

2016-01-01

The surface reflectance, i.e., satellite derived top of atmosphere (TOA) reflectance corrected for the temporally, spatially and spectrally varying scattering and absorbing effects of atmospheric gases and aerosols, is needed to monitor the land surface reliably. For this reason, the surface reflectance, and not TOA reflectance, is used to generate the greater majority of global land products, for example, from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Even if atmospheric effects are minimized by sensor design, atmospheric effects are still challenging to correct. In particular, the strong impact of aerosols in the visible and near infrared spectral range can be difficult to correct, because they can be highly discrete in space and time (e.g., smoke plumes) and because of the complex scattering and absorbing properties of aerosols that vary spectrally and with aerosol size, shape, chemistry and density.

Moderate Resolution Imaging Spectroradiometer (MODIS) Overview

USGS Publications Warehouse

,

2008-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) 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 MODIS instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make MODIS 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, MODIS acquires morning (EOS-Terra) and afternoon (EOS-Aqua) views almost daily. Terra data acquisitions began in February 2000 and Aqua 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. MODIS-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 MODIS 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 MODIS 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 Aqua MODIS data products.

Study of Sea Surface Temperatures changes due to tropical cyclone fanoos in the southwest Bay of Bengal using satellite and argo observations

NASA Astrophysics Data System (ADS)

Krishna Kailasam, Muni

Sea surface temperature (SST) plays an important role in the studies of global climate system and as a boundary condition for operational numerical forecasts. Estimation of SST has tra-ditionally been performed with satellite based sensors operating in the infrared (IR) portion of the electromagnetic spectrum, where the ocean emissivity is close to unity. The National Oceanic and Atmospheric Administration (NOAA) satellite series, the GOES Imagers on the Geostationary Operational Environmental Satellites, the Along Track Scanning Radiometer (ATSR) on the European Remote Sensing satellites and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA EOS platform are successful examples of IR sen-sors currently used for operational SST retrievals. Significant progress in SST retrieval from remote sensing data came with the introduction of a new low-frequency channel (10.7 GHz) on microwave (MW) sensors. The anthropogenic effects over a period of time resulted in increase of infrared absorbers such as greenhouse gases and absorbing aerosol would produce increase of both daytime maximum and nighttime minimum temperatures. In contrast, the increases of visible reflectors such as sulfate aerosols and low cloud amount would result in a decrease of the daytime maximum temperature. Solar radiation, wind stress and vertical mixing are known to be the three major factors impacting the SST seasonal variations. In the present study, impact of absorbing aerosols on the sea surface temperature (SST) over Bay of Bengal (BoB) region was investigated. Increased aerosol loading over BoB was observed due to advection of aerosols from continental region consisting of absorbing particles primarily from dust and biomass burning. This increased loading over BoB resulted in reduction of surface reaching solar radiation. Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) de-rived SST over BoB showed negative correlation with OMI-Aerosol Index (AI) (R = 0.87) and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) AOD550 (R = 0.77) suggesting reduction in SST due to absorption of incoming solar radiation by aerosols.

Fires and Smoke in Central Africa

NASA Technical Reports Server (NTRS)

2002-01-01

This year's fire season in central Africa may have been the most severe ever. This true-color image also shows the location of fires (red dots) in the Democratic Republic of the Congo, Angola, and Zambia. The image was taken by the Moderate-Resolution Imaging Spectroradiometer (MODIS) aboard NASA 's Terra spacecraft on August 23, 2000, and was produced using the MODIS Active Fire Detection product. NASA scientists studied these fires during the SAFARI 2000 field campaign. Image By Jacques Descloitres, MODIS Land Team

Airborne Spectral Measurements of Ocean Directional Reflectance

NASA Technical Reports Server (NTRS)

Gatebe, Charles K.; King, Michael D.; Lyapustin, Alexei; Arnold, G. Thomas; Redemann, Jens

2004-01-01

During summer of 2001 NASA's Cloud Absorption Radiometer (CAR) obtained measurement of ocean angular distribution of reflected radiation or BRDF (bidirectional reflectance distribution function) aboard the University of Washington Convair CV-580 research aircraft under cloud-free conditions. The measurements took place aver the Atlantic Ocean off the eastern seaboard of the U.S. in the vicinity of the Chesapeake Light Tower and at nearby National Oceanic and Atmospheric Administration (NOAA) Buoy Stations. The measurements were in support of CLAMS, Chesapeake Lighthouse and Aircraft Measurements for Satellites, field campaign that was primarily designed to validate and improve NASA's Earth Observing System (EOS) satellite data products being derived from three sensors: MODIS (MODerate Resolution Imaging Spectro-Radiometer), MISR (Multi-angle Imaging Spectro-Radiometer) and CERES (Clouds and Earth s Radiant Energy System). Because of the high resolution of the CAR measurements and its high sensitivity to detect weak ocean signals against a noisy background, results of radiance field above the ocean are seen in unprecedented detail. The study also attempts to validate the widely used Cox-Munk model for predicting reflectance from a rough ocean surface.

Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data

USGS Publications Warehouse

Henry, P.; Chander, G.; Fougnie, B.; Thomas, C.; Xiong, Xiaoxiong

2013-01-01

Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.

AOD trends during 2001-2010 from observations and model simulations

NASA Astrophysics Data System (ADS)

Pozzer, Andrea; de Meij, Alexander; Yoon, Jongmin; Astitha, Marina

2016-04-01

The trend of aerosol optical depth (AOD) between 2001 and 2010 is estimated globally and regionally from remote sensed observations by the MODIS (Moderate Resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer) and SeaWIFS (Sea-viewing Wide Field-of-view Sensor) satellite sensor. The resulting trends have been compared to model results from the EMAC (ECHAM5/MESSy Atmospheric Chemistry {[1]}), model. Although interannual variability is applied only to anthropogenic and biomass-burning emissions, the model is able to quantitatively reproduce the AOD trends as observed by MODIS, while some discrepancies are found when compared to MISR and SeaWIFS. An additional numerical simulation with the same model was performed, neglecting any temporal change in the emissions, i.e. with no interannual variability for any emission source. It is shown that decreasing AOD trends over the US and Europe are due to the decrease in the (anthropogenic) emissions. On contrary over the Sahara Desert and the Middle East region, the meteorological/dynamical changes in the last decade play a major role in driving the AOD trends. Further, over Southeast Asia, both meteorology and emissions changes are equally important in defining AOD trends {[2]}. Finally, decomposing the regional AOD trends into individual aerosol components reveals that the soluble components are the most dominant contributors to the total AOD, as their influence on the total AOD is enhanced by the aerosol water content. {[1]}: Jöckel, P., Kerkweg, A., Pozzer, A., Sander, R., Tost, H., Riede, H., Baumgaertner, A., Gromov, S., and Kern, B.: Development cycle 2 of the Modular Earth Submodel System (MESSy2), Geosci. Model Dev., 3, 717-752, doi:10.5194/gmd-3-717-2010, 2010. {[2]}: Pozzer, A., de Meij, A., Yoon, J., Tost, H., Georgoulias, A. K., and Astitha, M.: AOD trends during 2001-2010 from observations and model simulations, Atmos. Chem. Phys., 15, 5521-5535, doi:10.5194/acp-15-5521-2015, 2015.

Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-05-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S-NPP VIIRS as Part of the "Deep Blue" Aerosol Project

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Lee, J.; Bettenhausen, C.; Kim, W. V.; Smirnov, A.

2018-01-01

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over land. The SeaWiFS Deep Blue data set also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASA's VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASA's S-NPP VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550 nm AOD of order ±(0.03+10%), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Ångström exponent and fine-mode AOD fraction are also well correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.

Information content of visible and midinfrared radiances for retrieving tropical ice cloud properties

NASA Astrophysics Data System (ADS)

Chang, Kai-Wei; L'Ecuyer, Tristan S.; Kahn, Brian H.; Natraj, Vijay

2017-05-01

Hyperspectral instruments such as Atmospheric Infrared Sounder (AIRS) have spectrally dense observations effective for ice cloud retrievals. However, due to the large number of channels, only a small subset is typically used. It is crucial that this subset of channels be chosen to contain the maximum possible information about the retrieved variables. This study describes an information content analysis designed to select optimal channels for ice cloud retrievals. To account for variations in ice cloud properties, we perform channel selection over an ensemble of cloud regimes, extracted with a clustering algorithm, from a multiyear database at a tropical Atmospheric Radiation Measurement site. Multiple satellite viewing angles over land and ocean surfaces are considered to simulate the variations in observation scenarios. The results suggest that AIRS channels near wavelengths of 14, 10.4, 4.2, and 3.8 μm contain the most information. With an eye toward developing a joint AIRS-MODIS (Moderate Resolution Imaging Spectroradiometer) retrieval, the analysis is also applied to combined measurements from both instruments. While application of this method to MODIS yields results consistent with previous channel sensitivity studies, the analysis shows that this combination may yield substantial improvement in cloud retrievals. MODIS provides most information on optical thickness and particle size, aided by a better constraint on cloud vertical placement from AIRS. An alternate scenario where cloud top boundaries are supplied by the active sensors in the A-train is also explored. The more robust cloud placement afforded by active sensors shifts the optimal channels toward the window region and shortwave infrared, further constraining optical thickness and particle size.

Global trends in ocean phytoplankton: a new assessment using revised ocean colour data.

PubMed

Gregg, Watson W; Rousseaux, Cécile S; Franz, Bryan A

2017-01-01

A recent revision of the NASA global ocean colour record shows changes in global ocean chlorophyll trends. This new 18-year time series now includes three global satellite sensors, the Sea-viewing Wide Field of view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite (VIIRS). The major changes are radiometric drift correction, a new algorithm for chlorophyll, and a new sensor VIIRS. The new satellite data record shows no significant trend in global annual median chlorophyll from 1998 to 2015, in contrast to a statistically significant negative trend from 1998 to 2012 in the previous version. When revised satellite data are assimilated into a global ocean biogeochemical model, no trend is observed in global annual median chlorophyll. This is consistent with previous findings for the 1998-2012 time period using the previous processing version and only two sensors (SeaWiFS and MODIS). Detecting trends in ocean chlorophyll with satellites is sensitive to data processing options and radiometric drift correction. The assimilation of these data, however, reduces sensitivity to algorithms and radiometry, as well as the addition of a new sensor. This suggests the assimilation model has skill in detecting trends in global ocean colour. Using the assimilation model, spatial distributions of significant trends for the 18-year record (1998-2015) show recent decadal changes. Most notable are the North and Equatorial Indian Oceans basins, which exhibit a striking decline in chlorophyll. It is exemplified by declines in diatoms and chlorophytes, which in the model are large and intermediate size phytoplankton. This decline is partially compensated by significant increases in cyanobacteria, which represent very small phytoplankton. This suggests the beginning of a shift in phytoplankton composition in these tropical and subtropical Indian basins.

Deriving Aerosol Characteristics Over the Ocean from MODIS: Are We There Yet?

NASA Astrophysics Data System (ADS)

Remer, L. A.; Tanre, D.

2006-12-01

The MODerate resolution Imaging Spectroradiometer (MODIS) has been successfully retrieving aerosol characteristics over the ocean since shortly after the launch of the Terra satellite at the end of 1999. With its wide spectral range (0.47 to 2.13 μm) MODIS is able to derive spectral aerosol optical depth and information on the size of the aerosol particles. The products were quickly validated, the validation confirmed, and the products are now in wide use across the scientific community. The MODIS aerosol products over ocean are an outstanding success story, but are we done? As the years progress and we gain experience in using the products, evaluating them and nudging even greater information from them, we discover new challenges. Firstly, we continue to find issues affecting the integrity of the products we now produce. We need to find methods to reduce the uncertainty introduced by clouds that go beyond the classical concept of cloud masking and cloud contamination. Some of these novel cloud effects on aerosol retrieval include 3D scattering of light from cloud sides. Another issue that needs resolution is the uncertainty introduced by nonspherical particle shapes. Secondly, when MODIS was new we were excited to have spectral optical depth and particle size information. Now we find that aerosol characterization is still incomplete. We need more information. Are we there yet? Well, no, but we can see the future. To meet these new challenges we will need information beyond the spectral radiances that MODIS measures. We can see the future of satellite derivation of aerosol characteristics, and it looks more and more like a multi-sensor future.

Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

NASA Astrophysics Data System (ADS)

Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

2016-04-01

Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

High-frequency remote monitoring of large lakes with MODIS 500 m imagery

USGS Publications Warehouse

McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.

2012-01-01

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 (MODIS) sensors on Aqua/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 MODIS 500 m data and compared MODIS utility to Landsat-based methods. MODIS 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 reflectance. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, reflecting seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of MODIS 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 reflect 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.

Coast of the East Siberian Sea, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

Sea ice is pulling away from the coastline of northeastern Siberia in the east Siberia Sea. This true-color Moderate Resolution Imaging Spectroradiometer (MODIS) image from May 26, 2002, also the thinning of ice in bays and coves, and the blue reflection of the water from beneath causes the ice to appear bright blue. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Multitemporal MODIS-EVI relationships with precipitation and temperature at the Santa Rita Experimental Range

Treesearch

Jorry Z. U. Kaurivi; Alfredo R. Huete; Kamel Didan

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides temporal enhanced vegetation index (EVI) data at 250, 500, and 1,000 m spatial resolutions that can be compared to daily, weekly, monthly, and annual weather parameters. A study was conducted at the grassland site (less than 10 percent velvet mesquite [Prosopis juliflora, var. velutina]) and the...

Comparison of MODIS-derived land surface temperature with air temperature measurements

NASA Astrophysics Data System (ADS)

Georgiou, Andreas; Akçit, Nuhcan

2017-09-01

Air surface temperature is an important parameter for a wide range of applications such as agriculture, hydrology and climate change studies. Air temperature data is usually obtained from measurements made in meteorological stations, providing only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of air surface temperature at both regional and global scales. Land Surface (skin) Temperatures (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to groundbased near surface air (Tair) measurements obtained from 14 observational stations during 2011 to 2015, covering coastal, mountainous and urban areas over Cyprus. Combining Terra and Aqua LST-8 Day and Night acquisitions into a mean monthly value, provide a large number of LST observations and a better overall agreement with Tair. Comparison between mean monthly LSTs and mean monthly Tair for all sites and all seasons pooled together yields a very high correlation and biases. In addition, the presented high standard deviation can be explained by the influence of surface heterogeneity within MODIS 1km2 grid cells, the presence of undetected clouds and the inherent difference between LST and Tair. However, MODIS LST data proved to be a reliable proxy for surface temperature and mostly for studies requiring temperature reconstruction in areas with lack of observational stations.

Assessment of MODIS RSB Detector Uniformity Using Deep Convective Clouds

NASA Technical Reports Server (NTRS)

Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen

2016-01-01

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 reflective solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (MODIS). Each detector of MODIS 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 MODIS 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 Aqua 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 MODIS band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to reflectance images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.

Improvement in the cloud mask for Terra MODIS mitigated by electronic crosstalk correction in the 6.7 μm and 8.5 μm channels

NASA Astrophysics Data System (ADS)

Sun, Junqiang; Madhavan, S.; Wang, M.

2016-09-01

MODerate resolution Imaging Spectroradiometer (MODIS), a remarkable 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 Aqua (A) platforms which tracks the Earth in the morning and afternoon orbits. T-MODIS has continued to operate over 15 years easily surpassing the 6 year design life time on orbit. Of the several science products derived from MODIS, one of the primary derivatives is the MODIS Cloud Mask (MOD035). The cloud mask algorithm incorporates several of the MODIS channels in both reflective and thermal infrared wavelengths to identify cloud pixels from clear sky. Two of the thermal infrared channels used in detecting clouds are the 6.7 μm and 8.5 μm. Based on a difference threshold with the 11 μm channel, the 6.7 μm channel helps in identifying thick high clouds while the 8.5 μm channel being useful for identifying thin clouds. Starting 2010, it had been observed in the cloud mask products that several pixels have been misclassified due to the change in the thermal band radiometry. The long-term radiometric changes in these thermal channels have been attributed to the electronic crosstalk contamination. In this paper, the improvement in cloud detection using the 6.7 μm and 8.5 μm channels are demonstrated using the electronic crosstalk correction. The electronic crosstalk phenomena analysis and characterization were developed using the regular moon observation of MODIS and reported in several works. The results presented in this paper should significantly help in improving the MOD035 product, maintaining the long term dataset from T-MODIS which is important for global change monitoring.

On-Orbit Performance and Calibration Improvements For the Reflective Solar Bands of Terra and Aqua MODIS

NASA Technical Reports Server (NTRS)

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

2016-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) is the keystone instrument for NASAs 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 micrometers to 2.2 micrometers, 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 deg. 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 detail the recent calibration improvements implemented in the MODIS L1B C6.

Assessment of the Relative Accuracy of Hemispheric-Scale Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Kelly, Richard E.; Riggs, George A.; Chang, Alfred T. C.; Foster, James L.; Houser, Paul (Technical Monitor)

2001-01-01

There are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period October 23 - December 25, 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), which both rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, however discrepancies exist as to the location and extent of the snow cover among those maps. The large (approx. 30 km) footprint of the SSM/I data and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.32 million sq km in the amount of snow mapped using MODIS versus SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping ability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.

Development of IDEA product for GOES-R aerosol data

NASA Astrophysics Data System (ADS)

Zhang, Hai; Hoff, Raymond M.; Kondragunta, Shobha

2009-08-01

The NOAA GOES-R Advanced Baseline Imager (ABI) will have nearly the same capabilities as NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) to generate multi-wavelength retrievals of aerosol optical depth (AOD) with high temporal and spatial resolution, which can be used as a surrogate of surface particulate measurements such as PM2.5 (particulate matter with diameter less than 2.5 μm). To prepare for the launch of GOES-R and its application in the air quality forecasting, we have transferred and enhanced the Infusing satellite Data into Environmental Applications (IDEA) product from University of Wisconsin to NOAA NESDIS. IDEA was created through a NASA/EPA/NOAA cooperative effort. The enhanced IDEA product provides near-real-time imagery of AOD derived from multiple satellite sensors including MODIS Terra, MODIS Aqua, GOES EAST and GOES WEST imager. Air quality forecast guidance is produced through a trajectory model initiated at locations with high AOD retrievals and/or high aerosol index (AI) from OMI (Ozone Monitoring Instrument). The product is currently running at http://www.star.nesdis.noaa.gov/smcd/spb/aq/. The IDEA system will be tested using the GOES-R ABI proxy dataset, and will be ready to operate with GOES-R aerosol data when GOES-R is launched.

Mapping wildfire burn severity in the Arctic Tundra from downsampled MODIS data

USGS Publications Warehouse

Kolden, Crystal A.; Rogan, John

2013-01-01

Wildfires are historically infrequent in the arctic tundra, but are projected to increase with climate warming. Fire effects on tundra ecosystems are poorly understood and difficult to quantify in a remote region where a short growing season severely limits ground data collection. Remote sensing has been widely utilized to characterize wildfire regimes, but primarily from the Landsat sensor, which has limited data acquisition in the Arctic. Here, coarse-resolution remotely sensed data are assessed as a means to quantify wildfire burn severity of the 2007 Anaktuvuk River Fire in Alaska, the largest tundra wildfire ever recorded on Alaska's North Slope. Data from Landsat Thematic Mapper (TM) and downsampled Moderate-resolution Imaging Spectroradiometer (MODIS) were processed to spectral indices and correlated to observed metrics of surface, subsurface, and comprehensive burn severity. Spectral indices were strongly correlated to surface severity (maximum R2 = 0.88) and slightly less strongly correlated to substrate severity. Downsampled MODIS data showed a decrease in severity one year post-fire, corroborating rapid vegetation regeneration observed on the burned site. These results indicate that widely-used spectral indices and downsampled coarse-resolution data provide a reasonable supplement to often-limited ground data collection for analysis and long-term monitoring of wildfire effects in arctic ecosystems.

Application of Polarization to the MODIS Aerosol Retrieval Over Land

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine R.; Kaufman, Yoram J.

2004-01-01

Reflectance measurements in the visible and infrared wavelengths, from the Moderate Resolution Imaging Spectroradiometer (MODIS), are used to derive aerosol optical thicknesses (AOT) and aerosol properties over land surfaces. The measured spectral reflectance is compared with lookup tables, containing theoretical reflectance 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 reflectance. 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 reflectance differences at the TOA, with and without polarization. We find that the differences in blue channel TOA reflectance (vector - scalar) may reach values of 0.01 or greater, depending on the sun/surface/sensor scattering geometry. Reflectance 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 MODIS over land will include polarization.

In-Situ Transfer Standard and Coincident-View Intercomparisons for Sensor Cross-Calibration

NASA Technical Reports Server (NTRS)

Thome, Kurt; McCorkel, Joel; Czapla-Myers, Jeff

2013-01-01

There exist numerous methods for accomplishing on-orbit calibration. Methods include the reflectance-based approach relying on measurements of surface and atmospheric properties at the time of a sensor overpass as well as invariant scene approaches relying on knowledge of the temporal characteristics of the site. The current work examines typical cross-calibration methods and discusses the expected uncertainties of the methods. Data from the Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), Moderate Resolution Imaging Spectroradiometer (MODIS), and Thematic Mapper (TM) are used to demonstrate the limits of relative sensor-to-sensor calibration as applied to current sensors while Landsat-5 TM and Landsat-7 ETM+ are used to evaluate the limits of in situ site characterizations for SI-traceable cross calibration. The current work examines the difficulties in trending of results from cross-calibration approaches taking into account sampling issues, site-to-site variability, and accuracy of the method. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The results show that cross calibrations with absolute uncertainties lesser than 1.5 percent (1 sigma) are currently achievable even for sensors without coincident views.

Comparing MODIS-Terra and GOES surface albedo for New York City NY, Baltimore MD and Washington DC for 2005

NASA Astrophysics Data System (ADS)

Mubenga, K.; Hoff, R.; McCann, K.; Chu, A.; Prados, A.

2006-05-01

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 MODIS, 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 (MODIS) sensor on the Earth Observing System Terra and Aqua platforms provides an independent measurement of the surface albedo at a resolution greater than available on GOES. In this research, the MODIS 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 reflectance. Int.Journal of Remote Sensing 26, 4097-4116

Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods

Treesearch

Zhuosen Wang; Crystal B. Schaaf; Alan H. Strahler; Mark J. Chopping; Miguel O. Román; Yanmin Shuai; Curtis E. Woodcock; David Y. Hollinger; David R. Fitzjarrald

2014-01-01

This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and...

Alerts of forest disturbance from MODIS imagery

NASA Astrophysics Data System (ADS)

Hammer, Dan; Kraft, Robin; Wheeler, David

2014-12-01

This paper reports the methodology and computational strategy for a forest cover disturbance alerting system. Analytical techniques from time series econometrics are applied to imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to detect temporal instability in vegetation indices. The characteristics from each MODIS pixel's spectral history are extracted and compared against historical data on forest cover loss to develop a geographically localized classification rule that can be applied across the humid tropical biome. The final output is a probability of forest disturbance for each 500 m pixel that is updated every 16 days. The primary objective is to provide high-confidence alerts of forest disturbance, while minimizing false positives. We find that the alerts serve this purpose exceedingly well in Pará, Brazil, with high probability alerts garnering a user accuracy of 98 percent over the training period and 93 percent after the training period (2000-2005) when compared against the PRODES deforestation data set, which is used to assess spatial accuracy. Implemented in Clojure and Java on the Hadoop distributed data processing platform, the algorithm is a fast, automated, and open source system for detecting forest disturbance. It is intended to be used in conjunction with higher-resolution imagery and data products that cannot be updated as quickly as MODIS-based data products. By highlighting hotspots of change, the algorithm and associated output can focus high-resolution data acquisition and aid in efforts to enforce local forest conservation efforts.

Satellite and Surface Perspectives of Snow Extent in the Southern Appalachian Mountains

NASA Technical Reports Server (NTRS)

Sugg, Johnathan W.; Perry, Baker L.; Hall, Dorothy K.

2012-01-01

Assessing snow cover patterns in mountain regions remains a challenge for a variety of reasons. Topography (e.g., elevation, exposure, aspect, and slope) strongly influences snowfall accumulation and subsequent ablation processes, leading to pronounced spatial variability of snow cover. In-situ observations are typically limited to open areas at lower elevations (<1000 m). In this paper, we use several products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess snow cover extent in the Southern Appalachian Mountains (SAM). MODIS daily snow cover maps and true color imagery are analyzed after selected snow events (e.g., Gulf/Atlantic Lows, Alberta Clippers, and Northwest Upslope Flow) from 2006 to 2012 to assess the spatial patterns of snowfall across the SAM. For each event, we calculate snow cover area across the SAM using MODIS data and compare with the Interactive Multi-sensor Snow and ice mapping system (IMS) and available in-situ observations. Results indicate that Gulf/Atlantic Lows are typically responsible for greater snow extent across the entire SAM region due to intensified cyclogenesis associated with these events. Northwest Upslope Flow events result in snow cover extent that is limited to higher elevations (>1000 m) across the SAM, but also more pronounced along NW aspects. Despite some limitations related to the presence of ephemeral snow or cloud cover immediately after each event, we conclude that MODIS products are useful for assessing the spatial variability of snow cover in heavily forested mountain regions such as the SAM.

Assessment of Terra MODIS On-Orbit Polarization Sensitivity Using Pseudoinvariant Desert Sites

NASA Technical Reports Server (NTRS)

Wu, Aisheng; Geng, Xu; Wald, Andrew; Angal, Amit; Xiong, Xiaoxiong

2017-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is currently flying on NASA's Earth Observing System Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS reflective solar bands in the visible wavelength range are known to be sensitive to polarized light based on prelaunch polarization sensitivity tests. After about five years of on-orbit operations, it was discovered that the polarization sensitivity at short wavelengths had shown a noticeable increase. In this paper, we examine the impact of polarization on measured top-of-atmosphere (TOA) reflectance based on MODIS Collection-6 L1B over pseudo invariant desert sites. The standard polarization correction equation is used in combination with simulated at-sensor radiances using the second simulation of a satellite signal in the Solar Spectrum, Vector Radiative Transfer Code (6SV). We ignore the polarization contribution from the surface and a ratio approach is used for both 6SV-derived in put parameters and observed TOA reflectance. Results indicate that significant gain corrections up to 25% are required near the end of scan for the 412 and 443 nm bands. The polarization correction reduces the seasonal fluctuations in reflectance trends and mirror side ratios from 30% and 12% to 10% and 5%, respectively, for the two bands. Comparison of the effectiveness of the polarization correction with the results from the NASA Ocean Biology Processing Group shows a good agreement in the corrected reflectance trending results and their seasonal fluctuations.

MODIS Solar Diffuser Attenuation Screen Modeling Results

NASA Technical Reports Server (NTRS)

Waluschka, Eugene; Xuong, Xiaoxiong; Guenther, Bruce; Barnes, William

2004-01-01

On-orbit calibration of the reflected solar bands on the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) is accomplished by have the instrument view a high reflectance diffuse surface illuminated by the sun. For some of the spectral bands this proves to be much too bright a signal that results in the saturation of detectors designed for measuring low reflectance (ocean) surfaces signals. A mechanical attenuation device in the form of a pin hole screen is used to reduce the signals to calibrate these bands. The sensor response to solar illumination of the SD with and without the attenuation screen in place will be presented. The MODIS detector response to the solar diffuser is smooth when the attenuation screen is absent, but has structures up to a few percent when the attenuation screen is present. This structure corresponds to non-uniform illumination from the solar diffuser. Each pin hole produces a pin-hole image of the sun on the solar diffuser, and there are very many pin hole images of the sun on the solar diffuser for each MODIS detector. Even though there are very many pin-hole images of the sun on the solar diffuser, it is no longer perfectly uniformly illuminated. This non-uniformly illuminated solar diffuser produces intensity variation on the focal planes. The results of a very detailed simulation will be discussed which show how the illumination of the focal plane changes as a result of the attenuation, and the impacts on the calibration will be discussed.

Dynamics of the turbidity maximum zone in a macrotidal estuary (the Gironde, France): Observations from field and MODIS satellite data

NASA Astrophysics Data System (ADS)

Doxaran, David; Froidefond, Jean-Marie; Castaing, Patrice; Babin, Marcel

2009-02-01

Over a 1-year period, field and satellite measurements of surface water turbidity were combined in order to study the dynamics of the turbidity maximum zone (TM) in a macrotidal estuary (the Gironde, France). Four fixed platforms equipped with turbidity sensors calibrated to give the suspended particulate matter (SPM) concentration provided continuous information in the upper estuary. Full resolution data recorded by the moderate resolution imaging spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellite platforms provided information in the central and lower estuary twice a day (depending on cloud cover). Field data were used to validate a recently developed SPM quantification algorithm applied to the MODIS 'surface reflectance' product. The algorithm is based on a relationship between the SPM concentration and a reflectance ratio of MODIS bands 2 (near-infrared) and 1 (red). Based on 62 and 75 match-ups identified in 2005 with MODIS Terra and Aqua data, the relative uncertainty of the algorithm applied to these sensors was found to be 22 and 18%, respectively. Field measurements showed the tidal variations of turbidity in the upper estuary, while monthly-averaged MODIS satellite data complemented by field data allowed observing the monthly movements of the TM in the whole estuary. The trapping of fine sediments occurred in the upper estuary during the period of low river flow. This resulted in the formation of a highly concentrated TM during a 4-month period. With increasing river flow, the TM moved rapidly to the central estuary. A part of the TM detached, moved progressively in the lower estuary and was finally either massively exported to the ocean during peak floods or temporary trapped (settled) on intertidal mudflats. The massive export to the ocean was apparently the result of combined favorable environmental conditions: presence of fluid mud near the mouth, high river flow, high tides and limited wind speeds. The mean SPM concentration within surface waters of the whole estuary showed strong seasonal variations but remained almost unchanged on a 1-year-basis. These observations suggest that the masses of suspended sediments exported toward the ocean and supplied by the rivers were almost equivalent during the year investigated (2005). Results show the usefulness of information extracted from combined field and current ocean color satellite data in order to monitor the transport of suspended particles in coastal and estuarine waters.

Computational provenance in hydrologic science: a snow mapping example.

PubMed

Dozier, Jeff; Frew, James

2009-03-13

Computational provenance--a record of the antecedents and processing history of digital information--is key to properly documenting computer-based scientific research. To support investigations in hydrologic science, we produce the daily fractional snow-covered area from NASA's moderate-resolution imaging spectroradiometer (MODIS). From the MODIS reflectance data in seven wavelengths, we estimate the fraction of each 500 m pixel that snow covers. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry, so we interpolate and smooth to produce our best estimate of the daily snow cover. To manage the data, we have developed the Earth System Science Server (ES3), a software environment for data-intensive Earth science, with unique capabilities for automatically and transparently capturing and managing the provenance of arbitrary computations. Transparent acquisition avoids the scientists having to express their computations in specific languages or schemas in order for provenance to be acquired and maintained. ES3 models provenance as relationships between processes and their input and output files. It is particularly suited to capturing the provenance of an evolving algorithm whose components span multiple languages and execution environments.

Remote Sensing of Suspended Sediments and Shallow Coastal Waters

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram J.; Gao, Bo-Cai; Davis, Curtiss O.

2002-01-01

Ocean color sensors were designed mainly for remote sensing of chlorophyll concentrations over the clear open oceanic areas (case 1 water) using channels between 0.4 and 0.86 micrometers. The Moderate Resolution Imaging Spectroradiometer (MODIS) launched on the NASA Terra and Aqua Spacecrafts is equipped with narrow channels located within a wider wavelength range between 0.4 and 2.5 micrometers for a variety of remote sensing applications. The wide spectral range can provide improved capabilities for remote sensing of the more complex and turbid coastal waters (case 2 water) and for improved atmospheric corrections for Ocean scenes. In this article, we describe an empirical algorithm that uses this wide spectral range to identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. The algorithm takes advantage of the strong water absorption at wavelengths longer than 1 micrometer that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS 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.

Terrestrial vegetation dynamics and global climate controls

NASA Astrophysics Data System (ADS)

Potter, Christopher; Boriah, Shyam; Steinbach, Michael; Kumar, Vipin; Klooster, Steven

2008-07-01

Monthly data from the moderate resolution imaging spectroradiometer (MODIS) and its predecessor satellite sensors was used to reconstruct vegetation dynamics in response to climate patterns over the period 1983 2005. Results suggest that plant growth over extensive land areas of southern Africa and Central Asia were the most closely coupled of any major land area to El Niño southern oscillation (ENSO) effects on regional climate. Others land areas strongly tied to recent ENSO climate effects were in northern Canada, Alaska, western US, northern Mexico, northern Argentina, and Australia. Localized variations in precipitation were the most common controllers of monthly values for the fraction absorbed of photosynthetically active radiation (FPAR) over these regions. In addition to the areas cited above, seasonal FPAR values from MODIS were closely coupled to rainfall patterns in grassland and cropland areas of the northern and central US. Historical associations between global vegetation FPAR and atmospheric carbon dioxide (CO2) anomalies suggest that the terrestrial biosphere can contribute major fluxes of CO2 during major drought events, such as those triggered by 1997 1998 El Niño event.

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

The Global Aerosol System As Viewed By MODIS Today

NASA Technical Reports Server (NTRS)

Remer, Lorraine

2008-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms have been working steadily since early 2000 to transform the MODIS-measured spectral solar reflectance from the Earth's surface and atmosphere into a variety of aerosol products. In this lecture I will proceed through a survey of these products, answering the following questions as I proceed. What are the products? How do they compare with ground truth? How do we use these products to describe the global aerosol system? Are aerosols increasing or decreasing? How do aerosols affect climate and clouds?

On-orbit characterization of hyperspectral imagers

NASA Astrophysics Data System (ADS)

McCorkel, Joel

Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne- and satellite-based sensors. Often, ground-truth measurements at these tests sites are not always successful due to weather and funding availability. Therefore, RSG has also employed automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor. This dissertation presents a method for determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on a multispectral sensor, Moderate-resolution Imaging Spectroradiometer (MODIS), as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. A method to predict hyperspectral surface reflectance using a combination of MODIS data and spectral shape information is developed and applied for the characterization of Hyperion. Spectral shape information is based on RSG's historical in situ data for the Railroad Valley test site and spectral library data for the Libyan test site. Average atmospheric parameters, also based on historical measurements, are used in reflectance prediction and transfer to space. Results of several cross-calibration scenarios that differ in image acquisition coincidence, test site, and reference sensor are found for the characterization of Hyperion. These are compared with results from the reflectance-based approach of vicarious calibration, a well-documented method developed by the RSG that serves as a baseline for calibration performance for the cross-calibration method developed here. Cross-calibration provides results that are within 2% of those of reflectance-based results in most spectral regions. Larger disagreements exist for shorter wavelengths studied in this work as well as in spectral areas that experience absorption by the atmosphere.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.

Remote Sensing of Water Vapor and Thin Cirrus Clouds using MODIS Near-IR Channels

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yoram J.

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major facility instrument on board the Terra Spacecraft, was successfully launched into space in December of 1999. MODIS has several near-IR channels within and around the 0.94 micrometer water vapor bands for remote sensing of integrated atmospheric water vapor over land and above clouds. MODIS also has a special near-IR channel centered at 1.375-micron with a width of 30 nm for remote sensing of cirrus clouds. In this paper, we describe briefly the physical principles on remote sensing of water vapor and cirrus clouds using these channels. We also present sample water vapor images and cirrus cloud images obtained from MODIS data.

Aerosol Optical Depth Retrievals from High-Resolution Commercial Satellite Imagery Over Areas of High Surface Reflectance

DTIC Science & Technology

2006-06-01

angle Imaging SpectroRadiometer MODIS Moderate Resolution Imaging Spectroradiometer NGA National Geospatial Intelligence Agency POI Principles of...and µ , the cosine of the viewing zenith angle and the effect of the variation of each of these variables on total optical depth. Extraterrestrial ...Eq. (34). Additionally, solar zenith angle also plays a role in the third term on the RHS of Eq. (34) by modifying extraterrestrial spectral solar

MISR Aerosol Product Attributes and Statistical Comparisons with MODIS

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Nelson, David L.; Garay, Michael J.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Paradise, Susan R.; Hansen, Earl G.; Remer, Lorraine A.

2009-01-01

In this paper, Multi-angle Imaging SpectroRadiometer (MISR) aerosol product attributes are described, including geometry and algorithm performance flags. Actual retrieval coverage is mapped and explained in detail using representative global monthly data. Statistical comparisons are made with coincident aerosol optical depth (AOD) and Angstrom exponent (ANG) retrieval results from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The relationship between these results and the ones previously obtained for MISR and MODIS individually, based on comparisons with coincident ground-truth observations, is established. For the data examined, MISR and MODIS each obtain successful aerosol retrievals about 15% of the time, and coincident MISR-MODIS aerosol retrievals are obtained for about 6%-7% of the total overlap region. Cloud avoidance, glint and oblique-Sun exclusions, and other algorithm physical limitations account for these results. For both MISR and MODIS, successful retrievals are obtained for over 75% of locations where attempts are made. Where coincident AOD retrievals are obtained over ocean, the MISR-MODIS correlation coefficient is about 0.9; over land, the correlation coefficient is about 0.7. Differences are traced to specific known algorithm issues or conditions. Over-ocean ANG comparisons yield a correlation of 0.67, showing consistency in distinguishing aerosol air masses dominated by coarse-mode versus fine-mode particles. Sampling considerations imply that care must be taken when assessing monthly global aerosol direct radiative forcing and AOD trends with these products, but they can be used directly for many other applications, such as regional AOD gradient and aerosol air mass type mapping and aerosol transport model validation. Users are urged to take seriously the published product data-quality statements.

Ocean Data from MODIS at the NASA Goddard DAAC

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory G.; Wharton, Stephen (Technical Monitor)

2000-01-01

Terra satellite carrying the Moderate Resolution Imaging Spectroradiometer (MODIS) was successfully launched on December 18, 1999. Some of the 36 different wavelengths that MODIS samples have never before been measured from space. New ocean data products, which have not been derived on a global scale before, are made available for research to the scientific community. For example, MODIS uses a new split window in the four-micron region for the better measurement of Sea Surface Temperature (SST), and provides the unprecedented ability (683 nm band) to measure chlorophyll fluorescence. At full ocean production, more than a thousand different ocean products in three major categories (ocean color, sea surface temperature, and ocean primary production) are archived at the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) at the rate of approx. 230GB/day. The challenge is to distribute such large volumes of data to the ocean community. It is achieved through a combination of public and restricted EOS Data Gateways, the GES DAAC Search and Order WWW interface, and an FTP site that contains samples of MODIS data. A new Search and Order WWW interface at http://acdisx.gsfc.nasa.gov/data/ developed at the GES DAAC is based on a hierarchical organization of data, will always return non-zero results. It has a very convenient geographical representation of five-minute data granule coverage for each day MODIS Data Support Team (MDST) continues the tradition of quality support at the GES DAAC for the ocean color data from the Coastal Zone Color Scanner (CZCS) and the Sea Viewing Wide Field-of-View Sensor (SeaWiFS) by providing expert assistance to users in accessing data products, information on visualization tools, documentation for data products and formats (Hierarchical Data Format-Earth Observing System (HDF-EOS)), information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN DOCS/MODIS/index.html

Evaluating MODIS satellite versus terrestrial data driven productivity estimates in Austria

NASA Astrophysics Data System (ADS)

Petritsch, R.; Boisvenue, C.; Pietsch, S. A.; Hasenauer, H.; Running, S. W.

2009-04-01

Sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite, are developed for monitoring global and/or regional ecosystem fluxes like net primary production (NPP). Although these systems should allow us to assess carbon sequestration issues, forest management impacts, etc., relatively little is known about the consistency and accuracy in the resulting satellite driven estimates versus production estimates driven from ground data. In this study we compare the following NPP estimation methods: (i) NPP estimates as derived from MODIS and available on the internet; (ii) estimates resulting from the off-line version of the MODIS algorithm; (iii) estimates using regional meteorological data within the offline algorithm; (iv) NPP estimates from a species specific biogeochemical ecosystem model adopted for Alpine conditions; and (v) NPP estimates calculated from individual tree measurements. Single tree measurements were available from 624 forested sites across Austria but only the data from 165 sample plots included all the necessary information for performing the comparison on plot level. To ensure independence of satellite-driven and ground-based predictions, only latitude and longitude for each site were used to obtain MODIS estimates. Along with the comparison of the different methods, we discuss problems like the differing dates of field campaigns (<1999) and acquisition of satellite images (2000-2005) or incompatible productivity definitions within the methods and come up with a framework for combining terrestrial and satellite data based productivity estimates. On average MODIS estimates agreed well with the output of the models self-initialization (spin-up) and biomass increment calculated from tree measurements is not significantly different from model results; however, correlation between satellite-derived versus terrestrial estimates are relatively poor. Considering the different scales as they are 9km² from MODIS and 1000m² from the sample plots together with the heterogeneous landscape may qualify the low correlation, particularly as the correlation increases when strongly fragmented sites are left out.

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

2007-01-01

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2005-05-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Land product validation of MODIS derived FPAR product over the tropical dry-forest of Santa Rosa National Park, Guanacaste, Costa Rica.

NASA Astrophysics Data System (ADS)

Sharp, Iain; Sanchez, Arturo

2017-04-01

Land-product validation of the MODIS derived FPAR product over the tropical dry-forest of Santa Rosa National Park, Guanacaste, Costa Rica. By Iain Sharp & Dr. Arturo Sanchez-Azofeifa In remote sensing, being able to ensure the accuracy of the satellite data being produced remains an issue; this is especially true for phenological variables such as the Fraction of Photosynthetically Active Radiation (FPAR). FPAR, which is considered an essential climate variable by the Global Terrestrial Observation System (GTOS), utilizes the 400-700 nm wavelength range to quantify the total amount of solar radiation available for photosynthetic use. It is a variable that is strongly influenced by the seasonal, diurnal, and optic properties of vegetation making it an accurate representation of vegetation health. Measurements of ground level FPAR can be completed using flux towers along with a limited number of wireless ground sensors, but due to the finite number and location of these towers, many research initiatives instead use the Moderate resolution Imaging Spectroradiometer (MODIS) FPAR product, which converts Leaf Area Index (LAI) to a FPAR value using Beer's Law. This is done despite there being little consensus on whether this is the best method to use for all ecosystems and vegetation types. One particular ecosystem that has had limited study to determine the accuracy of the MODIS derived FPAR products are the Tropical Dry Forests (TDFs) of Latin America. This ecosystem undergoes drastic seasonal changes from leaf off during the dry season to green-up during the wet seasons. This study aims to test the congruency between the MODIS derived FPAR values and ground-based FPAR values in relation to growing season length, growing season start and end dates, the peak and mean of FPAR values, and overall growth/phenological trends at the Santa Rosa National Park Environmental Monitoring Super Site (SR-EMSS) in Costa Rica and FPAR MODIS products. We derive our FPAR from a Wireless Sensor Network (WSN) consisting of more than 50 nodes measuring transmitted PAR, temperature, relative humidity, and soil moisture over custom time intervals ranging from 2-Hz to 15 min since 2013. Our fundamental goal is to demonstrate how accurate and reflective the MODIS derived FPAR product is of TDF phenology. This will be the first step taken in identifying potential problems with the MODIS derived FPAR products over TDFs in the Americas.

Massive Cloud-Based Big Data Processing for Ocean Sensor Networks and Remote Sensing

NASA Astrophysics Data System (ADS)

Schwehr, K. D.

2017-12-01

Until recently, the work required to integrate and analyze data for global-scale environmental issues was prohibitive both in cost and availability. Traditional desktop processing systems are not able to effectively store and process all the data, and super computer solutions are financially out of the reach of most people. The availability of large-scale cloud computing has created tools that are usable by small groups and individuals regardless of financial resources or locally available computational resources. These systems give scientists and policymakers the ability to see how critical resources are being used across the globe with little or no barrier to entry. Google Earth Engine has the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra, MODIS Aqua, and Global Land Data Assimilation Systems (GLDAS) data catalogs available live online. Here we demonstrate these data to calculate the correlation between lagged chlorophyll and rainfall to identify areas of eutrophication, matching these events to ocean currents from datasets like HYbrid Coordinate Ocean Model (HYCOM) to check if there are constraints from oceanographic configurations. The system can provide addition ground truth with observations from sensor networks like the International Comprehensive Ocean-Atmosphere Data Set / Voluntary Observing Ship (ICOADS/VOS) and Argo floats. This presentation is intended to introduce users to the datasets, programming idioms, and functionality of Earth Engine for large-scale, data-driven oceanography.

Validation of MODIS Aerosol Retrieval Over Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Mattoo, Shana; Levy, Robert; Chu, D. Allen; Holben, Brent N.; Dubovik, Oleg; Ahmad, Ziauddin;

Snow and Ice Mask for the MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Remer, Lorraine; Kaufman, Yoram J.; Mattoo, Shana; Gao, Bo-Cai; Vermote, Eric

2005-01-01

The atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging SpectroRadiometers (MODIS) on board the NASA Terra and Aqua spacecrafts. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-IR channels centered near 0.86 and 1.24 pm and a thermal emission channel near 11 pm to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.

The Synergistic Use of NASA's A-Train Observations to Characterize the Planetary Boundary Layer and Enable Improved Understanding and Prediction of Land-Atmosphere Interactions

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Santanello, J. A.; Friedl, M. A.; Susskind, J.; Palm, S. P.

2010-12-01

The planetary boundary layer (PBL) serves as a short-term memory of land-atmosphere (L-A) interactions through the diurnal integration of surface fluxes and subsequent evolution of PBL fluxes and states. Recent advances in satellite remote sensing offer the ability to monitor PBL and land surface properties at increasingly high spatial and temporal resolutions and, consequently, have the potential to provide valuable information on the terrestrial energy and water cycle across a range of scales. In this study, we evaluate the retrieval of PBL structure and temperature and moisture properties from measurements made by NASA's Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), Moderate Resolution Imaging Spectroradiometer (MODIS) , and Atmospheric Infrared Sounder (AIRS) instruments aboard the 'A-Train' constellation. The global coverage of these sensors greatly improves upon the coarse network of synoptic radiosonde and intermittent satellite and ground remote sensing currently available, and combining the high vertical and spectral resolution of these sensors allows for PBL retrievals to be evaluated in the context of their relationship with the land surface. Results include an evaluation of CALIPSO, MODIS, and AIRS temperature and humidity retrievals using radiosonde data, focusing on how well PBL properties (e.g. PBL height, temperature, humidity, and stability) can be discerned from each sensor under a range of conditions. Overall, this research is timely in assessing the potential for merging complimentary information from independent sensors, and provides a unique opportunity to evaluate and apply NASA data to answer fundamental questions regarding observation, understanding, and prediction of L-A interactions and coupling.

Sulfur plumes off Namibia

NASA Technical Reports Server (NTRS)

2002-01-01

Sulfur plumes rising up from the bottom of the ocean floor produce colorful swirls in the waters off the coast of Namibia in southern Africa. The plumes come from the breakdown of marine plant matter by anaerobic bacteria that do not need oxygen to live. This image was acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite on April 24, 2002 Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) Global Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; Scharfen, Greg R.

2000-01-01

Following the 1999 launch of the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), the capability exists to produce global snow-cover maps on a daily basis at 500-m resolution. Eight-day composite snow-cover maps will also be available. MODIS snow-cover products are produced at Goddard Space Flight Center and archived and distributed by the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado. The products are available in both orbital and gridded formats. An online search and order tool and user-services staff will be available at NSIDC to assist users with the snow products. The snow maps are available at a spatial resolution of 500 m, and 1/4 degree x 1/4 degree spatial resolution, and provide information on sub-pixel (fractional) snow cover. Pre-launch validation work has shown that the MODIS snow-mapping algorithms perform best under conditions of continuous snow cover in low vegetation areas, but can also map snow cover in dense forests. Post-launch validation activities will be performed using field and aircraft measurements from a February 2000 validation mission, as well as from existing satellite-derived snow-cover maps from NOAA and Landsat-7 Enhanced Thematic Mapper Plus (ETM+).

Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

DOE Office of Scientific and Technical Information (OSTI.GOV)

Misra, Amit; Kanawade, Vijay P.; Tripathi, Sachchida Nand

Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD andmore » MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. In conclusion, latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.« less

Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

DOE PAGES

Misra, Amit; Kanawade, Vijay P.; Tripathi, Sachchida Nand

2016-08-03

Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD andmore » MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. In conclusion, latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.« less

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maclaurin, Galen; Sengupta, Manajit; Xie, Yu

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance)more » broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the Northern Hemisphere for the temporal extent of the NSRDB (1998-2015). We provide a review of validation studies conducted on these two products and describe the methodology developed by NREL to remap the data products to the NSRDB grid and integrate them into a seamless daily data set.« less

Improving Access to MODIS Biophysical Science Products for NACP Investigators

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Gao, Feng; Morisette, Jeffrey T.; Ederer, Gregory A.; Pedelty, Jeffrey A.

2007-01-01

MODIS 4 NACP is a NASA-funded project supporting the North American Carbon Program (NACP). The purpose of this Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) project is to provide researchers with Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical data products that are custom tailored for use in NACP model studies. Standard MODIS biophysical products provide used to improve our understanding on the climate and ecosystem changes. However, direct uses of the MODIS biophysical parameters are constrained by retrieval quality and cloud contamination. Another challenge that NACP users face is acquiring MODIS data in formats and at spatial-temporal resolutions consistent with other data sets they use. We have been working closely with key NACP users to tailor the MODIS products to fit their needs. First, we provide new temporally smoothed and spatially continuous MODIS biophysical data sets. Second, we are distributing MODIS data at suitable spatial-temporal resolutions and in formats consistent with other data integration into model studies.

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-01-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Inversion of AMSR-E observations for land surface temperature estimation: 2. Global comparison with infrared satellite temperature

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Jiménez, C.; Prigent, C.; Trigo, I. F.; DaCamara, C. C.

2017-03-01

A comparison of land surface temperature (Ts) derived from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) with infrared Ts is presented. The infrared Ts include clear-sky estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Spinning Enhanced Visible and Infrared Imager, the Geostationary Operational Environmental Satellite (GOES) Imager, and the Japanese Meteorological Imager. The higher discrepancies between AMSR-E and MODIS are observed over deserts and snow-covered areas. The former seems to be associated with Ts underestimation by MODIS, whereas the latter is mostly related to uncertainties in microwave emissivity over snow/ice. Ts differences between AMSR-E and MODIS are significantly reduced after masking out snow and deserts, with a bias change from 2.6/4.6 K to 3.0/1.4 K for daytime/nighttime and a standard deviation (STD) decrease from 7.3/7.9 K to 5.1/3.9 K. When comparing with all infrared sensors, the STD of the differences between microwave and infrared Ts is generally higher than between IR retrievals. However, the biases between microwave and infrared Ts are, in some cases, of the same order as the ones observed between infrared products. This is the case for GOES, with daytime biases with respect to AMSR-E and MODIS of 0.45 K and 0.60 K, respectively. While the infrared Ts are clear-sky estimates, AMSR-E also provides Ts under cloudy conditions. For frequently cloudy regions, this results in a large increase of available Ts estimates (>250%), making the microwave Ts a very powerful complement of the infrared estimates.

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data

PubMed Central

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2016-01-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting. PMID:27667901

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data.

PubMed

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2015-08-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

Snow-Cover Variability in North America in the 2000-2001 Winter as Determined from MODIS Snow Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Janet Y. L.; Houser, Paul R. (Technical Monitor)

2001-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500 m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5 km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.

Snow-Cover Variability in North America in the 2000-2001 Winter as Determined from MODIS Snow Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Y. L.; Houser, Paul R. (Technical Monitor)

2001-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500-m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5-km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.

A Decade of Satellite Ocean Color Observations

NASA Technical Reports Server (NTRS)

McClain, Charles R.

2009-01-01

After the successful Coastal Zone Color Scanner (CZCS, 1978-1986), demonstration that quantitative estimations of geophysical variables such as chlorophyll a and diffuse attenuation coefficient could be derived from top of the atmosphere radiances, a number of international missions with ocean color capabilities were launched beginning in the late 1990s. Most notable were those with global data acquisition capabilities, i.e., the Ocean Color and Temperature Sensor (OCTS 1996-1997), the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, United States, 1997-present), two Moderate Resolution Imaging Spectroradiometers, (MODIS, United States, Terra/2000-present and Aqua/2002-present), the Global Imager (GLI, Japan, 2002-2003), and the Medium Resolution Imaging Spectrometer (MERIS, European Space Agency, 2002-present). These missions have provided data of exceptional quality and continuity, allowing for scientific inquiries into a wide variety of marine research topics not possible with the CZCS. This review focuses on the scientific advances made over the past decade using these data sets.

Evaluation of VIIRS ocean color products

NASA Astrophysics Data System (ADS)

Wang, Menghua; Liu, Xiaoming; Jiang, Lide; Son, SeungHyun; Sun, Junqiang; Shi, Wei; Tan, Liqin; Naik, Puneeta; Mikelsons, Karlis; Wang, Xiaolong; Lance, Veronica

2014-11-01

The Suomi National Polar-orbiting Partnership (SNPP) was successfully launched on October 28, 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP, which has 22 spectral bands (from visible to infrared) similar to the NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), is a multi-disciplinary sensor providing observations for the Earth's atmosphere, land, and ocean properties. In this paper, we provide some evaluations and assessments of VIIRS ocean color data products, or ocean color Environmental Data Records (EDR), including normalized water-leaving radiance spectra nLw(λ) at VIIRS five spectral bands, chlorophyll-a (Chl-a) concentration, and water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490). Specifically, VIIRS ocean color products derived from the NOAA Multi-Sensor Level-1 to Level-2 (NOAA-MSL12) ocean color data processing system are evaluated and compared with MODIS ocean color products and in situ measurements. MSL12 is now NOAA's official ocean color data processing system for VIIRS. In addition, VIIRS Sensor Data Records (SDR or Level- 1B data) have been evaluated. In particular, VIIRS SDR and ocean color EDR have been compared with a series of in situ data from the Marine Optical Buoy (MOBY) in the waters off Hawaii. A notable discrepancy of global deep water Chl-a derived from MODIS and VIIRS between 2012 and 2013 is observed. This discrepancy is attributed to the SDR (or Level-1B data) calibration issue and particularly related to VIIRS green band at 551 nm. To resolve this calibration issue, we have worked on our own sensor calibration by combining the lunar calibration effect into the current calibration method. The ocean color products derived from our new calibrated SDR in the South Pacific Gyre show that the Chl-a differences between 2012 and 2013 are significantly reduced. Although there are still some issues, our results show that VIIRS is capable of providing high-quality global ocean color products in support of science research and operational applications. The VIIRS evaluation and monitoring results can be found at the website: http://www.star.nesdis.noaa.gov/sod/mecb/color/index.html.

On-Orbit Cross-Calibration of AM Satellite Remote Sensing Instruments using the Moon

NASA Technical Reports Server (NTRS)

Butler, James J.; Kieffer, Hugh H.; Barnes, Robert A.; Stone, Thomas C.

2003-01-01

On April 14,2003, three Earth remote sensing spacecraft were maneuvered enabling six satellite instruments operating in the visible through shortwave infrared wavelength region to view the Moon for purposes of on-orbit cross-calibration. These instruments included the Moderate Resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer on the Earth Observing System (EOS) Terra spacecraft, the Advanced Land Imager (ALI) and Hyperion instrument on Earth Observing-1 (EO-1) spacecraft, and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on the SeaStar spacecraft. Observations of the Moon were compared using a spectral photometric mode for lunar irradiance developed by the Robotic Lunar Observatory (ROLO) project located at the United States Geological Survey in Flagstaff, Arizona. The ROLO model effectively accounts for variations in lunar irradiance corresponding to lunar phase and libration angles, allowing intercomparison of observations made by instruments on different spacecraft under different time and location conditions. The spacecraft maneuvers necessary to view the Moon are briefly described and results of using the lunar irradiance model in comparing the radiometric calibration scales of the six satellite instruments are presented here.

Monitoring the On-Orbit Calibration of Terra MODIS Reflective Solar Bands Using Simultaneous Terra MISR Observations

NASA Technical Reports Server (NTRS)

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng

2016-01-01

On December 18, 2015, the Terra spacecraft completed 16 years of successful operation in space. Terra has five instruments designed to facilitate scientific measurements of the earths land, ocean, and atmosphere. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging Spectroradiometer (MISR) instruments provide information for the temporal studies of the globe. After providing over 16 years of complementary measurements, a synergistic use of the measurements obtained from these sensors is beneficial for various science products. The 20 reflective solar bands (RSBs) of MODIS are calibrated using a combination of solar diffuser and lunar measurements, supplemented by measurements from pseudoinvariant desert sites. MODIS views the on-board calibrators and the earth via a two-sided scan mirror at three spatial resolutions: 250 m using 40 detectors in bands 1 and 2, 500 m using 20 detectors in bands 3 and 4, and 1000 m using 10 detectors in bands 819 and 26. Simultaneous measurements of the earths surface are acquired in a push-broom fashion by MISR at nine view angles spreading out in the forward and backward directions along the flight path. While the swath width for MISR acquisitions is 360 km, MODIS scans a wider swath of 2330 km via its two-sided scan mirror. The reflectance of the MODIS scan mirror has an angle dependence characterized by the response versus scan angle (RVS). Its on-orbit change is derived using the gain from a combination of on-board and earth-view measurements. The on-orbit RVS for MODIS has experienced a significant change, especially for the short-wavelength bands. The on-orbit RVS change for the short-wavelength bands (bands 3, 8, and 9) at nadir is observed to be greater than 10 over the mission lifetime. Due to absence of a scanning mechanism, MISR can serve as an effective tool to evaluate and monitor the on-orbit performance of the MODIS RVS. Furthermore, it can also monitor the detector and scan-mirror differences for the MODIS bands using simultaneous measurements from earth-scene targets, e.g., North Atlantic Ocean and North African desert. Simultaneous measurements provide the benefit of minimizing the impact of earth-scene features while comparing the radiometric performance using vicarious techniques. Long-term observations of both instruments using select ground targets also provide an evaluation of the long-term calibration stability. The goal of this paper is to demonstrate the use of MISR to monitor and enhance the on-orbit calibration of the MODIS RSB. The radiometric calibration requirements for the MODIS RSB are +/- 2% in reflectance and +/- 5% in radiance at typical radiance levels within +/- 45 deg. of nadir. The results show that the long-term changes in the MODIS reflectance at nadir frames are generally within 1. The MODIS level 1B calibrated products, generated after correcting for the on-orbit changes in the gain and RVS, do not have any correction for changes in the instruments polarization sensitivity. The mirror-side-dependent polarization sensitivity exhibits an on-orbit change, primarily in the blue bands, that manifests in noticeable mirror side differences in the MODIS calibrated products. The mirror side differences for other RSB are observed to be less than 1%, therefore demonstrating an excellent on-orbit performance. The detector differences in the blue bands of MODIS exhibit divergence in recent years beyond 1%, and a calibration algorithm improvement has been identified to mitigate this effect. Short-term variations in the recent year caused by the forward updates were identified in bands 1 and 2 and are planned to be corrected in the next reprocess.

Modelling the Shallow Water Equations in Curvilinear Coordinates with Physical Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wingenter, Suzanne

2005-01-12

The goal of this project is to provide the capability for simulating fluid flow on complicated geometries, such as in the Bahia de Todos Santos. The Bahia de Todos Santos is a bay situated in the northwest corner of Mexico, off the coast of Ensenada and south of San Diego, California, USA. Figure 1.1 shows the Bahia de Todos Santos. It is part of an image taken from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Aqua and Terra satellites in late June and early July 2003 [8]. Roughly 200 square kilometers in size, the bay also contains twomore » islands off the peninsula of Punta Banda. Characteristics of flow in this bay are driven by the moon tide (M2) and wind forcing [9].« less

ESA DUE GlobTemperature project: Infrared-based LST Product

NASA Astrophysics Data System (ADS)

Ermida, Sofia; Pires, Ana; Ghent, Darren; Trigo, Isabel; DaCamara, Carlos; Remedios, John

2016-04-01

One of the purposes of the GlobTemperature project is to provide a product of global Land Surface Temperature (LST) based on Geostationary Earth Orbit (GEO) and Low Earth polar Orbit (LEO) satellite data. The objective is to use existing LST products, which are obtained from different sensors/platforms, combining them into a harmonized product for a reference view angle. In a first approach, only infra-red based retrievals are considered, and LEO LSTs will be used as a common denominator among geostationary sensors. LST data is provided by a wide range of sensors to optimize spatial coverage, namely: (i) 2 LEO sensors - the Advanced Along Track Scanning Radiometer (AATSR) series of instruments on-board ESA's Envisat, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and (ii) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). The merged LST product is generated in two steps: 1) calibration between each LEO and each GEO that consists in the removal of systematic differences (associated to sensor type and LST algorithms, including calibration, atmospheric and surface emissivity corrections, amongst others) represented by linear regressions; 2) angular correction that consists in bringing all LST data to reference (nadir) view. Angular effects on LST are estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as function of viewing and illumination geometry. The model is adjusted to MODIS and SEVIRI/MSG LST estimates and validated against LST retrievals from those sensors obtained for other years (not used in the calibration). It is shown that the model leads to a reduction of LST differences between the two sensors, indicating that it may be used to effectively estimate/correct angular dependence in LST. A global set of kernel model parameters is finally obtained by adjusting the model to either a GEO and a LEO or the two LEOs (poles). A first version of the merged product will be released in 2016, available for download through the GlobTemperature portal. This includes only the calibration process (step 1), incorporating LST data from SEVIRI, GOES, MTSAT and MODIS; information on directional effects added as an extra layer of information. A second version of the dataset with a better incorporation of the angular correction is currently in preparation.

Phytoplankton off the Coast of Portugal

NASA Technical Reports Server (NTRS)

2002-01-01

A large phytoplankton bloom off of the coast of Portugal can be seen in this true-color image taken on April 23, 2002, by the Moderate-resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra satellite. The bloom is roughly half the size of Portugal and forms a bluish-green cloud in the water. The red spots in northwest Spain denote what are likely small agricultural fires. Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

East Siberian Sea, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

The winter sea ice in the east Siberian Sea is looking a bit like a cracked windshield in these true-color Moderate Resolution Imaging Spectroradiometer (MODIS) images from June 16 and 23, 2002. North of the thawing tundra, the sea ice takes on its cracked, bright blue appearance as it thins, which allows the reflection of the water to show through. Numerous still-frozen lakes dot the tundra. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Extending 'Deep Blue' aerosol retrieval coverage to cases of absorbing aerosols above clouds: sensitivity analysis and first case studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sayer, Andrew M.; Hsu, C.; Bettenhausen, Corey

Cases of absorbing aerosols above clouds (AAC), such as smoke or mineral dust, are omitted from most routinely-processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar

Size-dependent validation of MODIS MCD64A1 burned area over six vegetation types in boreal Eurasia: Large underestimation in croplands.

PubMed

Zhu, Chunmao; Kobayashi, Hideki; Kanaya, Yugo; Saito, Masahiko

2017-07-05

Pollutants emitted from wildfires in boreal Eurasia can be transported to the Arctic, and their subsequent deposition could accelerate global warming. The Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned area product is the basis of fire emission products. However, uncertainties due to the "moderate resolution" (500 m) characteristic of the MODIS sensor could be introduced. Here, we present a size-dependent validation of MCD64A1 with reference to higher resolution (better than 30 m) satellite products (Landsat 7 ETM+, RapidEye, WorldView-2, and GeoEye-1) for six ecotypes over 12 regions of boreal Eurasia. We considered the 2012 boreal Eurasia burning season when severe wildfires occurred and when Arctic sea ice extent was historically low. Among the six ecotypes, we found MCD64A1 burned areas comprised only 13% of the reference products in croplands because of inadequate detection of small fires (<100 ha). Our results indicate that over all ecotypes, the actual burned area in boreal Eurasia (15,256 km 2 ) could have been ~16% greater than suggested by MCD64A1 (13,187 km 2 ) when applying the correction factors proposed in this study. This implies the effects of wildfire emissions in boreal Eurasia on Arctic warming could be greater than currently estimated.

Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions

PubMed Central

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2018-01-01

Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious. PMID:29651373

Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions.

PubMed

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2017-05-27

Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious.

Sulfur Upwelling off the African Coast

NASA Technical Reports Server (NTRS)

2002-01-01

Though these aquamarine clouds in the waters off the coast of northern Namibia may look like algae blooms, they are in fact clouds of sulfur produced by anaerobic bacteria on the ocean's floor. This image of the sulfur-filled water was taken on April 24, 2002, by the Sea-viewing Wide Field-of-View Sensor (SeaWiFS), flying aboard the Orbview-2 satellite. The anaerobic bacteria (bacteria that can live without oxygen) feed upon algae carcasses that exist in abundance on the ocean's floor off of Namibia. As the bacteria ingest the algae husks, they produce hydrogen sulfide, which slowly builds up in the sea-floor sediments. Eventually, the hydrogen sulfide reaches the point where the sediment can no longer contain it, and it bubbles forth. When this poisonous chemical reaches the surface, it combines with the oxygen in the upper layers of the ocean to create clouds of pure sulfur. The sulfur causes the Namibian coast to smell like rotten eggs, and the hydrogen sulfide will often kill fish and drive lobsters away. For more information, read: A Bloom By Any Other Name A high-resolution (250 meters per pixel) image earlier on the 24th taken from the Moderate-Resolution Imaging Spectroradiometer (MODIS) shows additional detail in the plumes. Image courtesy the SeaWiFS Project, NASA/Goddard Space Flight Center, and ORBIMAGE. MODIS image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

Assessment of the Short-Term Radiometric Stability between Terra MODIS and Landsat 7 ETM+ Sensors

NASA Technical Reports Server (NTRS)

Choi, Taeyoung; Xiong, Xiaxiong; Chander, G.; Angal, Amit

2009-01-01

The Landsat 7 (L7) Enhanced Thematic Mapper (ETM+) sensor was launched on April 15th, 1999 and has been in operation for over nine years. It has six reflective solar spectral bands located in the visible and shortwave infrared part of the electromagnetic spectrum (0.5 - 2.5 micron) at a spatial resolution of 30 m. The on-board calibrators are used to monitor the on-orbit sensor system changes. The ETM+ performs solar calibrations using on-board Full Aperture Solar Calibrator (FASC) and the Partial Aperture Solar Calibrator (PASC). The Internal Calibrator Lamp (IC) lamps, a blackbody and shutter optics constitute the on-orbit calibration mechanism for ETM+. On 31 May 2003, a malfunction of the scan-line corrector (SLC) mirror assembly resulted in the loss of approximately 22% of the normal scene area. The missing data affects most of the image with scan gaps varying in width from one pixel or less near the centre of the image to 14 pixels along the east and west edges of the image, creating a wedge-shaped pattern. However, the SLC failure has no impacts on the radiometric performance of the valid pixels. On December 18, 1999, the Moderate Resolution Imaging Spectroradiometer (MODIS) Proto-Flight Model (PFM) was launched on-board the NASA's EOS Terra spacecraft. Terra MODIS has 36 spectral bands with wavelengths ranging from 0.41 to 14.5 micron and collects data over a wide field of view angle (+/-55 deg) at three nadir spatial resolutions of 250 m, 500 in 1 km for bands 1 to 2, 3 to 7, and 8 to 36, respectively. It has 20 reflective solar bands (RSB) with spectral wavelengths from 0.41 to 2.1 micron. The RSB radiometric calibration is performed by using on-board solar diffuser (SD), solar diffuser stability monitor (SDSM), space-view (SV), and spectro-radiometric calibration assembly (SRCA). Through the SV port, periodic lunar observations are used to track radiometric response changes at different angles of incidence (AOI) of the scan mirror. As a part of the AM Constellation satellites, Terra MODIS flies approximately 30 minutes behind L7 ETM+ in the same orbit. The orbit of L7 is repetitive, circular, sunsynchronous, and near polar at a nominal altitude of 705 km (438 miles) at the Equator. The spacecraft crosses the Equator from north to south on a descending node between 10:00 AM and 10:15 AM. Circling the Earth at 7.5 km/sec, each orbit takes nearly 99 minutes. The spacecraft completes just over 14 orbits per day, covering the entire Earth between 81 degrees north and south latitude every 16 days. The longest continuous imaging swath that L7 sensor can collect is for a 14-minute subinterval contact period which is equivalent to 35 full WRS-2 scenes. On the other hand, Terra can provide the entire corresponding orbit with wider swath at any given ETM+ collection without contact time limitation. There are six spectral matching band pairs between MODIS (bands 3, 4, 1, 2, 6, 7) and ETM+ (bands 1, 2, 3, 4, 5, 7) sensor. MODIS has narrower spectral responses than ETM+ in all the bands. A short-term radiometric stability was evaluated using continuous ETM+ scenes within the contact period and the corresponding half orbit MODIS scenes. The near simultaneous earth observations (SNO) were limited by the smaller swath size of ETM+ (187 km) as compared to MODIS (2330 km). Two sets of continuous granules for MODIS and ETM+ were selected and mosaiced based on pixel geolocation information for non cloudy pixels over the North American continent. The Top-of- Atmosphere (TOA) reflectances were computed for the spectrally matching bands between ETM+ and MODIS over the regions of interest (ROI). The matching pixel pairs were aggregated from a finer to a coarser pixel resolution and the TOA reflectance values covering a wide dynamic range of the sensors were compared and analyzed. Considering the uncertainties of the absolute calibration of the both sensors, radiometric stability was verified for the band pairs. The Railroad Valley Playa, Nada (RVPN) was included in the path of this continuous orbit, which served as a verification point between the shortterm and the long-term trending results from previous studies. This work focuses on monitoring the short-term on-orbit stability of MODIS and the ETM+ RSB. It also provides an assessment of the absolute calibration differences between the two sensors over their wide dynamic ranges.

Sources, Sinks, and Transatlantic Transport of North African Dust Aerosol: A Multimodel Analysis and Comparison With Remote Sensing Data

NASA Technical Reports Server (NTRS)

Kim, Dongchul; Chin, Mian; Yu, Hongbin; Diehl, Thomas; Tan, Qian; Kahn, Ralph A.; Tsigaridis, Kostas; Bauer, Susanne E.; Takemura, Toshihiko; Pozzoli, Luca;

Production and Distribution of Global Products From MODIS

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Smith, David E. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer was launched on the EOS Terra spacecraft in December 1999 and will also fly on EOS Aqua in December 2000. With 36 spectral bands from the visible through thermal infrared and spatial resolution of 250m to 1 kilometer, each MODIS instrument will image the entire Earth surface in 2 days. This paper traces the flow of MODIS data products from the receipt of Level 0 data at the EDOS facility, through the production and quality assurance process to the Distributed Active Archive Centers (DAACs), which ship products to the user community. It describes where to obtain products and plans for reprocessing MODIS products. As most components of the ground system are severely limited in their capacity to distribute MODIS products, it also describes the key characteristics of MODIS products and their metadata that allow a user to optimize their selection of products given anticipate bottlenecks in distribution.

Global Tropospheric Noise Maps for InSAR Observations

NASA Astrophysics Data System (ADS)

Yun, S. H.; Hensley, S.; Agram, P. S.; Chaubell, M.; Fielding, E. J.; Pan, L.

2014-12-01

Radio wave's differential phase delay variation through the troposphere is 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 (PWV) products from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors mounted on Terra and Aqua satellites to produce tropospheric noise maps of InSAR. We estimate the slope and y-intercept of power spectral density curve of MODIS PWV 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 for the science Level-1 requirements of the planned NASA-ISRO L-band SAR mission (NISAR mission). We populate lookup tables of such power spectrum parameters derived from each 1-by-1 degree tile of global coverage. The MODIS data were retrieved from OSCAR (Online Services for Correcting Atmosphere in Radar) server. Users will be able to use the lookup tables and calculate expected tropospheric noise level of any date of MODIS data at any distance scale. Such calculation results can be used for constructing covariance matrix for geophysical modeling, or building statistics to support InSAR missions' requirements. For example, about 74% of the world had InSAR tropospheric noise level (along a radar line-of-sight for an incidence angle of 40 degrees) of 2 cm or less at 50 km distance scale during the time period of 2010/01/01 - 2010/01/09.

Tropical Atlantic Dust and Smoke Aerosol Variations Related to the Madden-Julian Oscillation in MODIS and MISR Observations

NASA Technical Reports Server (NTRS)

Guo, Yanjuan; Tian, Baijun; Kahn, Ralph A.; Kalashnikova, Olga; Wong, Sun; Waliser, Duane E.

2013-01-01

In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) fine mode fraction and Multi-angle Imaging SpectroRadiometer (MISR) nonspherical fraction data are used to derive dust and smoke aerosol optical thickness (T(sub dust) and T(sub smoke)) over the tropical Atlantic in a complementary way: due to its wider swath, MODIS has 3-4 times greater sampling than MISR, but MISR dust discrimination is based on particle shape retrievals, whereas an empirical scheme is used for MODIS. MODIS and MISR show very similar dust and smoke winter climatologies. T(sub dust) is the dominant aerosol component over the tropical Atlantic, accounting for 40-70 percent of the total aerosol optical thickness (AOT), whereas T(sub smoke) is significantly smaller than T(sub dust). The consistency and high correlation between these climatologies and their daily variations lends confidence to their use for investigating the relative dust and smoke contributions to the total AOT variation associated with the Madden-Julian Oscillation (MJO). The temporal evolution and spatial patterns of the tdus anomalies associated with the MJO are consistent between MODIS and MISR: the magnitude of MJO-realted T(sub dust) anomalies is comparable to or even larger than that of the total T, while the T(sub smoke) anomaly represents about 15 percent compared to the total, which is quite different from their relative magnitudes to the total T on the climatological time scale. This suggests that dust and smoke are not influenced by the MJO in the same way. Based on correlation analysis, dust is strongly influenced by the MJO-modulated trade wind and precipitation anomalies, and can last as long as one MJO phase, whereas smoke is less affected.

Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles

NASA Technical Reports Server (NTRS)

Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Kittaka, C.; Vaughn, M. A.; Remer, L. A.

2010-01-01

We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lidar ratio. The backscatter data were acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The HSRL also simultaneously measures aerosol extinction coefficients independently using the high spectral resolution lidar technique, thereby providing an ideal data set for evaluating the retrieval. We retrieve aerosol extinction profiles from both HSRL and CALIOP attenuated backscatter data constrained with HSRL, Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer column AOT. The resulting profiles are compared with the aerosol extinction measured by HSRL. Retrievals are limited to cases where the column aerosol thickness is greater than 0.2 over land and 0.15 over water. In the case of large AOT, the results using the Aqua MODIS constraint over water are poorer than Aqua MODIS over land or Terra MODIS. The poorer results relate to an apparent bias in Aqua MODIS AOT over water observed in August 2007. This apparent bias is still under investigation. Finally, aerosol extinction coefficients are derived from CALIPSO backscatter data using AOT from Aqua MODIS for 28 profiles over land and 9 over water. They agree with coincident measurements by the airborne HSRL to within +/-0.016/km +/- 20% for at least two-thirds of land points and within +/-0.028/km +/- 20% for at least two-thirds of ocean points.

Use of Moderate-Resolution Imaging Spectroradiometer bidirectional reflectance distribution function products to enhance simulated surface albedos

NASA Astrophysics Data System (ADS)

Roesch, Andreas; Schaaf, Crystal; Gao, Feng

2004-06-01

Moderate-Resolution Imaging Spectroradiometer (MODIS) surface albedo at high spatial and spectral resolution is compared with other remotely sensed climatologies, ground-based data, and albedos simulated with the European Center/Hamburg 4 (ECHAM4) global climate model at T42 resolution. The study demonstrates the importance of MODIS data in assessing and improving albedo parameterizations in weather forecast and climate models. The remotely sensed PINKER surface albedo climatology follows the MODIS estimates fairly well in both the visible and near-infrared spectra, whereas ECHAM4 simulates high positive albedo biases over snow-covered boreal forests and the Himalayas. In contrast, the ECHAM4 albedo is probably too low over the Sahara sand desert and adjacent steppes. The study clearly indicates that neglecting albedo variations within T42 grid boxes leads to significant errors in the simulated regional climate and horizontal fluxes, mainly in mountainous and/or snow-covered regions. MODIS surface albedo at 0.05 resolution agrees quite well with in situ field measurements collected at Baseline Surface Radiation Network (BSRN) sites during snow-free periods, while significant positive biases are found under snow-covered conditions, mainly due to differences in the vegetation cover at the BSRN site (short grass) and the vegetation within the larger MODIS grid box. Black sky (direct beam) albedo from the MODIS bidirectional reflectance distribution function model captures the diurnal albedo cycle at BSRN sites with sufficient accuracy. The greatest negative biases are generally found when the Sun is low. A realistic approach for relating albedo and zenith angle has been proposed. Detailed evaluations have demonstrated that ignoring the zenith angle dependence may lead to significant errors in the surface energy balance.

Results and Validation of MODIS Aerosol Retrievals Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2001-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Results and Validation of MODIS Aerosol Retrievals over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Ichoku, C.; Chu, D. A.; Mattoo, S.; Levy, R.; Martins, J. V.; Li, R.-R.; Einaudi, Franco (Technical Monitor)

2000-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Vegetation chlorophyll estimates in the Amazon from multi-angle MODIS observations and canopy reflectance model

NASA Astrophysics Data System (ADS)

Hilker, Thomas; Galvão, Lênio Soares; Aragão, Luiz E. O. C.; de Moura, Yhasmin M.; do Amaral, Cibele H.; Lyapustin, Alexei I.; Wu, Jin; Albert, Loren P.; Ferreira, Marciel José; Anderson, Liana O.; dos Santos, Victor A. H. F.; Prohaska, Neill; Tribuzy, Edgard; Barbosa Ceron, João Vitor; Saleska, Scott R.; Wang, Yujie; de Carvalho Gonçalves, José Francisco; de Oliveira Junior, Raimundo Cosme; Cardoso Rodrigues, João Victor Figueiredo; Garcia, Maquelle Neves

2017-06-01

As a preparatory study for future hyperspectral missions that can measure canopy chemistry, we introduce a novel approach to investigate whether multi-angle Moderate Resolution Imaging Spectroradiometer (MODIS) data can be used to generate a preliminary database with long-term estimates of chlorophyll. MODIS monthly chlorophyll estimates between 2000 and 2015, derived from a fully coupled canopy reflectance model (ProSAIL), were inspected for consistency with eddy covariance fluxes, tower-based hyperspectral images and chlorophyll measurements. MODIS chlorophyll estimates from the inverse model showed strong seasonal variations across two flux-tower sites in central and eastern Amazon. Marked increases in chlorophyll concentrations were observed during the early dry season. Remotely sensed chlorophyll concentrations were correlated to field measurements (r2 = 0.73 and r2 = 0.98) but the data deviated from the 1:1 line with root mean square errors (RMSE) ranging from 0.355 μg cm-2 (Tapajós tower) to 0.470 μg cm-2 (Manaus tower). The chlorophyll estimates were consistent with flux tower measurements of photosynthetically active radiation (PAR) and net ecosystem productivity (NEP). We also applied ProSAIL to mono-angle hyperspectral observations from a camera installed on a tower to scale modeled chlorophyll pigments to MODIS observations (r2 = 0.73). Chlorophyll pigment concentrations (ChlA+B) were correlated to changes in the amount of young and mature leaf area per month (0.59 ≤ r2 ≤ 0.64). Increases in MODIS observed ChlA+B were preceded by increased PAR during the dry season (0.61 ≤ r2 ≤ 0.62) and followed by changes in net carbon uptake. We conclude that, at these two sites, changes in LAI, coupled with changes in leaf chlorophyll, are comparable with seasonality of plant productivity. Our results allowed the preliminary development of a 15-year time series of chlorophyll estimates over the Amazon to support canopy chemistry studies using future hyperspectral sensors.

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

Remote sensing evaluation of CLM4 GPP for the period 2000 to 2009

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Jiafu; Thornton, Peter E; Shi, Xiaoying

2012-01-01

The ability of a process-based ecosystem model like Version 4 of the Community Land Model (CLM4) to provide accurate estimates of CO2 flux is a top priority for researchers, modelers and policy makers. Remote sensing can provide long-term and large scale products suitable for ecosystem model evaluation. Global estimations of gross primary production (GPP) at the 1 km spatial resolution from years 2000 to 2009 from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor offer a unique opportunity for evaluating the temporal and spatial patterns of global GPP and its relationship with climate for CLM4. We compare monthly GPP simulated bymore » CLM4 at half-degree resolution with satellite estimates of GPP from the MODIS GPP (MOD17) dataset for the 10-yr period, January 2000 December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intra-annual and inter-annual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and later decline of GPP in autumn. Empirical Orthogonal Function (EOF) analysis of the monthly GPP changes indicates that on the intra-annual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and the very dry region in central Australia. For 2000-2009, CLM4 simulates increases in annual averaged GPP over both hemispheres, however estimates from MODIS suggest a reduction in the Southern Hemisphere (-0.2173 PgC/year) balancing the significant increase over the Northern Hemisphere (0.2157 PgC/year).« less

Lena River Delta and East Siberian Sea

NASA Technical Reports Server (NTRS)

2002-01-01

The winter sea ice in the east Siberian Sea is looking a bit like a cracked windshield in these true-color Moderate Resolution Imaging Spectroradiometer (MODIS) images from June 16 and 23, 2002. North of the thawing tundra, the sea ice takes on its cracked, bright blue appearance as it thins, which allows the reflection of the water to show through. Numerous still-frozen lakes dot the tundra. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Moderate Imaging Resolution Spectroradiometer (MODIS) Aerosol Optical Depth Retrieval for Aerosol Radiative Forcing

NASA Astrophysics Data System (ADS)

Asmat, A.; Jalal, K. A.; Ahmad, N.

2018-02-01

The present study uses the Aerosol Optical Depth (AOD) retrieved from Moderate Imaging Resolution Spectroradiometer (MODIS) data for the period from January 2011 until December 2015 over an urban area in Kuching, Sarawak. The results show the minimum AOD value retrieved from MODIS is -0.06 and the maximum value is 6.0. High aerosol loading with high AOD value observed during dry seasons and low AOD monitored during wet seasons. Multi plane regression technique used to retrieve AOD from MODIS (AODMODIS) and different statistics parameter is proposed by using relative absolute error for accuracy assessment in spatial and temporal averaging approach. The AODMODIS then compared with AOD derived from Aerosol Robotic Network (AERONET) Sunphotometer (AODAERONET) and the results shows high correlation coefficient (R2) for AODMODIS and AODAERONET with 0.93. AODMODIS used as an input parameters into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model to estimate urban radiative forcing at Kuching. The observed hourly averaged for urban radiative forcing is -0.12 Wm-2 for top of atmosphere (TOA), -2.13 Wm-2 at the surface and 2.00 Wm-2 in the atmosphere. There is a moderate relationship observed between urban radiative forcing calculated using SBDART and AERONET which are 0.75 at the surface, 0.65 at TOA and 0.56 in atmosphere. Overall, variation in AOD tends to cause large bias in the estimated urban radiative forcing.

Inter-Annual Variability of Burned Area in Brazil Based on a Synergistic use of Information Derived from MODIS and Landsat-TM

NASA Astrophysics Data System (ADS)

Libonati, R.; Dacamara, C. C.; Setzer, A. W.; Morelli, F.

2014-12-01

A procedure is presented that allows using information from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor to improve the quality of monthly burned area estimates over Brazil. The method integrates MODIS derived information from two sources; the NASA MCD64A1 Direct Broadcast Monthly Burned Area Product and INPE's Monthly Burned Area MODIS product (AQM-MODIS). The latter product relies on an algorithm that was specifically designed for ecosystems in Brazil, taking advantage of the ability of MIR reflectances to discriminate burned areas. Information from both MODIS products is incorporated by means of a linear regression model where an optimal estimate of the burned area is obtained as a linear combination of burned area estimates from MCD64A1 and AQM-MODIS. The linear regression model is calibrated using as optimal estimates values of burned area derived from Landsat TM during 2005 and 2006 over Jalapão, a region of Cerrado covering an area of 187 x 187 km2. Obtained values of coefficients for MCD64A1 and AQM-MODIS were 0.51 and 0.35, respectively and the root mean square error was 7.6 km2. Robustness of the model was checked by calibrating the model separately for 2005 and 2006 and cross-validating with 2006 and 2005; coefficients for 2005 (2006) were 0.46 (0.54) for MCD64A1 and 0.35 (0.35) for AQM-MODIS and the corresponding root mean square errors for 2006 (2005) were 7.8 (7.4) km2. The linear model was then applied to Brazil as well as to the six Brazilian main biomes, namely Cerrado, Amazônia, Caatinga, Pantanal, Mata Atlântica and Pampa. As to be expected the interannual variability based on the proposed synergistic use of MCD64A1, AQM-MODIS and Landsat Tm data for the period 2005-2010 presents marked differences with the corresponding amounts derived from MCD64A1 alone. For instance during the considered period, values (in 103 km2) from the proposed approach (from MCD64A1) are 399 (142), 232 (62), 559 (259), 274 (73), 219 (31) and 415 (251). Values obtained with the proposed approach may be viewed as an improved alternative to the currently available products over Brazil.

Flood Mapping in the Lower Mekong River Basin Using Daily MODIS Observations

NASA Technical Reports Server (NTRS)

Fayne, Jessica V.; Bolten, John D.; Doyle, Colin S.; Fuhrmann, Sven; Rice, Matthew T.; Houser, Paul R.; Lakshmi, Venkat

2017-01-01

In flat homogenous terrain such as in Cambodia and Vietnam, the monsoon season brings significant and consistent flooding between May and November. To monitor flooding in the Lower Mekong region, the near real-time NASA Flood Extent Product (NASA-FEP) was developed using seasonal normalized difference vegetation index (NDVI) differences from the 250 m resolution Moderate Resolution Imaging Spectroradiometer (MODIS) sensor compared to daily observations. The use of a percentage change interval classification relating to various stages of flooding reduces might be confusing to viewers or potential users, and therefore reducing the product usage. To increase the product usability through simplification, the classification intervals were compared with other commonly used change detection schemes to identify the change classification scheme that best delineates flooded areas. The percentage change method used in the NASA-FEP proved to be helpful in delineating flood boundaries compared to other change detection methods. The results of the accuracy assessments indicate that the -75% NDVI change interval can be reclassified to a descriptive 'flood' classification. A binary system was used to simplify the interpretation of the NASA-FEP by removing extraneous information from lower interval change classes.

On the Use of Deep Convective Clouds to Calibrate AVHRR Data

NASA Technical Reports Server (NTRS)

Doelling, David R.; Nguyen, Louis; Minnis, Patrick

2004-01-01

Remote sensing of cloud and radiation properties from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellites requires constant monitoring of the visible sensors. NOAA satellites do not have onboard visible calibration and need to be calibrated vicariously in order to determine the calibration and the degradation rate. Deep convective clouds are extremely bright and cold, are at the tropopause, have nearly a Lambertian reflectance, and provide predictable albedos. The use of deep convective clouds as calibration targets is developed into a calibration technique and applied to NOAA-16 and NOAA-17. The technique computes the relative gain drift over the life-span of the satellite. This technique is validated by comparing the gain drifts derived from inter-calibration of coincident AVHRR and Moderate-Resolution Imaging Spectroradiometer (MODIS) radiances. A ray-matched technique, which uses collocated, coincident, and co-angled pixel satellite radiance pairs is used to intercalibrate MODIS and AVHRR. The deep convective cloud calibration technique was found to be independent of solar zenith angle, by using well calibrated Visible Infrared Scanner (VIRS) radiances onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, which precesses through all solar zenith angles in 23 days.

Comparison of Sub-pixel Classification Approaches for Crop-specific Mapping

EPA Science Inventory

The Moderate Resolution Imaging Spectroradiometer (MODIS) data has been increasingly used for crop mapping and other agricultural applications. Phenology-based classification approaches using the NDVI (Normalized Difference Vegetation Index) 16-day composite (250 m) data product...

Band-to-Band Misregistration of the Images of MODIS Onboard Calibrators and Its Impact on Calibration

NASA Technical Reports Server (NTRS)

Wang, Zhipeng; Xiong, Xiaoxiong

2017-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard Terra and Aqua satellites are radiometrically calibrated on-orbit with a set of onboard calibrators (OBCs), including a solar diffuser, a blackbody, and a space view port through which the detectors can view the dark space. As a whisk-broom scanning spectroradiometer, thirty-six MODIS spectral bands are assembled in the along-scan direction on four focal plane assemblies (FPAs). These bands capture images of the same target sequentially with the motion of a scan mirror. Then the images are coregistered onboard by delaying the appropriate band-dependent amount of time, depending on the band locations on the FPA. While this coregistration mechanismis functioning well for the far-field remote targets such as earth view scenes or the moon, noticeable band-to-band misregistration in the along-scan direction has been observed for near field targets, particularly in OBCs. In this paper, the misregistration phenomenon is presented and analyzed. It is concluded that the root cause of the misregistration is that the rotating element of the instrument, the scan mirror, is displaced from the focus of the telescope primary mirror. The amount of the misregistrationis proportional to the band location on the FPA and is inversely proportional to the distance between the target and the scan mirror. The impact of this misregistration on the calibration of MODIS bands is discussed. In particular, the calculation of the detector gain coefficient m1of bands 8-16 (412 nm 870 nm) is improved by up to 1.5% for Aqua MODIS.

Remote Sensing of Aerosol Over the Land from the Earth Observing System MODIS Instrument

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2000-01-01

On Dec 18, 1999, NASA launched the Moderate-Resolution Imaging Spectroradiometer (MODIS) 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 MODIS instrument on EOS Aqua for afternoon observations (1:30 PM). MODIS 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 MODIS 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 MODIS 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 MODIS measurements. During the Aqua 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. Aqua-MODIS, PICASSO and PARASOL will fly in formation for detailed simultaneous characterization of the aerosol three-dimensional field, which will feed and evaluate global aerosol transport and climate models. In this talk, some examples of the MODIS measurements will be shown.

Evaluation of Aerosol Properties over Ocean from Moderate Resolution Imaging Spectroradiometer (MODIS) during ACE-Asia

NASA Technical Reports Server (NTRS)

Chu, D. A.; Remer, L. A.; Kaufman, Y. J.; Schmid, B.; Redemann, J.; Knobelspiesse, K.; Chern, J.-D.; Livingston, J.; Russell, P. B.; Xiong, X.;

Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

2010-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance 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 MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, 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 MODIS on the Terra spacecraft. Finally, this MODIS-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.

Flooding of the Ob River, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

A mixture of heavy rainfall, snowmelt, and ice jams in late May and early June of this year caused the Ob River and surrounding tributaries in Western Siberia to overflow their banks. The flooding can be seen in thess image taken on June 16, 2002, by the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra satellite. Last year, the river flooded farther north. Normally, the river resembles a thin black line, but floods have swollen the river considerably. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

NASA Technical Reports Server (NTRS)

Tucker, Compton; Puma, Michael

2015-01-01

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Kingfield, D.; de Beurs, K.

2014-12-01

It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

Development of Fire Emissions Inventory Using Satellite Data

EPA Science Inventory

There are multiple satellites observing and reporting fire imagery at various spatial and temporal resolutions and each system has inherent merits and deficiencies. In our study, data are acquired from the Moderate Resolution Imaging Spectro-radiometer (MODIS) aboard the Nationa...

A COMPARISON OF CMAQ-BASED AEROSOL PROPERTIES WITH IMPROVE, MODIS, AND AERONET DATA

EPA Science Inventory

We compare select aerosol Properties derived from the Community Multiscale Air Quality (CMAQ) model-simulated aerosol mass concentrations with routine data from the National Aeronautics and Space Administration (NASA) satellite-borne Moderate Resolution Imaging Spectro-radiometer...

Improving the MODIS Global Snow-Mapping Algorithm

NASA Technical Reports Server (NTRS)

Klein, Andrew G.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

An algorithm (Snowmap) is under development to produce global snow maps at 500 meter resolution on a daily basis using data from the NASA MODIS instrument. MODIS, 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 MODIS Airborne Simulator (MAS) data are used to investigate the changes in reflectance 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.

Global Enhanced Vegetation Index

NASA Technical Reports Server (NTRS)

2002-01-01

By carefully measuring the wavelengths and intensity of visible and near-infrared light reflected by the land surface back up into space, the Moderate-resolution Imaging Spectroradiometer (MODIS) Team can quantify the concentrations of green leaf vegetation around the world. The above MODIS Enhanced Vegetation Index (EVI) map shows the density of plant growth over the entire globe. Very low values of EVI (white and brown areas) correspond to barren areas of rock, sand, or snow. Moderate values (light greens) represent shrub and grassland, while high values indicate temperate and tropical rainforests (dark greens). The MODIS EVI gives scientists a new tool for monitoring major fluctuations in vegetation and understanding how they affect, and are affected by, regional climate trends. For more information, read NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Land Group/Vegetation Indices, Alfredo Huete, Principal Investigator, and Kamel Didan, University of Arizona

MODIS land data at the EROS data center DAAC

USGS Publications Warehouse

Jenkerson, Calli B.; Reed, B.C.

2001-01-01

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 (MODIS) Land Data collected from the Earth Observing System (EOS) satellite Terra. More than 500,000 publicly available MODIS 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 MODIS Land data, which include land surface reflectance/albedo, temperature/emissivity, vegetation characteristics, and land cover, by responding to user inquiries, constructing user information sites on the EDC web page, and presenting MODIS materials worldwide.

Verification and Validation of NASA-Supported Enhancements to Decision Support Tools of PECAD

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; McKellip, Rodney; Moore, Roxzana F.; Fendley, Debbie

2005-01-01

This section of the evaluation report summarizes the verification and validation (V&V) of recently implemented, NASA-supported enhancements to the decision support tools of the Production Estimates and Crop Assessment Division (PECAD). The implemented enhancements include operationally tailored Moderate Resolution Imaging Spectroradiometer (MODIS) products and products of the Global Reservoir and Lake Monitor (GRLM). The MODIS products are currently made available through two separate decision support tools: the MODIS Image Gallery and the U.S. Department of Agriculture (USDA) Foreign Agricultural Service (FAS) MODIS Normalized Difference Vegetation Index (NDVI) Database. Both the Global Reservoir and Lake Monitor and MODIS Image Gallery provide near-real-time products through PECAD's CropExplorer. This discussion addresses two areas: 1. Assessments of the standard NASA products on which these enhancements are based. 2. Characterizations of the performance of the new operational products.

Application-ready expedited MODIS data for operational land surface monitoring of vegetation condition

USGS Publications Warehouse

Brown, Jesslyn; Howard, Daniel M.; Wylie, Bruce K.; Friesz, Aaron M.; Ji, Lei; Gacke, Carolyn

2015-01-01

Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) system. Because of near-daily global coverage, MODIS 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 MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1), the eMODIS Normalized Difference Vegetation Index (NDVI) maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra) or afternoon (Aqua) orbits. The Aqua eMODIS 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 eMODIS data.

Spatial Statistical Data Fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Nguyen, Hai

2010-01-01

Data fusion is the process of combining information from heterogeneous sources into a single composite picture of the relevant process, such that the composite picture is generally more accurate and complete than that derived from any single source alone. Data collection is often incomplete, sparse, and yields incompatible information. Fusion techniques can make optimal use of such data. When investment in data collection is high, fusion gives the best return. Our study uses data from two satellites: (1) Multiangle Imaging SpectroRadiometer (MISR), (2) Moderate Resolution Imaging Spectroradiometer (MODIS).

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.

2011-01-01

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 (MODIS) sensor aboard the polar orbiting NASA Aqua 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 MODIS 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 MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Quality Assessment of Collection 6 MODIS Atmospheric Science Products

NASA Astrophysics Data System (ADS)

Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.

2015-12-01

Since the launch of the NASA Terra and Aqua satellites in December 1999 and May 2002, respectively, atmosphere and land data acquired by the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on-board these satellites have been reprocessed five times at the MODAPS (MODIS Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA MODIS science team investigators. MODAPS completed Collection 6 reprocessing of MODIS 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 MODIS Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of MODIS 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 recently processed C6 products. We will also describe the various tools and approaches developed to verify and assess the algorithm changes implemented by the science team to address known issues in the products and improve the quality of the products.

Detecting Soil Moisture Related Impacts on Gross Primary Productivity using the MODIS-based Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Running, S. W.; Ballantyne, A.; Guan, K.; Huemmrich, K. F.

2016-12-01

Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to photosynthetic light use efficiency (LUE), GPP and canopy water-stress. The NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) sensor provides potential PRI estimation globally at daily time step and 1-km spatial resolution for more than 10 years. Here, we use the MODIS based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing 5 major plant functional types (PFT) within the continental USA (CONUS) to assess GPP sensitivity to seasonal water supply variability. The sPRI (scaled PRI) derived using MODIS band 13 as a reference band (sPRI13) generally shows higher correspondence with tower GPP observations than other potential MODIS reference bands (MODIS band 1, 4, 10 and 12). The sPRI13 was used to represent soil moisture related water supply constraints to LUE within a terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally strong relationships with tower GPP observations (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a proxy for soil moisture related water supply limits indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in northwest and southwest CONUS subregions, and drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and soil water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent GPP sensitivity to seasonal soil moisture related water supply variability, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations, providing an effective tool to characterize sub-grid spatial heterogeneity in soil moisture related water supply controls that inform coarser scale observations and estimates determined from other satellite observations and global carbon, and climate models.

MODIS Observations of Smoke and Fires

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Ichoku, Charles; Remer, Lorraine; Lau, William K. M. (Technical Monitor)

2002-01-01

The MODIS (Moderate Resolution Imaging Spectroradiometer) instruments collect daily measurements of our planet since early 2000 from the Terra spaceborne polar platform. It has unique channels to observe smoke over land and ocean and to observe fires. Using unsaturated channels at 3.9 micron MODIS detects the fires and estimates the fire radiative energy. Using solar channels in the visible (0.47 and 0.66 micron) and in the mid IR (2.1 micron) MODIS measures the smoke optical thickness distribution and evolution over the land. Seven Channels in the solar spectrum are used to detect the smoke properties and distribution over the oceans. Data from the Aerosol Robotic Network, are used to validate the MODIS observations. The MODIS aerosol data presented in a movie form is used to observe the generation of smoke plumes and their dispersion around the globe. For example a key conclusion is that smoke in particular from Southern Africa can pollute significantly the 'pristine' Southern Hemisphere zonal range of 45'S-60'S, and the Northern Pacific.

Evaluating Crop Area Mapping from MODIS Time-Series as an Assessment Tool for Zimbabwe’s “Fast Track Land Reform Programme”

PubMed Central

2016-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) data forms the basis for numerous land use and land cover (LULC) mapping and analysis frameworks at regional scale. Compared to other satellite sensors, the spatial, temporal and spectral specifications of MODIS are considered as highly suitable for LULC classifications which support many different aspects of social, environmental and developmental research. The LULC mapping of this study was carried out in the context of the development of an evaluation approach for Zimbabwe’s land reform program. Within the discourse about the success of this program, a lack of spatially explicit methods to produce objective data, such as on the extent of agricultural area, is apparent. We therefore assessed the suitability of moderate spatial and high temporal resolution imagery and phenological parameters to retrieve regional figures about the extent of cropland area in former freehold tenure in a series of 13 years from 2001–2013. Time-series data was processed with TIMESAT and was stratified according to agro-ecological potential zoning of Zimbabwe. Random Forest (RF) classifications were used to produce annual binary crop/non crop maps which were evaluated with high spatial resolution data from other satellite sensors. We assessed the cropland products in former freehold tenure in terms of classification accuracy, inter-annual comparability and heterogeneity. Although general LULC patterns were depicted in classification results and an overall accuracy of over 80% was achieved, user accuracies for rainfed agriculture were limited to below 65%. We conclude that phenological analysis has to be treated with caution when rainfed agriculture and grassland in semi-humid tropical regions have to be separated based on MODIS spectral data and phenological parameters. Because classification results significantly underestimate redistributed commercial farmland in Zimbabwe, we argue that the method cannot be used to produce spatial information on land-use which could be linked to tenure change. Hence capabilities of moderate resolution data are limited to assess Zimbabwe’s land reform. To make use of the unquestionable potential of MODIS time-series analysis, we propose an analysis of plant productivity which allows to link annual growth and production of vegetation to ownership after Zimbabwe’s land reform. PMID:27253327

Thermal Imagery Details Larsen C Iceberg Calving

NASA Astrophysics Data System (ADS)

Shuman, C. A.; Scambos, T. A.; Schmaltz, J. E.; Melocik, K. A.; Klinger, M. J.

2017-12-01

The final calving of the 5800 km2 iceberg, initially named A-68, from the Larsen C ice shelf took place in darkness during Antarctica's austral winter. Landsat 8 special acquisitions by the Thermal Infrared Sensor (TIRS) on June 19th and July 21st showed the near-final extent of the rift as well as the iceberg after it had released. Such thermal imagery was a critical tool for seeing changes during this period of winter darkness. The completion of the rift across the Larsen C was first announced by Project MIDAS on 12 July based on thermal imagery from Aqua's Moderate Resolution Imaging Spectroradiometer (MODIS). The thermal contrast between the ocean and ice surfaces made it clear that the iceberg had released before Sentinel-1's radar and Landsat 8's thermal data confirmed that later on the same day. In addition to TIRS on Landsat 8 (Band 10) and the MODIS sensors on the Terra and Aqua satellites (Bands 31/32), the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite also acquires thermal imagery at a similar wavelength ( 11.5 microns) with its I5 Band. The advantage to these data relative to MODIS is that they are at a higher resolution, 375 m vs 1 km. This, along with multiple passes per day has enabled a detailed temporal study of the early drift movement of A68, followed by visible-band tracking and structural analysis using MODIS band 1 (Aqua and Terra; 250 m resolution) and Landsat 8 panchromatic band (15 m). Along with constraining the timing of the rift's breakthrough to a small time window on July 11th, these data allow tracking of the major pieces of A-68 as they formed, and of the intact area behind the deep embayment in the Larsen C's ice front. Further, we will track the movement of these large ice masses, and monitor summer melt and effects of further calving and thinning as they move northward in the circulation of the Weddell Gyre.

Glacier albedo change and its relationship to surface temperature change from MODIS data: Queen Elizabeth Islands, Arctic Canada, 2001-2015

NASA Astrophysics Data System (ADS)

Mortimer, C.; Sharp, M. J.

2016-12-01

Glacier and ice cap surface albedo change over the Canadian High Arctic is assessed using measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors for the period 2001-2015. Mean summer black-sky broadband surface albedo (MCD43A3 v05) over all glaciated surfaces in the Queen Elizabeth Islands south of 80°N decreased at a rate of 0.0038 ± 0.0037 yr-1 over that period. The bulk of this albedo decrease occurred from 2008 to 2012 when mean summer albedo was anomalously low. Albedo declines were greatest in the west of the QEI and at lower elevations on the ice caps. The period 2005-2012 included some of the warmest summers in the region since at least the 1950s. Between 2001 and 2015, mean summer glacier surface temperatures for the QEI (south of 80°N), derived from MODIS data (MOD11A2 v05), increased at a rate of 0.034 ± 0.037 °C yr-1. Net shortwave energy is modulated by changes in the surface albedo and is the largest source of summer melt energy in the QEI. During 2001-2015, the summer albedo record was negatively correlated with the mean summer glacier surface temperature record across 91% of the region; clusters of positive correlations between surface temperature and albedo were observed at high elevations in eastern Ellesmere Island.

Estimating surface visibility at Hong Kong from ground-based LIDAR, sun photometer and operational MODIS products.

PubMed

Shahzad, Muhammad I; Nichol, Janet E; Wang, Jun; Campbell, James R; Chan, Pak W

2013-09-01

Hong Kong's surface visibility has decreased in recent years due to air pollution from rapid social and economic development in the region. In addition to deteriorating health standards, reduced visibility disrupts routine civil and public operations, most notably transportation and aviation. Regional estimates of visibility solved operationally using available ground and satellite-based estimates of aerosol optical properties and vertical distribution may prove more effective than standard reliance on a few existing surface visibility monitoring stations. Previous studies have demonstrated that such satellite measurements correlate well with near-surface optical properties, despite these sensors do not consider range-resolved information and indirect parameterizations necessary to solve relevant parameters. By expanding such analysis to include vertically resolved aerosol profile information from an autonomous ground-based lidar instrument, this work develops six models for automated assessment of surface visibility. Regional visibility is estimated using co-incident ground-based lidar, sun photometer visibility meter and MODerate-resolution maging Spectroradiometer (MODIS) aerosol optical depth data sets. Using a 355 nm extinction coefficient profile solved from the lidar MODIS AOD (aerosol optical depth) is scaled down to the surface to generate a regional composite depiction of surface visibility. These results demonstrate the potential for applying passive satellite depictions of broad-scale aerosol optical properties together with a ground-based surface lidar and zenith-viewing sun photometer for improving quantitative assessments of visibility in a city such as Hong Kong.

Retrievals of Surface Air Temperature Using Multiple Satellite Data Combinations over Complex Terrain in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Jang, K.; Won, M.; Yoon, S.; Lim, J.

2016-12-01

Surface air temperature (Tair) is a fundamental factor for terrestrial environments and plays a major role in the fields of applied meteorology, climatology, and ecology. The satellite remotely sensed data offers the opportunity to estimate Tair on the earth's surface with high spatial and temporal resolutions. The Moderate Resolution Imaging Spectroradiometer (MODIS) provides effective Tair retrievals although restricted to clear sky condition. MODIS Tair over complex terrain can result in significant retrieval errors due to the retrieval height mismatch to the elevation of local weather stations. In this study, we propose the methodology to estimate Tair over complex terrain for all sky conditions using multiple satellite data fusion based on the pixel-wise regression method. The combination of synergistic information from MODIS Tair and the brightness temperature (Tb) retrievals at 37 GHz frequency from the satellite microwave sensor were used for analysis. The air temperature lapse rate was applied to estimate the near-surface Tair considering the complex terrain such as mountainous regions. The retrieval results produced from this study showed a good agreement (RMSE < 2.5 K) with weather measurements from the Korea Forest Service (KFS) for mountain regions and the Korea Meteorology Administration (KMA). The gaps in the MODIS Tair data due to cloud contamination were successfully filled using the proposed method which yielded similar accuracy as retrievals of clear sky. The results of this study indicate that the satellite data fusion can continuously produce Tair retrievals with reasonable accuracy and that the application of the temperature lapse rate can lead to improvement of the reliability over complex terrains such as the Korean Peninsula.

Air Pollution Over the Ganges Basin and Northwest Bay of Bengal in the Early Postmonsoon Season Based on NASA MERRAero Data

NASA Technical Reports Server (NTRS)

Kishcha, Pavel; Da Silva, Arlindo M.; Starobinets, Boris; Alpert, Pinhas

2014-01-01

The MERRA Aerosol Reanalysis (MERRAero) has been recently developed at NASA's Global Modeling Assimilation Office. This reanalysis is based on a version of the Goddard Earth Observing System-5 (GEOS-5) model radiatively coupled with Goddard Chemistry, Aerosol, Radiation, and Transport aerosols, and it includes assimilation of bias-corrected aerosol optical thickness (AOT) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on both Terra and Aqua satellites. In October over the period 2002-2009, MERRAero showed that AOT was lower over the east of the Ganges basin than over the northwest of the Ganges basin: this was despite the fact that the east of the Ganges basin should have produced higher anthropogenic aerosol emissions because of higher population density, increased industrial output, and transportation. This is evidence that higher aerosol emissions do not always correspond to higher AOT over the areas where the effects of meteorological factors on AOT dominate those of aerosol emissions. MODIS AOT assimilation was essential for correcting modeled AOT mainly over the northwest of the Ganges basin, where AOT increments were maximal. Over the east of the Ganges basin and northwest Bay of Bengal (BoB), AOT increments were low and MODIS AOT assimilation did not contribute significantly to modeled AOT. Our analysis showed that increasing AOT trends over northwest BoB (exceeding those over the east of the Ganges basin) were reproduced by GEOS-5, not because of MODIS AOT assimilation butmainly because of the model capability of reproducing meteorological factors contributing to AOT trends. Moreover, vertically integrated aerosol mass flux was sensitive to wind convergence causing aerosol accumulation over northwest BoB.

Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements

NASA Astrophysics Data System (ADS)

Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho

2016-12-01

Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.

Global cloud database from VIRS and MODIS for CERES

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan

2003-04-01

The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

An Algorithm for the Retrieval of Droplet Number Concentration and Geometrical Thickness of Stratiform Marine Boundary Layer Clouds Applied to MODIS Radiometric Observations.

NASA Astrophysics Data System (ADS)

Schüller, Lothar; Bennartz, Ralf; Fischer, Jürgen; Brenguier, Jean-Louis

2005-01-01

Algorithms are now currently used for the retrieval of cloud optical thickness and droplet effective radius from multispectral radiance measurements. This paper extends their application to the retrieval of cloud droplet number concentration, cloud geometrical thickness, and liquid water path in shallow convective clouds, using an algorithm that was previously tested with airborne measurements of cloud radiances and validated against in situ measurements of the same clouds. The retrieval is based on a stratified cloud model of liquid water content and droplet spectrum. Radiance measurements in visible and near-infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is operated from the NASA platforms Terra and Aqua, are analyzed. Because of uncertainties in the simulation of the continental surface reflectance, the algorithm is presently limited to the monitoring of the microphysical structure of boundary layer clouds over the ocean. Two MODIS scenes of extended cloud fields over the North Atlantic Ocean trade wind region are processed. A transport and dispersion model (the Hybrid Single-Particle Lagrangian Integrated Trajectory Model, HYSPLIT4) is also used to characterize the origin of the air masses and hence their aerosol regimes. One cloud field formed in an air mass that was advected from southern Europe and North Africa. It shows high values of the droplet concentration when compared with the second cloud system, which developed in a more pristine environment. The more pristine case also exhibits a higher geometrical thickness and, thus, liquid water path, which counterbalances the expected cloud albedo increase of the polluted case. Estimates of cloud liquid water path are then compared with retrievals from the Special Sensor Microwave Imager (SSM/I). SSM/I-derived liquid water paths are in good agreement with the MODIS-derived values.

Monitoring Rangeland Health by Remote Sensing

USDA-ARS?s Scientific Manuscript database

Based on a land-cover classification from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS), rangelands cover 48% of the Earth’s land surface, not including Antarctica. Nearly all analyses imply the most economical means of monitoring large areas of rangelands worldwide is with remote s...

Classification and Accuracy Assessment for Coarse Resolution Mapping within the Great Lakes Basin, USA

EPA Science Inventory

This study applied a phenology-based land-cover classification approach across the Laurentian Great Lakes Basin (GLB) using time-series data consisting of 23 Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) composite images (250 ...

Measuring Radiant Emissions from Entire Prescribed Fires with Ground, Airborne and Satellite Sensors RxCADRE 2012

NASA Technical Reports Server (NTRS)

Dickinson, Matthew B.; Hudak, Andrew T.; Zajkowski, Thomas; Loudermilk, E. Louise; Schroeder, Wilfrid; Ellison, Luke; Kremens, Robert L.; Holley, William; Martinez, Otto; Paxton, Alexander;

Capability of MODIS radiance to analyze Iberian turbid plumes

NASA Astrophysics Data System (ADS)

Fernandez-Novoa, Diego; deCastro, Maite; Des, Marisela; Costoya, Xurxo; Mendes, Renato; Gomez-Gesteira, Moncho

2017-04-01

River plumes are formed near river mouths by freshwater and riverine materials. Therefore, the area influenced by freshwater (salinity plume) is usually negatively correlated with the area occupied by suspension and dissolved material (turbid plume). Suspended material results in a strong signal detected by satellite sensors whereas ocean clear waters have negligible contributions. Thus, remote sensing data, such as radiance obtained from Moderate Resolution Imaging Spectroradiometer (MODIS), are a very useful tool to analyze turbid plumes due to the high spatial and time resolution provided. Here, MODIS capability for characterizing similarities and differences among the most important Iberian plumes was assessed under the influence of their main forcing. Daily radiance data from MODIS-Aqua and MODIS-Terra satellite sensors were processed obtaining a resolution of 500 m. Two approaches are usually used for atmospheric correction treatments: Near-Infrared (NIR) bands and a combined algorithm using NIR and Short Wave Infrared (SWIR) bands. In the particular case of Iberian Peninsula plumes both methods offered similar results, although NIR bands present a lower associated error. MODIS allows working with several bands of normalized water-leaving radiances (nLw). Focusing in the resolution provided, nLw555 and 645 were the most appropriate because both provide the best coverage and correlation with river discharge. The nLw645 band was chosen because has a lower water penetration avoiding overestimations of turbidity caused by shallow seafloor areas and/or upwelling blooms. Daily data from both satellites were merged to enhance the robustness and precision of the study by increasing the number of available pixels. Results indicate that differences between radiance data from both satellites are negligible for Iberian plumes, justifying the merging. By last, each turbid limit, to delimit the respective plume from adjacent seawater, was obtained using two alternative methods. The first method evaluates the maximum correlation between river discharge and plume extension and the second one analyzes a histogram of radiance distribution for days characterized by a negligible plume and days showing a well-developed plume. The capability of MODIS radiance to delimit each river plume was tested by means of salinity data from Atlantic-Iberian Biscay Irish-Ocean Physics Reanalysis (IBI) database. Significant and negative correlations were found in the Atlantic Iberian plumes, showing the capability of MODIS to adequately track them. However, no correlation was found for Ebro River. This discrepancy is due to the presence of fresh water associated to other external sources (Rhone River), promoting low salinity values when Ebro discharge is low. In this particular case, the MODIS methodology is better to determine the river plume. In general, Atlantic Iberian plumes show a moderate or high dependence on river discharge, being wind a secondary forcing and tide the third one, although each plume presents particular features. On the other hand, Ebro plume has low dependence on river discharge and wind, and a negligible one on tide, being mainly driven for the Liguro-Provençal current.

Influence of Humidity On the Aerosol Scattering Coefficient and Its Effect on the Upwelling Radiance During ACE-2

NASA Technical Reports Server (NTRS)

Gasso, S.; Hegg, D. A.; Covert, D. S.; Collins, D.; Noone, K. J.; Oestroem, E.; Schmid, B.; Russell, P. B.; Livingston, J. M.; Durkee, P. A.

2000-01-01

Aerosol scattering coefficients (sigma(sub sp)) have been measured over the ocean at different relative humidities (RH) as a function of altitude in the region surrounding the Canary Islands during the Second Aerosol Characterization Experiment (ACE-2) in June and July 1997. The data were collected by the University of Washington passive humidigraph (UWPH) mounted on the Pelican research aircraft. Concurrently, particle size distributions, absorption coefficients and aerosol optical depth were measured throughout 17 flights. A parameterization of sigma(sub sp) as a function of RH was utilized to assess the impact of aerosol hydration on the upwelling radiance (normalized to the solar constant and cosine of zenith angle). The top of the atmosphere radiance signal was simulated at wavelengths corresponding to visible and near-infrared bands of the EOS (Earth Observing System) AM-1 (Terra) detectors, MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer). The UWPH measured sigma(sub sp) at two RHs, one below and the other above ambient conditions. Ambient sigma(sub sp) was obtained by interpolation of these two measurements. The data were stratified in terms of three types of aerosols: Saharan dust, clean marine (marine boundary layer background) and polluted marine aerosols (i.e., two- or one-day old polluted aerosols advected from Europe). An empirical relation for the dependence of sigma(sub sp) on RH, defined by sigma(sub sp)(RH) = k.(1 - RH/100)(sup gamma), was used with the hygroscopic exponent gamma derived from the data. The following gamma values were obtained for the 3 aerosol types: gamma(dust) = 0.23 +/- 0.05, gamma(clean marine) = 0.69 +/- 0.06 and gamma(polluted marine) = 0.57 +/- 0.06. Based on the measured gammas, the above equation was utilized to derive aerosol models with different hygroscopicities. The satellite simulation signal code 6S was used to compute the upwelling radiance corresponding to each of those aerosol models at several ambient humidities. For the prelaunch estimated precision of the sensors and the assumed viewing geometry of the instrument, the simulations suggest that the spectral and angular dependence of the reflectance measured by MISR is not sufficient to distinguish aerosol models with various different combinations of values for dry composition, gamma and ambient RH. A similar behavior is observed for MODIS at visible wavelengths. However, the 2100 nm band of MODIS appears to be able to differentiate between at least same aerosol models with different aerosol hygroscopicity given the MODIS calibration error requirements. This result suggests the possibility of retrieval of aerosol hygroscopicity by MODIS.

Automatic Boosted Flood Mapping from Satellite Data

NASA Technical Reports Server (NTRS)

Coltin, Brian; McMichael, Scott; Smith, Trey; Fong, Terrence

2016-01-01

Numerous algorithms have been proposed to map floods from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, most require human input to succeed, either to specify a threshold value or to manually annotate training data. We introduce a new algorithm based on Adaboost which effectively maps floods without any human input, allowing for a truly rapid and automatic response. The Adaboost algorithm combines multiple thresholds to achieve results comparable to state-of-the-art algorithms which do require human input. We evaluate Adaboost, as well as numerous previously proposed flood mapping algorithms, on multiple MODIS flood images, as well as on hundreds of non-flood MODIS lake images, demonstrating its effectiveness across a wide variety of conditions.

Fires in Kamchatka Peninsula, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

Numerous thermal anomalies were detected on the Kamchatka Peninsula in northeastern Russia in late June and early July by the Moderate Resolution Imaging Spectroradiometer (MODIS). Some of the anomalies (red dots) were fires, but at least one was the result of ongoing volcanic activity at one of the Peninsula's numerous active volcanoes. The erupting volcano, called Sheveluch, can be seen most clearly in the image from July 8, 2002. It is located in the upper right quadrant of the image, and appears as a grayish circular patch amid the surrounding green vegetation. In its center is a red dot indicating that MODIS detected a thermal signature coming from the restless volcano. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations

NASA Astrophysics Data System (ADS)

Le, Chengfeng; Hu, Chuanmin; English, David; Cannizzaro, Jennifer; Chen, Zhiqiang; Feng, Lian; Boler, Richard; Kovach, Charles

2013-02-01

Despite recent advances in using satellite data for continuous monitoring of estuarine water quality parameters such as turbidity and water clarity, estimating chlorophyll-a concentrations (Chla) has remained problematic due to the optical complexity of estuarine waters and imperfect atmospheric correction. This poses a significant challenge to the community as synoptic and frequent Chla “measurements” from satellites are in high demand by various government agencies and environmental groups to help make management decisions. Here, using 10 years of in situ and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from a moderately sized, turbid estuary, Tampa Bay (Florida, USA), we developed and validated a new algorithm specifically designed for retrieving Chla from MODIS data. The algorithm takes the red-to-green remote-sensing reflectance (Rrs(λ)) band ratio of [Rrs(667) + Rrs(678)]/[Rrs(531) + Rrs(547)] as the independent variable, and estimates Chla through the non-linear regression function: Ln(Chla) = 1.91Ln(x) + 3.40 (R2 = 0.87, N = 97, p < 0.01, 1.5 < Chla < 80 mg m-3) where ‘x' is the band ratio. Validation of the algorithm using two independent datasets collected by different groups and near-concurrent MODIS measurements showed robust algorithm performance for Chla within this range, with mean relative errors of 25.8% and 41.7% for the two datasets. Time-series analyses at representative stations using both in situ and MODIS Chla also showed general agreement, with instances of noticeable discrepancy attributed to different measurement frequencies. The algorithm was implemented to establish a 10-year Chla data record for Tampa Bay in order to serve as a baseline for monitoring future phytoplankton bloom events. The 10-year Chla data record showed substantial variability in both space and time, with generally higher Chla observed during the wet season and in upper bay segments, and Chla minima observed in all bay segments during May and June. These spatial and temporal distributions appear to be regulated primarily by wind and river discharge, which also explain the significant declining trend in Chla since 2005. The established 10-year MODIS-based Chla data record provides complementary information to existing field-based monitoring programs, helping to make nutrient reduction management decisions. Furthermore, preliminary tests of the algorithm for the Chesapeake Bay and for Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements suggest possible applicability of the proposed approach to other estuaries and satellite ocean color sensors.

On the impact of different volcanic hot spot detection methods on eruption energy quantification

NASA Astrophysics Data System (ADS)

Pergola, Nicola; Coviello, Irina; Falconieri, Alfredo; Lacava, Teodosio; Marchese, Francesco; Tramutoli, Valerio

2016-04-01

Several studies have shown that sensors like the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) may be effectively used to identify volcanic hotspots. These sensors offer in fact some spectral channels in the Medium Infrared (MIR) and Thermal Infrared (TIR) bands together with a good compromise between spatial and temporal resolution suited to study and monitor thermal volcanic activity. Many algorithms were developed to identify volcanic thermal anomalies from space with some of them that were extensively tested in very different geographich areas. In this work, we analyze the volcanic radiative power (VRP) representing one of parameters of major interest for volcanologists that may be estimated by satellite. In particular, we compare the radiative power estimations driven by some well-established state of the art hotspot detection methods (e.g. RSTVOLC, MODVOLC, HOTSAT). Differences in terms of radiative power estimations achieved during recent Mt. Etna (Italy) eruptions will be evaluated, assessing how much the VRP retrieved during effusive eruptions is affected by the sensitivity of hotspot detection methods.

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Zubko, V.; Gopalan, A.

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

Phytoplankton off the West Coast of Africa

NASA Technical Reports Server (NTRS)

2002-01-01

Just off the coast of West Africa, persistent northeasterly trade winds often churn up deep ocean water. When the nutrients in these deep waters reach the ocean's surface, they often give rise to large blooms of phytoplankton. This image of the Mauritanian coast shows swirls of phytoplankton fed by the upwelling of nutrient-rich water. The scene was acquired by the Medium Resolution Imaging Spectrometer (MERIS) aboard the European Space Agency's ENVISAT. MERIS will monitor changes in phytoplankton across Earth's oceans and seas, both for the purpose of managing fisheries and conducting global change research. NASA scientists will use data from this European instrument in the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program. The mission of SIMBIOS is to construct a consistent long-term dataset of ocean color (phytoplankton abundance) measurements made by multiple satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the Moderate-Resolution Imaging Spectroradiometer (MODIS). For more information about MERIS and ENVISAT, visit the ENVISAT home page. Image copyright European Space Agency

Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Friedl, Mark A.; Schaaf, Crystal B.

2006-12-01

In the last two decades the availability of global remote sensing data sets has provided a new means of studying global patterns and dynamics in vegetation. The vast majority of previous work in this domain has used data from the Advanced Very High Resolution Radiometer, which until recently was the primary source of global land remote sensing data. In recent years, however, a number of new remote sensing data sources have become available that have significantly improved the capability of remote sensing to monitor global ecosystem dynamics. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer to study global vegetation phenology. Using a novel new method based on fitting piecewise logistic models to time series data from MODIS, key transition dates in the annual cycle(s) of vegetation growth can be estimated in an ecologically realistic fashion. Using this method we have produced global maps of seven phenological metrics at 1-km spatial resolution for all ecosystems exhibiting identifiable annual phenologies. These metrics include the date of year for (1) the onset of greenness increase (greenup), (2) the onset of greenness maximum (maturity), (3) the onset of greenness decrease (senescence), and (4) the onset of greenness minimum (dormancy). The three remaining metrics are the growing season minimum, maximum, and summation of the enhanced vegetation index derived from MODIS. Comparison of vegetation phenology retrieved from MODIS with in situ measurements shows that these metrics provide realistic estimates of the four transition dates identified above. More generally, the spatial distribution of phenological metrics estimated from MODIS data is qualitatively realistic, and exhibits strong correspondence with temperature patterns in mid- and high-latitude climates, with rainfall seasonality in seasonally dry climates, and with cropping patterns in agricultural areas.

Validation of the MODIS "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Koenig, L. S.; DiGirolamo, N. E.; Comiso, J.; Shuman, C. A.

2011-01-01

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 (MODIS) 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 Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua 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 Reflection 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 (MODIS) 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 Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua 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 Reflection Radiometer. In this work, we focus on 1) and 2) above. First we provide comparisons between Terra and Aqua swath-based ISTs at approximately 14:00 Local Solar Time, reprojected to 12.5 km polar stereographic cells. Results show good correspondence when Terra and Aqua data were acquired within 2 hrs of each other. For example, for a cell centered over Summit Camp (72.58 N, 38.5 W), the average agreement between Terra and Aqua ISTs is 0.74 K (February 2003), 0.47 K (April 2003), 0.7 K (August 2003) and 0.96 K (October 2003) with the Terra ISTs being generally lower than the Aqua ISTs. More precise comparisons will be calculated using pixel data at the swath level, and correspondence between Terra and Aqua IST is expected to be closer. (Because of cloud cover and other considerations, only a few common cloud-free swaths are typically available for each month for comparison.) Additionally, previous work comparing land-surface temperatures (LSTs) from the standard MODIS LST product and in-situ surface-temperature data at Summit Camp on the Greenland Ice Sheet show that Terra MODIS LSTs are about 3 K lower than in-situ temperatures at Summit Camp, during the winter of 2008-09. This work will be repeated using both Terra and Aqua IST pixel data (in place of LST data). In conclusion, we demonstrate that the uncertainties in the CDR will be well characterized as we work through the various facets of its validation.

Multiple Scale Remote Sensing for Monitoring Rangelands

USDA-ARS?s Scientific Manuscript database

Based on a land-cover classification from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS), rangelands cover 48% of the Earth’s land surface, not including Antarctica. Nearly all analyses imply the most economical means of monitoring large areas of rangelands worldwide is with remote se...

Recent weather extremes and impact agricultural production and vector-borne disease patterns

USDA-ARS?s Scientific Manuscript database

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA’s satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to ...

Global inter-comparison of microwave and infrared LST from multiple sensors (AMSR-E, MODIS, SEVIRI, GOES, and MTSAT-2)

NASA Astrophysics Data System (ADS)

Ermida, Sofia L.; Jiménez, Carlos; Prigent, Catherine; Trigo, Isabel F.; DaCamara, Carlos C.

2017-04-01

Land Surface Temperature (LST) is an important diagnostic parameter of land surface conditions. Satellite LST products generally rely on measurements in the thermal infrared (IR) atmospheric window, which only allows clear sky estimates. Microwave (MW) observations can alternatively be used to derive an all-weather LST. Here we present an inter-comparison between LST derived from the Advanced Microwave Scanning Radiometer - Earth observation system (AMSR-E), the MODerate resolution Imaging Spectroradiometer (MODIS) on-board Aqua, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board Meteosat Second Generation (MSG) satellites, the Geostationary Operational Environmental Satellite (GOES) and the Japanese Meteorological Imager (JAMI) on-board the Multifunction Transport SATellite (MTSAT-2). The higher discrepancies between MW and IR products are observed over snow covered areas. MW emissivity is highly variable for snow-covered ground and not always properly accounted for by the climatological emissivity used in the retrieval. There is a conspicuous bias between MODIS and AMSR-E over desert areas, which is most likely related to the underestimation of LST by MODIS as previously reported in other studies. Inter-comparison between all IR and MW retrievals shows that the STD of the differences between MW and IR LST is generally higher than between IR retrievals. However, the biases between MW and IR LST are, in some cases, of the same order as the ones observed among infrared products. In particular, GOES presents a daytime bias with respect to AMSR-E of 0.45 K whereas the bias with respect to MODIS is 0.60 K. Given that AMSR-E can provide LST under cloudy conditions, the use of microwaves, considering simultaneous overpasses with IR, represents an increase of more than 250% of the number of available LST estimates over equatorial regions. With the MW products of a comparable quality to the IR ones, the MW LST is a very powerful complement of the IR estimates.

Applications of MODIS satellite data and products for monitoring air quality in the state of Texas

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.

The Center for Space Research (CSR), in conjunction with the Monitoring Operations Division (MOD) of the Texas Commission on Environmental Quality (TCEQ), is evaluating the use of remotely sensed satellite data to assist in monitoring and predicting air quality in Texas. The challenges of meeting air quality standards established by the US Environmental Protection Agency (US EPA) are impacted by the transport of pollution into Texas that originates from outside our borders and are cumulative with those generated by local sources. In an attempt to quantify the concentrations of all pollution sources, MOD has installed ground-based monitoring stations in rural regions along the Texas geographic boundaries including the Gulf coast, as well as urban regions that are the predominant sources of domestic pollution. However, analysis of time-lapse GOES satellite imagery at MOD, clearly demonstrates the shortcomings of using only ground-based observations for monitoring air quality across Texas. These shortcomings include the vastness of State borders, that can only be monitored with a large number of ground-based sensors, and gradients in pollution concentration that depend upon the location of the point source, the meteorology governing its transport to Texas, and its diffusion across the region. With the launch of NASA's MODerate resolution Imaging Spectroradiometer (MODIS), the transport of aerosol-borne pollutants can now be monitored over land and ocean surfaces. Thus, CSR and MOD personnel have applied MODIS data to several classes of pollution that routinely impact Texas air quality. Results demonstrate MODIS data and products can detect and track the migration of pollutants. This paper presents one case study in which continental haze from the northeast moved into the region and subsequently required health advisories to be issued for 150 counties in Texas. It is concluded that MODIS provides the basis for developing advanced data products that will, when used in conjunction with ground-based observations, create a cost-effective and accurate pollution monitoring system for the entire state of Texas.

Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

NASA Astrophysics Data System (ADS)

Wang, Y.; Hioki, S.; Yang, P.; Di Girolamo, L.; Fu, D.

2017-12-01

The precise estimation of two important cloud optical and microphysical properties, cloud particle optical thickness and cloud particle effective radius, is fundamental in the study of radiative energy budget and hydrological cycle. In retrieving these two properties, an appropriate selection of ice particle surface roughness is important because it substantially affects the single-scattering properties. At present, using a predetermined ice particle shape without spatial and temporal variations is a common practice in satellite-based retrieval. This approach leads to substantial uncertainties in retrievals. The cloud radiances measured by each of the cameras of the Multi-angle Imaging SpectroRadiometer (MISR) instrument are used to estimate spherical albedo values at different scattering angles. By analyzing the directional distribution of estimated spherical albedo values, the degree of ice particle surface roughness is estimated. With an optimal degree of ice particle roughness, cloud optical thickness and effective radius are retrieved based on a bi-spectral shortwave technique in conjunction with two Moderate Resolution Imaging Spectroradiometer (MODIS) bands centered at 0.86 and 2.13 μm. The seasonal biases of retrieved cloud optical and microphysical properties, caused by the uncertainties in ice particle roughness, are investigated by using one year of MISR-MODIS fused data.

Variability of Marine Aerosol Fine-Mode Fraction and Estimates of Anthropogenic Aerosol Component Over Cloud-Free Oceans from the Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Yu, Hongbin; Chin, Mian; Remer, Lorraine A.; Kleidman, Richard G.; Bellouin, Nicolas; Bian, Huisheng; Diehl, Thomas

2009-01-01

In this study, we examine seasonal and geographical variability of marine aerosol fine-mode fraction (f(sub m)) and its impacts on deriving the anthropogenic component of aerosol optical depth (tau(sub a)) and direct radiative forcing from multispectral satellite measurements. A proxy of f(sub m), empirically derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 data, shows large seasonal and geographical variations that are consistent with the Goddard Chemistry Aerosol Radiation Transport (GOCART) and Global Modeling Initiative (GMI) model simulations. The so-derived seasonally and spatially varying f(sub m) is then implemented into a method of estimating tau(sub a) and direct radiative forcing from the MODIS measurements. It is found that the use of a constant value for fm as in previous studies would have overestimated Ta by about 20% over global ocean, with the overestimation up to 45% in some regions and seasons. The 7-year (2001-2007) global ocean average tau(sub a) is 0.035, with yearly average ranging from 0.031 to 0.039. Future improvement in measurements is needed to better separate anthropogenic aerosol from natural ones and to narrow down the wide range of aerosol direct radiative forcing.

Assessing the Success of Postfire Reseeding in Semiarid Rangelands Using Terra MODIS

NASA Technical Reports Server (NTRS)

Chen, Fang; Weber, Keith T.; Scbnase, John L.

2012-01-01

Successful postfire reseeding efforts can aid rangeland ecosystem recovery by rapidly establishing a desired plant community and thereby reducing the likelihood of infestation by invasive plants. Although the success of postfire remediation is critical, few efforts have been made to leverage existing geospatial technologies to develop methodologies to assess reseeding success following a fire. In this study, Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data were used to improve the capacity to assess postfire reseeding rehabilitation efforts, with particular emphasis on the semiarid rangelands of Idaho. Analysis of MODIS data demonstrated a positive effect of reseeding on rangeland ecosystem recovery, as well as differences in vegetation between reseeded areas and burned areas where no reseeding had occurred (P,0.05). We conclude that MODIS provides useful data to assess the success of postfire reseeding.

A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions

USGS Publications Warehouse

Selkowitz, David J.; Green, Gordon; Peterson, Birgit E.; Wylie, Bruce

2012-01-01

Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of resulting height maps. The finding that winter, snow-covered MISR imagery can be used to map canopy height is important because clear sky days are nearly three times as common during the late winter period as during the growing season. The increased odds of acquiring cloud-free imagery during the target acquisition period make regularly updated forest height inventories for Interior Alaska much more feasible. A major advantage of the GLAS–MISR–MODIS canopy height mapping methodology described here is that this approach uses only data that is freely available worldwide, making the approach potentially applicable across the entire circumpolar boreal forest region.

MODIS: Moderate-resolution imaging spectrometer. Earth observing system, volume 2B

NASA Technical Reports Server (NTRS)

1986-01-01

The Moderate-Resolution Imaging Spectrometer (MODIS), as presently conceived, is a system of two imaging spectroradiometer components designed for the widest possible applicability to research tasks that require long-term (5 to 10 years), low-resolution (52 channels between 0.4 and 12.0 micrometers) data sets. The system described is preliminary and subject to scientific and technological review and modification, and it is anticipated that both will occur prior to selection of a final system configuration; however, the basic concept outlined is likely to remain unchanged.

View Angle Effects on MODIS Snow Mapping in Forests

NASA Technical Reports Server (NTRS)

Xin, Qinchuan; Woodcock, Curtis E.; Liu, Jicheng; Tan, Bin; Melloh, Rae A.; Davis, Robert E.

2012-01-01

Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas.

Space environment's effect on MODIS calibration

NASA Astrophysics Data System (ADS)

Dodd, J. L.; Wenny, B. N.; Chiang, K.; Xiong, X.

2010-09-01

The MODerate resolution Imaging Spectroradiometer flies on board the Earth Observing System (EOS) satellites Terra and Aqua 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 Aqua was launched on May 4, 2002. As the MODIS instruments on board these satellites continue to operate beyond the design lifetime of six years, the cumulative effect of the space environment on MODIS 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 MODIS. 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 MODIS and the spacecraft, either directly or indirectly, possibly resulting in data loss. Efforts from the Terra and Aqua Flight Operations Teams (FOT), the MODIS Instrument Operations Team (IOT), and the MODIS Characterization Support Team (MCST) prevent or minimize external impact on the TOA calibrated data. This paper discusses specific effects of the space environment on MODIS and how they are minimized.

eMODIS Expedited: Overview of a Near Real Time MODIS Production System for Operational Vegetation Monitoring

NASA Astrophysics Data System (ADS)

Jenkerson, C.; Meyer, D. J.; Werpy, J.; Evenson, K.; Merritt, M.

2010-12-01

The expedited MODIS, or eMODIS production system derives near-real time Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance 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 eMODIS 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/eMODIS) allows users direct access to eMODIS 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.

Abstract Art or Arbiters of Energy?

NASA Technical Reports Server (NTRS)

2002-01-01

More than just the idle stuff of daydreams, clouds help control the flow of radiant energy around our world. Clouds are plentiful and widespread throughout Earth's atmosphere-covering up to 75 percent of our planet at any given time-so they play a dominant role in determining how much sunlight reaches the surface, how much sunlight is reflected back into space, how and where warmth is spread around the globe, and how much heat escapes from the surface and atmosphere back into space. Clouds are also highly variable. Clouds' myriad variations through time and space make them one of the greatest areas of uncertainty in scientists' understanding and predictions of climate change. In short, they play a central role in our world's climate system. The false-color image above shows a one-month composite of cloud optical thickness measured by the Moderate-resolution Imaging Spectroradiometer (MODIS) and averaged globally for April 2001. Optical thickness is a measure of how much solar radiation is not allowed to travel through a column of atmosphere. Areas colored red and yellow indicate very cloudy skies, on average, while areas colored green and light blue show moderately cloudy skies. Dark blue regions show where there is little or no cloud cover. This data product is an important new tool for helping scientists understand the roles clouds play in our global climate system. MODIS gives scientists new capabilities for measuring the structure and composition of clouds. MODIS observes the entire Earth almost every day in 36 spectral bands ranging from visible to thermal infrared wavelengths, enabling it to quantify a wide suite of clouds' physical and radiative properties. Specifically, MODIS can determine whether a cloud is composed of ice or water particles (or some combination of the two), it can measure the effective radius of the particles within a cloud, it can determine the temperature and altitude of cloud tops, and it can observe how much sunlight passes through a cloud. MODIS is one of five sensors flying aboard NASA's Terra satellite, the flagship in NASA's Earth Observing System, launched in December 1999. For more information about this and other new MODIS products, read NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Atmosphere Group, NASA GSFC

Characterizing surface temperature and clarity of Kuwait's seawaters using remotely sensed measurements and GIS analyses

NASA Astrophysics Data System (ADS)

Alsahli, Mohammad M. M.

Kuwait sea surface temperature (SST) and water clarity are important water characteristics that influence the entire Kuwait coastal ecosystem. The spatial and temporal distributions of these important water characteristics should be well understood to obtain a better knowledge about this productive coastal environment. The aim of this project was therefore to study the spatial and temporal distributions of: Kuwait SST using Moderate Resolution Imaging Spectroradiometer (MODIS) images collected from January 2003 to July 2007; and Kuwait Secchi Disk Depth (SDD), a water clarity measure, using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and MODIS data collected from November 1998 to October 2004 and January 2003 to June 2007, respectively. Kuwait SST was modeled based on the linear relationship between level 2 MODIS SST data and in situ SST data. MODIS SST images showed a significant relationship with in situ SST data ( r2= 0.98, n = 118, RMSE = 0.7°C). Kuwait SST images derived from MODIS data exhibited three spatial patterns of Kuwait SST across the year that were mainly attributed to the northwestern counterclockwise water circulation of the Arabian Gulf, and wind direction and intensity. The temporal variation of Kuwait SST was greatly influenced by the seasonal variation of solar intensity and air temperatures. Kuwait SDD was measured through two steps: first, computing the diffuse light attenuation coefficient at 490 nm, Kd(490), and 488 nm, Kd(488), derived from SeaWiFS and MODIS, respectively, using a semi-analytical algorithm; second, establishing two SDD models based on the empirical relationship of Kd(490) and Kd(488) with in situ SDD data. Kd(490) and Kd(488) showed a significant relationship with in situ SDD data ( r2= 0.67 and r2= 0.68, respectively). Kuwait SDD images showed distinct spatial and temporal patterns of Kuwait water clarity that were mainly attributed to three factors: the Shatt Al-Arab discharge, water circulation, and coastal currents. The SeaWiFS and MODIS data compared to in situ measurements provided a comprehensive view of the studied seawater characteristics that improved their overall estimation within Kuwait's waters. Also, the near-real-time availability of SeaWiFS and MODIS data and their highly temporal resolution make them a very advantageous tool for studying coastal environments. Thus, I recommend involving this method in monitoring Kuwait coastal environments.

Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic.

PubMed

Kampel, Milton; Lorenzzetti, João A; Bentz, Cristina M; Nunes, Raul A; Paranhos, Rodolfo; Rudorff, Frederico M; Politano, Alexandre T

2009-01-01

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3M(RAD)), Ocean Chlorophyll 4 bands (OC4v4(RAD)), and Ocean Chlorophyll 2 bands (OC2v4(RAD)). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3M(SAT), and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01(SAT)), and Carder(SAT). In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m(3). In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m(3) (OC2v4(RAD)). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m(3)) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m(3), respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of R(RS) by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm performance, in the satellite sensor calibration, and in the atmospheric-correction algorithm.

Implementation of the Land, Atmosphere Near Real-Time Capability for EOS (LANCE)

NASA Technical Reports Server (NTRS)

Michael, Karen; Murphy, Kevin; Lowe, Dawn; Masuoka, Edward; Vollmer, Bruce; Tilmes, Curt; Teague, Michael; Ye, Gang; Maiden, Martha; Goodman, H. Michael;

Post-hurricane forest damage assessment using satellite remote sensing

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu; J.A. Stanturf

2010-01-01

This study developed a rapid assessment algorithm for post-hurricane forest damage estimation using moderate resolution imaging spectroradiometer (MODIS) measurements. The performance of five commonly used vegetation indices as post-hurricane forest damage indicators was investigated through statistical analysis. The Normalized Difference Infrared Index (NDII) was...

Cross-Calibration of Earth Observing System Terra Satellite Sensors MODIS and ASTER

NASA Technical Reports Server (NTRS)

McCorkel, J.

2014-01-01

The Advanced Spaceborne Thermal Emissive and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (MODIS) are two of the five sensors onboard the Earth Observing System's Terra satellite. These sensors share many similar spectral channels while having much different spatial and operational parameters. ASTER is a tasked sensor and sometimes referred to a zoom camera of the MODIS that collects a full-earth image every one to two days. It is important that these sensors have a consistent characterization and calibration for continued development and use of their data products. This work uses a variety of test sites to retrieve and validate intercalibration results. The refined calibration of Collection 6 of the Terra MODIS data set is leveraged to provide the up-to-date reference for trending and validation of ASTER. Special attention is given to spatially matching radiance measurements using prelaunch spatial response characterization of MODIS. Despite differences in spectral band properties and spatial scales, ASTER-MODIS is an ideal case for intercomparison since the sensors have nearly identical views and acquisitions times and therefore can be used as a baseline of intercalibration performance of other satellite sensor pairs.

Characterization of 2014 summer drought over Henan province using remotely sensed data

NASA Astrophysics Data System (ADS)

Lu, Jing; Jia, Li; Zhou, Jie

2015-12-01

An exceptional drought struck Henan province during the summer of 2014. It caused directly the financial loss reaching to hundreds of billion Yuan (RMB), and brought the adverse influence for people's life, agricultural production as well as the ecosystem. The study in this paper characterized the Henan 2014 summer drought event through analyzing the spatial distribution of drought severity using precipitation data from Tropical Rainfall Measuring Mission (TRMM) sensor and Normalized difference vegetation index (NDVI) and land surface temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The trend analysis of the annual precipitation from 2003 to 2014 showed that the region over Henan province is becoming dry. Especially in the east of Henan province, the decrease of precipitation is more obvious with the maximum change rate of ~48 mm/year. The rainfall in summer (from June to August) of 2014 was the largest negtive anomaly in contrast with the same period of historical years, which was 43% lower than the average of the past ten years. Drought severity derived from Standardized Precipitation Index (SPI) indicated that all areas of Henan province experienced drought in summer of 2014 with different severity levels. The extreme drought, accounting for about 22.7 % of Henan total area, mainly occurred in Luohe, Xuchang, and Pingdingshan regions, and partly in Nanyang, Zhengzhou, and Jiaozuo. This is consistent with the statistics from local municipalities. The Normalized Drought Index Anomaly (NDAI), calculated from MODIS NDVI and LST products, can capture the evolution of the Henan 2014 summer drought effectively. Drought severity classified by NDAI also agreed well with the result from the SPI.

Detection of Green up Phenomenon in Amazon Forests Using Spaceborne Solar-induced Fluorescence

NASA Astrophysics Data System (ADS)

Chen, S.; Chen, X.; Chen, J.; Cao, X.

2016-12-01

The role of Amazon forests in the global carbon budget still remains uncertain. The critical issue is whether tropical forest productivity is more limited by sunlight or rainfall. Recent studies using satellite data have challenged the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions because of the adding effects of variations in sun-sensor geometry. To reducing uncertainties in knowing the sensitivity of Amazon rainforests to dry season droughts, we evaluated a newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll for the seasonal green-up phenomenon, providing for the first time a direct measurement related to vegetation photosynthetic activity as well as unaffected by sun-sensor geometry. Moreover, NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) products (the enhanced vegetation index (EVI) and leaf area index (LAI)) and Landsat Operational Land Imager (OLI) data are also compared to evaluate this phenomenon. Here we show that the green up of Amazon forests in the study area around manas site did show in SIF of chlorophyll data in 2015 drought resulted from seasonal changes. The EVI has more apparent green up phenomenon than the NDVI data both in MODIS and OLI data, suggesting that the EVI can better reflect near-infrared (NIR) and LAI information of vegetation. The OLI data is less influenced by variations caused by bidirectional reflectance effect. In addition, SIF of chlorophyll data shows well correlation relationship with the EVI, LAI and NDVI, suggesting that the SIF of chlorophyll data present well quality to capture the characteristics of the phenology of vegetation.

Fractional Snowcover Estimates from Earth Observing System (EOS) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Salomonson, Vincent V.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua missions has shown considerable capability for mapping snowcover. The typical approach that has used, along with other criteria, the Normalized Snow Difference Index (NDSI) that takes the difference between 500 meter observations at 1.64 micrometers (MODIS band 6) and 0.555 micrometers (MODIS band 4) over the sum of these observations to determine whether MODIS pixels are snowcovered or not in mapping the extent of snowcover. For many hydrological and climate studies using remote sensing of snowcover, it is desirable to assess if the MODIS snowcover observations could not be enhanced by providing the fraction of snowcover in each MODIS observation (pixel). Pursuant to this objective studies have been conducted to assess whether there is sufficient "signal%o in the NDSI parameter to provide useful estimates of fractional snowcover in each MODIS 500 meter pixel. To accomplish this objective high spatial resolution (30 meter) Landsat snowcover observations were used and co-registered with MODIS 500 meter pixels. The NDSI approach was used to assess whether a Landsat pixel was or was not snowcovered. Then the number of snowcovered Landsat pixels within a MODIS pixel was used to determine the fraction of snowcover within each MODIS pixel. The e results were then used to develop statistical relationships between the NDSI value for each 500 meter MODIS pixel and the fraction of snowcover in the MODIS pixel. Such studies were conducted for three widely different areas covered by Landsat scenes in Alaska, Russia, and the Quebec Province in Canada. The statistical relationships indicate that a 10 percent accuracy can be attained. The variability in the statistical relationship for the three areas was found to be remarkably similar (-0.02 for mean error and less than 0.01 for mean absolute error and standard deviation). Independent tests of the relationships were accomplished by taking the relationship of fractional snow-cover to NDSI from one area (e.g., Alaska) and testing it on the other two areas (e.g. Russia and Quebec). Again the results showed that fractional snow-cover can be estimated to 10 percent. The results have been shown to have advantages over other published fractional snowcover algorithms applied to MODIS data. Most recently the fractional snow-cover algorithm has been applied using 500-meter observations over the state of Colorado for a period spanning 25 days. The results exhibit good behavior in mapping the spatial and temporal variability in snowcover over that 25-day period. Overall these studies indicate that robust estimates of fractional snow-cover can be attained using the NDSI parameter over areas extending in size from watersheds relatively large compared to MODIS pixels to global land cover. Other refinements to this approach as well as different approaches are being examined for mapping fractional snow-cover using MODIS observations.

Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

NASA Technical Reports Server (NTRS)

Yang, Wenze; Huang, Dong; Tan, Bin; Stroeve, Julienne C.; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2006-01-01

The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

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

2004-01-01

Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Techniques that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that rely on visible, near-infrared, and thermal infrared channels. The availability of thermal channels to aid in cloud screening for aerosol properties is an important additional piece of information that has not always been incorporated into sensor designs. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud effective radius), and highlight the global and 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 radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles that are currently available from space-based observations, and show selected cases in which aerosol particles are observed to modify the cloud optical properties.

Development of a Multilayer MODIS IST-Albedo Product of Greenland

NASA Technical Reports Server (NTRS)

Hall, D. K.; Comiso, J. C.; Cullather, R. I.; Digirolamo, N. E.; Nowicki, S. M.; Medley, B. C.

2017-01-01

A new multilayer IST-albedo Moderate Resolution Imaging Spectroradiometer (MODIS) product of Greenland was developed to meet the needs of the ice sheet modeling community. The multiple layers of the product enable the relationship between IST and albedo to be evaluated easily. Surface temperature is a fundamental input for dynamical ice sheet models because it is a component of the ice sheet radiation budget and mass balance. Albedo influences absorption of incoming solar radiation. The daily product will combine the existing standard MODIS Collection-6 ice-surface temperature, derived melt maps, snow albedo and water vapor products. The new product is available in a polar stereographic projection in NetCDF format. The product will ultimately extend from March 2000 through the end of 2017.

Modeling spatial patterns of wildfire susceptibility in southern California: Applications of MODIS remote sensing data and mesoscale numerical weather models

NASA Astrophysics Data System (ADS)

Schneider, Philipp

This dissertation investigates the potential of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and mesoscale numerical weather models for mapping wildfire susceptibility in general and for improving the Fire Potential Index (FPI) in southern California in particular. The dissertation explores the use of the Visible Atmospherically Resistant Index (VARI) from MODIS data for mapping relative greenness (RG) of vegetation and subsequently for computing the FPI. VARI-based RG was validated against in situ observations of live fuel moisture. The results indicate that VARI is superior to the previously used Normalized Difference Vegetation Index (NDVI) for computing RG. FPI computed using VARI-based RG was found to outperform the traditional FPI when validated against historical fire detections using logistic regression. The study further investigates the potential of using Multiple Endmember Spectral Mixture Analysis (MESMA) on MODIS data for estimating live and dead fractions of vegetation. MESMA fractions were compared against in situ measurements and fractions derived from data of a high-resolution, hyperspectral sensor. The results show that live and dead fractions obtained from MODIS using MESMA are well correlated with the reference data. Further, FPI computed using MESMA-based green vegetation fraction in lieu of RG was validated against historical fire occurrence data. MESMA-based FPI performs at a comparable level to the traditional NDVI-based FPI, but can do so using a single MODIS image rather than an extensive remote sensing time series as required for the RG approach. Finally this dissertation explores the potential of integrating gridded wind speed data obtained from the MM5 mesoscale numerical weather model in the FPI. A new fire susceptibility index, the Wind-Adjusted Fire Potential Index (WAFPI), was introduced. It modifies the FPI algorithm by integrating normalized wind speed. Validating WAFPI against historical wildfire events using logistic regression indicates that gridded data sets of wind speed are a valuable addition to the FPI as they can significantly increase the probability range of the fitted model and can further increase the model's discriminatory power over that of the traditional FPI.

Assessment of Consistencies and Uncertainties between the NASA MODIS and VIIRS Snow-Cover Maps

NASA Astrophysics Data System (ADS)

Hall, D. K.; Riggs, G. A., Jr.; DiGirolamo, N. E.; Roman, M. O.

2017-12-01

Snow cover has great climatic and economic importance in part due to its high albedo and low thermal conductivity and large areal extent in the Northern Hemisphere winter, and its role as a freshwater source for about one-sixth of the world's population. The Rutgers University Global Snow Lab's 50-year climate-data record (CDR) of Northern Hemisphere snow cover is invaluable for climate studies, but, at 25-km resolution, the spatial resolution is too coarse to provide accurate snow information at the basin scale. Since 2000, global snow-cover maps have been produced from the MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites at 500-m resolution, and from the Suomi-National Polar Program (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) since 2011 at 375-m resolution. Development of a moderate-resolution (375 - 500 m) earth system data record (ESDR) that utilizes both MODIS and VIIRS snow maps is underway. There is a 6-year overlap between the data records. In late 2017 the second in a series of VIIRS sensors will be launched on the Joint Polar Satellite System-1 (JPSS-1), with the JPSS-2 satellite scheduled for launch in 2021, providing the potential to extend NASA's snow-cover ESDR for decades into the future and to create a CDR. Therefore it is important to investigate the continuity between the MODIS and VIIRS NASA snow-cover data products and evaluate whether there are any inconsistencies and biases that would affect their value as CDR. Time series of daily normalized-difference snow index (NDSI) Terra and Aqua MODIS Collection 6 (C6) and NASA VIIRS Collection 1 (C1) snow-cover tile maps (MOD10A1 and VNP10A1) are studied for North America to identify NDSI differences and possible biases between the datasets. Developing a CDR using the MODIS and VIIRS records is challenging. Though the instruments and orbits are similar, differences in bands, viewing geometry, spatial resolution, and cloud- and snow-mapping algorithms affect snow detection.

Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Lawrence, William T.; Plaza, Antonio J.

2006-01-01

The hierarchical segmentation (HSEG) algorithm is a hybrid of hierarchical step-wise optimization and constrained spectral clustering that produces a hierarchical set of image segmentations. This segmentation hierarchy organizes image data in a manner that makes the image's information content more accessible for analysis by enabling region-based analysis. This paper discusses data analysis with HSEG and describes several measures of region characteristics that may be useful analyzing segmentation hierarchies for various applications. Segmentation hierarchy analysis for generating landwater and snow/ice masks from MODIS (Moderate Resolution Imaging Spectroradiometer) data was demonstrated and compared with the corresponding MODIS standard products. The masks based on HSEG segmentation hierarchies compare very favorably to the MODIS standard products. Further, the HSEG based landwater mask was specifically tailored to the MODIS data and the HSEG snow/ice mask did not require the setting of a critical threshold as required in the production of the corresponding MODIS standard product.

MODIS Technical Report Series. Volume 4: MODIS data access user's guide: Scan cube format

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.; Goff, Thomas E.

1994-01-01

The software described in this document provides I/O functions to be used with Moderate Resolution Spectroradiometer (MODIS) level 1 and 2 data, and could be easily extended to other data sources. This data is in a scan cube data format: a 3-dimensional ragged array containing multiple bands which have resolutions ranging from 250 to 1000 meters. The complexity of the data structure is handled internally by the library. The I/O calls allow the user to access any pixel in any band through 'C' structure syntax. The high MODIS data volume (approaching half a terabyte per day) has been a driving factor in the library design. To avoid recopying data for user access, all I/O is performed through dynamic 'C' pointer manipulation. This manual contains background material on MODIS, several coding examples of library usage, in-depth discussions of each function, reference 'man' type pages, and several appendices with details of the included files used to customize a user's data product for use with the library.

Validation of MODIS Aerosol Retrievals during PRIDE

NASA Technical Reports Server (NTRS)

Levy, R.; Remier, L.; Kaufman, Y.; Kleidman, R.; Holben, B.; Russell, P.; Livingston, J.; Einaudi, Franco (Technical Monitor)

2000-01-01

The Puerto Rico Dust Experiment (PRIDE) was held in Roosevelt Roads, Puerto Rico from June 26 to July 24, 2000. It was intended to study the radiative and microphysical properties of Saharan dust transported into Puerto Rico. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from MODIS (MODerate Imaging Spectro-radiometer - aboard the Terra satellite) with data from a variety of ground, shipboard and air-based instruments. Over the ocean the MODIS algorithm retrieves optical depth as well as information about the aerosol's size. During PRIDE, MODIS passed over Roosevelt Roads approximately once per day during daylight hours. Due to sunglint and clouds over Puerto Rico, aerosol retrievals can be made from only about half the MODIS scenes. In this study we try to "validate" our aerosol retrievals by comparing to measurements taken by sun-photometers from multiple platforms, including: Cimel (AERONET) from the ground, Microtops (handheld) from ground and ship, and the NASA-Ames sunphotometer from the air.

Operational data fusion framework for building frequent Landsat-like imagery in a cloudy region

USDA-ARS?s Scientific Manuscript database

An operational data fusion framework is built to generate dense time-series Landsat-like images for a cloudy region by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) data products and Landsat imagery. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is integrated in ...

REFINING FIRE EMISSIONS FOR AIR QUALITY MODELING WITH REMOTELY-SENSED FIRE COUNTS: A WILDFIRE CASE STUDY

EPA Science Inventory

This paper examines the use of Moderate Resolution Imaging Spectroradiometer (MODIS) observed active fire data (pixel counts) to refine the National Emissions Inventory (NEI) fire emission estimates for major wildfire events. This study was motivated by the extremely limited info...

Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu

2009-01-01

In the southeastern United States, most wildland fires are of low intensity. Asubstantial number of these fires cannot be detected by the MODIS contextual algorithm. Toimprove the accuracy of fire detection for this region, the remote-sensed characteristics ofthese fires have to be systematically...

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. In this paper, the algorithms of these approaches are described, their performance is demonstrated, and their impact on L1B products is discussed. In general, the shorter wavelength bands have experienced a larger on-orbit RVS change, which, in general, are mirror side and detector dependent. The on-orbit RVS change due to the degradation of band 8 can be as large as 35 percent for Terra MODIS and 20 percent for Aqua MODIS. Vital to maintaining the accuracy of the MODIS L1B products is an accurate characterization of the on-orbit RVS change. The derived time-independent RVS, implemented in C6, makes an important improvement to the quality of the MODIS L1B products.

Evaluation, Calibration and Comparison of the Precipitation-Runoff Modeling System (PRMS) National Hydrologic Model (NHM) Using Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) Gridded Datasets

NASA Astrophysics Data System (ADS)

Norton, P. A., II; Haj, A. E., Jr.

2014-12-01

The United States Geological Survey is currently developing a National Hydrologic Model (NHM) to support and facilitate coordinated and consistent hydrologic modeling efforts at the scale of the continental United States. As part of this effort, the Geospatial Fabric (GF) for the NHM was created. The GF is a database that contains parameters derived from datasets that characterize the physical features of watersheds. The GF was used to aggregate catchments and flowlines defined in the National Hydrography Dataset Plus dataset for more than 100,000 hydrologic response units (HRUs), and to establish initial parameter values for input to the Precipitation-Runoff Modeling System (PRMS). Many parameter values are adjusted in PRMS using an automated calibration process. Using these adjusted parameter values, the PRMS model estimated variables such as evapotranspiration (ET), potential evapotranspiration (PET), snow-covered area (SCA), and snow water equivalent (SWE). In order to evaluate the effectiveness of parameter calibration, and model performance in general, several satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) gridded datasets including ET, PET, SCA, and SWE were compared to PRMS-simulated values. The MODIS and SNODAS data were spatially averaged for each HRU, and compared to PRMS-simulated ET, PET, SCA, and SWE values for each HRU in the Upper Missouri River watershed. Default initial GF parameter values and PRMS calibration ranges were evaluated. Evaluation results, and the use of MODIS and SNODAS datasets to update GF parameter values and PRMS calibration ranges, are presented and discussed.

Spatiotemporal changes of snow cover over the Tibetan plateau based on cloud-removed moderate resolution imaging spectroradiometer fractional snow cover product from 2001 to 2011

NASA Astrophysics Data System (ADS)

Tang, Zhiguang; Wang, Jian; Li, Hongyi; Yan, Lili

2013-01-01

Snow cover changes over the Tibetan plateau (TP) are examined using moderate resolution imaging spectroradiometer (MODIS) daily fractional snow cover (FSC) data from 2001 to 2011 as well as in situ temperature data. First, the accuracy of the MODIS FSC data under clear sky conditions is evaluated by comparing with Landsat 30-m observations. Then we describe a cloud-gap-filled (CGF) method using cubic spline interpolation algorithm to fill in data gaps caused by clouds. Finally, the spatial and temporal changes of snow cover are analyzed on the basis of the MODIS-derived snow-covered area and snow-covered days (SCD) data. Results show that the mean absolute error of MODIS FSC data under clear sky condition is about 0.098 over the TP. The CGF method is efficient in cloud reduction (overall mean absolute error of the retrieved FSC data is 0.092). There is a very high inter-annual and intra-seasonal variability of snow cover in the 11 years. The higher snow cover corresponds well with the huge mountains. The accumulation and melt periods of snow cover vary in different elevation zones. About 34.14% (5.56% with a significant decline) and 24.75% (3.9% with a significant increase) of the study area presents declining and increasing trend in SCD, respectively. The inter-annual fluctuation of snow cover can be explained by the high negative correlations observed between the snow cover and the in situ temperature, especially in some elevations of February, April, May, August, and September.

Production of Arctic Sea-ice Albedo by fusion of MISR and MODIS data

NASA Astrophysics Data System (ADS)

Kharbouche, Said; Muller, Jan-Peter

2017-04-01

We have combined data from the NASA MISR and MODIS spectro-radiometers to create a cloud-free albedo dataset specifically for sea-ice. The MISR (Multi-Angular Spectro-Radiometer) instrument on board Terra satellite has a unique ability to create high-quality Bidirectional Reflectance (BRF) over a 7 minute time interval per single overpass, thanks to its 9 cameras of different view angles (±70°,±60°,±45°,±26°). However, as MISR is limited to narrow spectral bands (443nm, 555nm, 670nm, 865nm), which is not sufficient to mask cloud effectively and robustly, we have used the sea-ice mask MOD09 product (Collection 6) from MODIS (Moderate resolution Imaging Spectoradiometer) instrument, which is also on board Terra satellite and acquiring data simultaneously. Only We have created a new and consistent sea-ice (for Arctic) albedo product that is daily, from 1st March to 22nd September for each and every year between 2000 to 2016 at two spatial grids, 1km x 1km and 5km x 5km in polar stereographic projection. Their analysis is described in a separate report [1]. References [1] Muller & Kharbouche, Variation of Arctic's Sea-ice Albedo between 2000 and 2016 by fusion of MISR and MODIS data. This conference. Acknowledgements This work was supported by www.QA4ECV.eu, a project of European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 607405. We thank our colleagues at JPL and NASA LaRC for processing these data, especially Sebastian Val and Steve Protack.

Invisible Cirrus Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

The Moderate-resolution Imaging Spectroradiometer's (MODIS') cloud detection capability is so sensitive that it can detect clouds that would be indistinguishable to the human eye. This pair of images highlights MODIS' ability to detect what scientists call 'sub-visible cirrus.' The image on top shows the scene using data collected in the visible part of the electromagnetic spectrum-the part our eyes can see. Clouds are apparent in the center and lower right of the image, while the rest of the image appears to be relatively clear. However, data collected at 1.38um (lower image) show that a thick layer of previously undetected cirrus clouds obscures the entire scene. These kinds of cirrus are called 'sub-visible' because they can't be detected using only visible light. MODIS' 1.38um channel detects electromagnetic radiation in the infrared region of the spectrum. These images were made from data collected on April 4, 2000. Image courtesy Mark Gray, MODIS Atmosphere Team

The Characterization of a DIRSIG Simulation Environment to Support the Inter-Calibration of Spaceborne Sensors

NASA Technical Reports Server (NTRS)

Ambeau, Brittany L.; Gerace, Aaron D.; Montanaro, Matthew; McCorkel, Joel

2016-01-01

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed..

The characterization of a DIRSIG simulation environment to support the inter-calibration of spaceborne sensors

NASA Astrophysics Data System (ADS)

Ambeau, Brittany L.; Gerace, Aaron D.; Montanaro, Matthew; McCorkel, Joel

2016-09-01

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed.

Multi-sensor Efforts to Detect Oil slicks at the Ocean Surface — An Applied Science Project

NASA Astrophysics Data System (ADS)

Gallegos, S. C.; Pichel, W. G.; Hu, Y.; Garcia-Pineda, O. G.; Kukhtarev, N.; Lewis, D.

2012-12-01

In 2008, The Naval Research Laboratory at Stennis Space Center (NRL-SSC), NASA-Langley Space Center (LaRC) and NOAA Center for Satellite Applications and Research (STAR) with the support of the NASA Applied Science Program developed the concept for an operational oil detection system to support NOAA's mission of oil spill monitoring and response. Due to the current lack of a spaceborne sensor specifically designed for oil detection, this project relied on data and algorithms for the Synthetic Aperture Radar (SAR) and the Moderate Resolution Imaging Spectroradiometer (MODIS). NOAA/Satellite Analyses Branch (NOAA/SAB) was the transition point of those algorithms. Part of the research also included the evaluation of the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) capabilities for detection of surface and subsurface oil. In April 2010, while conducting the research in the Gulf of Mexico, the Deep Water Horizon (DWH) oil spill, the largest accidental marine oil spill in the history of the petroleum industry impacted our area. This incident provided opportunities to expand our efforts to the field, the laboratory, and to the data of other sensors such as the Hyperspectral Imager of the Coastal Zone (HICO). We summarize the results of our initial effort and describe in detail those efforts carried out during the DWH oil spill.

The Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) Experiment

NASA Technical Reports Server (NTRS)

Smith, William L., Jr.; Charlock, Thomas; Wielicki, Bruce; Kahn, Ralph; Martins, J. Vanderlei; Gatebe, Charles; Hobbs, Peter V.; Purgold, G. Carl; Redemann, Jens; Remer, Lorraine

2004-01-01

NASA has developed an Earth Observing System (EOS) consisting of a series of satellites designed to study global change from space. The EOS flagship is the EOS TERRA satellite, launched in December 1999, equipped with five unique sensors to monitor and study the Earth s heat budget and many of the key controlling variables governing the Earth's climate system. CLAMS, the Chesapeake Lighthouse and Aircraft Measurements for Satellites field campaign was conducted from NASA Wallops Flight Facility and successfully executed over the middle Atlantic eastern seaboard from July 10 August 2, 2001. CLAMS is primarily a shortwave closure experiment designed to validate and improve EOS TERRA satellite data products being derived from three sensors: CERES (Clouds and Earth's Radiant Energy System), MISR (Multi-angle Imaging Spectro-Radiometer) and MODIS (MODerate Resolution Imaging Spectroradiometer). CLAMS is jointly sponsored by the CERES, MISR and MODIS instrument teams and the NASA GEWEX Global Aerosol Climatology Project (GACP). CLAMS primary objectives are to validate satellite-based retrievals of aerosol properties and vertical profiles of radiative flux, temperature and water vapor. Central to CLAMS measurement strategy is the Chesapeake Lighthouse, a stable sea platform located in the Atlantic Ocean, 13 miles east of Virginia Beach near the mouth of the Chesapeake Bay and the site of an ongoing CERES Ocean Validation Experiment (COVE). Six research aircraft were deployed to make detailed measurements of the atmosphere and ocean surface in the vicinity of COVE, over the surrounding ocean, over nearby NOAA buoys and over a few land sites. The measurements are used to validate and provide ground truth for simultaneous products being derived from TERRA data, a key step toward an improved understanding and ability to predict changes in the Earth's climate. One of the two CERES instruments on-board TERRA was programmed for Rotating Azimuth Plane Scans (RAPS) during CLAMS, increasing the CERES coverage over COVE by a factor of 10. Nine coordinated aircraft missions and numerous additional sorties were flown under a variety of atmospheric conditions and aerosol loadings. On one golden day, July 17, all six aircraft flew coordinated patterns, vertically stacked between 100 ft and 65,000 ft over the COVE site as the TERRA satellite orbited overhead. A summary of CLAMS measurement campaign and a description of the platforms and measurements is given.

High-resolution LIDAR and ground observations of snow cover in a complex forested terrain in the Sierra Nevada - implications for optical remote sensing of seasonal snow.

NASA Astrophysics Data System (ADS)

Kostadinov, T. S.; Harpold, A.; Hill, R.; McGwire, K.

2017-12-01

Seasonal snow cover is a key component of the hydrologic regime in many regions of the world, especially those in temperate latitudes with mountainous terrain and dry summers. Such regions support large human populations which depend on the mountain snowpack for their water supplies. It is thus important to quantify snow cover accurately and continuously in these regions. Optical remote-sensing methods are able to detect snow and leverage space-borne spectroradiometers with global coverage such as MODIS to produce global snow cover maps. However, snow is harder to detect accurately in mountainous forested terrain, where topography influences retrieval algorithms, and importantly - forest canopies complicate radiative transfer and obfuscate the snow. Current satellite snow cover algorithms assume that fractional snow-covered area (fSCA) under the canopy is the same as the fSCA in the visible portion of the pixel. In-situ observations and first principles considerations indicate otherwise, therefore there is a need for improvement of the under-canopy correction of snow cover. Here, we leverage multiple LIDAR overflights and in-situ observations with a distributed fiber-optic temperature sensor (DTS) to quantify snow cover under canopy as opposed to gap areas at the Sagehen Experimental Forest in the Northern Sierra Nevada, California, USA. Snow-off LIDAR overflights from 2014 are used to create a baseline high-resolution digital elevation model and classify pixels at 1 m resolution as canopy-covered or gap. Low canopy pixels are excluded from the analysis. Snow-on LIDAR overflights conducted by the Airborne Snow Observatory in 2016 are then used to classify all pixels as snow-covered or not and quantify fSCA under canopies vs. in gap areas over the Sagehen watershed. DTS observations are classified as snow-covered or not based on diel temperature fluctuations and used as validation for the LIDAR observations. LIDAR- and DTS-derived fSCA is also compared with retrievals from hyperspectral imaging spectroradiometer (AVIRIS) data. Initial evidence suggest fSCA was generally lower under canopy and that overall snow cover estimates were overestimated as a result. Implications for a canopy correction applicable to coarser-resolution sensors like MODIS are discussed, as are topography and view angle effects.

Evaluation of the MODIS Retrievals of Dust Aerosol over the Ocean during PRIDE

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Holben, Brent N.; Livingston, John M.; Russell, Philip B.; Maring, Hal

2002-01-01

The Puerto Rico Dust Experiment (PRIDE) took place in Roosevelt Roads, Puerto Rico from June 26 to July 24,2000 to study the radiative and physical properties of African dust aerosol transported into the region. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from the MODerate Imaging Spectro-radiometer (MODIS) with sunphotometer and in-situ aerosol measurements. Over the ocean, the MODIS algorithm retrieves aerosol optical depth (AOD) as well as information about the aerosols size distribution. During PRIDE, MODIS derived AODs in the red wavelengths (0.66 micrometers) compare closely with AODs measured from sunphotometers, but, are too large at blue and green wavelengths (0.47 and 0.55 micrometers) and too small in the infrared (0.87 micrometers). This discrepancy of spectral slope results in particle size distributions retrieved by MODIS that are small compared to in-situ measurements, and smaller still when compared to sunphotometer sky radiance inversions. The differences in size distributions are, at least in part, associated with MODIS simplification of dust as spherical particles. Analysis of this PRIDE data set is a first step towards derivation of realistic non-spherical models for future MODIS retrievals.

Size-dependent validation of MODIS MCD64A1 burned area over six vegetation types in boreal Eurasia: Large underestimation in croplands

NASA Astrophysics Data System (ADS)

Zhu, C.; Kobayashi, H.; Kanaya, Y.; Saito, M.

2017-12-01

Pollutants emitted from wildfires in boreal Eurasia can be transported to the Arctic, and their subsequent deposition could accelerate global warming. The Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned area product is used widely for global mapping of burned areas in conjunction with products such as the Global Fire Emission Database version 4, which can estimate pollutant emissions. However, uncertainties due to the "moderate resolution" (500 m) characteristic of the MODIS sensor could be introduced. Here, we present a size-dependent validation of MCD64A1 with reference to higher resolution (better than 30 m) satellite products (Landsat 7 ETM+, RapidEye, WorldView-2, and GeoEye-1) for six ecotypes over 12 regions of boreal Eurasia. We considered the 2012 boreal Eurasia burning season when severe wildfires occurred and when Arctic sea ice extent was historically low. Among the six ecotypes, we found MCD64A1 burned areas comprised only 13% of the reference products in croplands because of inadequate detection of small fires (<100 ha). Our results indicate that over all ecotypes, the actual burned area in boreal Eurasia (15,256 km2) could have been 16% greater than suggested by MCD64A1 (13,187 km2). We suggest applying correction factors of 0.5-8.2 when using emission rates based on MCD64A1 burned areas in chemistry and climate models of the studied regions. This implies the effects of wildfire emissions in boreal Eurasia on Arctic warming could be greater than currently estimated.

Terra Data Confirm Warm, Dry U.S. Winter

NASA Technical Reports Server (NTRS)

2002-01-01

New maps of land surface temperature and snow cover produced by NASA's Terra satellite show this year's winter was warmer than last year's, and the snow line stayed farther north than normal. The observations confirm earlier National Oceanic and Atmospheric Administration reports that the United States was unusually warm and dry this past winter. (Click to read the NASA press release and to access higher-resolution images.) For the last two years, a new sensor aboard Terra has been collecting the most detailed global measurements ever made of our world's land surface temperatures and snow cover. The Moderate-resolution Imaging Spectroradiometer (MODIS) is already giving scientists new insights into our changing planet. Average temperatures during December 2001 through February 2002 for the contiguous United States appear to have been unseasonably warm from the Rockies eastward. In the top image the coldest temperatures appear black, while dark green, blue, red, yellow, and white indicate progressively warmer temperatures. MODIS observes both land surface temperature and emissivity, which indicates how efficiently a surface absorbs and emits thermal radiation. Compared to the winter of 2000-01, temperatures throughout much of the U.S. were warmer in 2001-02. The bottom image depicts the differences on a scale from dark blue (colder this year than last) to red (warmer this year than last). A large region of warm temperatures dominated the northern Great Plains, while the area around the Great Salt Lake was a cold spot. Images courtesy Robert Simmon, NASA GSFC, based upon data courtesy Zhengming Wan, MODIS Land Science Team member at the University of California, Santa Barbara's Institute for Computational Earth System Science

Swirl of Clouds over the Pacific

NASA Image and Video Library

2017-12-08

Theodore von Kármán, a Hungarian-American physicist, was the first to describe the physical processes that create long chains of spiral eddies like the one shown above. Known as von Kármán vortices the patterns can form nearly anywhere that fluid flow is disturbed by an object. Since the atmosphere behaves like a fluid, the wing of an airplane, a bridge, even an island can trigger the distinctive phenomenon. On May 22, 2013, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this natural-color image of cloud vortices behind Isla Socorro, a volcanic island located in the Pacific Ocean. The island, which is located a few hundred kilometers off the west coast of Mexico and the southern tip of Baja California, is part of the Revillagigedo Archipelago. Satellite sensors have spotted von Kármán vortices around the globe, including off of Guadalupe Island, near the coast of Chile, in the Greenland Sea, in the Arctic, and even next to a tropical storm. NASA image courtesy Jeff Schmaltz, LANCE/EOSDIS MODIS Rapid Response Team at NASA GSFC. Caption by Adam Voiland. Instrument: Terra - MODIS More info: 1.usa.gov/14VSDQa Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Using normalized difference vegetation index to estimate carbon fluxes from small rotationally grazed pastures

USGS Publications Warehouse

Skinner, R.H.; Wylie, B.K.; Gilmanov, T.G.

2011-01-01

Satellite-based normalized difference vegetation index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern United States might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (submeter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the moderate resolution imaging spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007, and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on MODIS 7-d NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed from each other by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term management-induced changes in GPP at individual sites.

Stray-Light Correction of the Marine Optical Buoy

NASA Technical Reports Server (NTRS)

Brown, Steven W.; Johnson, B. Carol; Flora, Stephanie J.; Feinholz, Michael E.; Yarbrough, Mark A.; Barnes, Robert A.; Kim, Yong Sung; Lykke, Keith R.; Clark, Dennis K.

2003-01-01

In ocean-color remote sensing, approximately 90% of the flux at the sensor originates from atmospheric scattering, with the water-leaving radiance contributing the remaining 10% of the total flux. Consequently, errors in the measured top-of-the atmosphere radiance are magnified a factor of 10 in the determination of water-leaving radiance. Proper characterization of the atmosphere is thus a critical part of the analysis of ocean-color remote sensing data. It has always been necessary to calibrate the ocean-color satellite sensor vicariously, using in situ, ground-based results, independent of the status of the pre-flight radiometric calibration or the utility of on-board calibration strategies. Because the atmosphere contributes significantly to the measured flux at the instrument sensor, both the instrument and the atmospheric correction algorithm are simultaneously calibrated vicariously. The Marine Optical Buoy (MOBY), deployed in support of the Earth Observing System (EOS) since 1996, serves as the primary calibration station for a variety of ocean-color satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Japanese Ocean Color Temperature Scanner (OCTS) , and the French Polarization and Directionality of the Earth's Reflectances (POLDER). MOBY is located off the coast of Lanai, Hawaii. The site was selected to simplify the application of the atmospheric correction algorithms. Vicarious calibration using MOBY data allows for a thorough comparison and merger of ocean-color data from these multiple sensors.

Determination of the single scattering albedo and direct radiative forcing of biomass burning aerosol with data from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite instrument

NASA Astrophysics Data System (ADS)

Zhu, Li

Biomass burning aerosols absorb and scatter solar radiation and therefore affect the energy balance of the Earth-atmosphere system. The single scattering albedo (SSA), the ratio of the scattering coefficient to the extinction coefficient, is an important parameter to describe the optical properties of aerosols and to determine the effect of aerosols on the energy balance of the planet and climate. Aerosol effects on radiation also depend strongly on surface albedo. Large uncertainties remain in current estimates of radiative impacts of biomass burning aerosols, due largely to the lack of reliable measurements of aerosol and surface properties. In this work we investigate how satellite measurements can be used to estimate the direct radiative forcing of biomass burning aerosols. We developed a method using the critical reflectance technique to retrieve SSA from the Moderate Resolution Imaging Spectroradiometer (MODIS) observed reflectance at the top of the atmosphere (TOA). We evaluated MODIS retrieved SSAs with AErosol RObotic NETwork (AERONET) retrievals and found good agreements within the published uncertainty of the AERONET retrievals. We then developed an algorithm, the MODIS Enhanced Vegetation Albedo (MEVA), to improve the representations of spectral variations of vegetation surface albedo based on MODIS observations at the discrete 0.67, 0.86, 0.47, 0.55, 1.24, 1.64, and 2.12 mu-m channels. This algorithm is validated using laboratory measurements of the different vegetation types from the Amazon region, data from the Johns Hopkins University (JHU) spectral library, and data from the U.S. Geological Survey (USGS) digital spectral library. We show that the MEVA method can improve the accuracy of flux and aerosol forcing calculations at the TOA compared to more traditional interpolated approaches. Lastly, we combine the MODIS retrieved biomass burning aerosol SSA and the surface albedo spectrum determined from the MEVA technique to calculate TOA flux and aerosol direct radiative forcing over the Amazon region and compare it with Clouds and the Earth's Radiant Energy System (CERES) satellite results. The results show that MODIS based forcing calculations present similar averaged results compared to CERES, but MODIS shows greater spatial variation of aerosol forcing than CERES. Possible reasons for these differences are explored and discussed in this work. Potential future research based on these results is discussed as well.

Evaluation of Detector-to-Detector and Mirror Side Differences for Terra MODIS Reflective Solar Bands Using Simultaneous MISR Observations

NASA Technical Reports Server (NTRS)

Wu, Aisheng; Xiong, Xiaoxiong; Angal, A.; Barnes, W.

2011-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) 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. MODIS 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. MODIS makes observations using a two-sided paddle-wheel scan mirror. Its on-board calibrators (OBCs) for the reflective 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 MODIS observed Earth scene reflectances to track the detector-to-detector and mirror side differences. Simultaneous observed reflectances from the Multi-angle Imaging Spectroradiometer (MISR), also onboard the Terra spacecraft, are used with MODIS observed reflectances 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 study is part of the effort by the MODIS Characterization Support Team (MCST) in order to track the RSB on-orbit performance for MODIS collection 5 data products. To support MCST efforts for future data re-processing, this analysis will be extended to include more spectral bands and temporal coverage.

Clear-Sky Narrowband Albedo Datasets Derived from Modis Data

NASA Astrophysics Data System (ADS)

Chen, Y.; Minnis, P.; Sun-Mack, S.; Arduini, R. F.; Hong, G.

2013-12-01

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 the clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the near-infrared (NIR; 1.24, 1.6 or 2.13 μm) and visible (VIS; 0.63 μm) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to help identify clouds and retrieve their properties. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. The clear-sky albedos are derived using a radiative transfer parameterization of the impact of the atmosphere, including aerosols, on the observed reflectances. This paper presents the method of generating monthly clear-sky overhead albedo maps for both snow-free and snow-covered surfaces of these channels using one year of MODIS (Moderate Resolution Imaging Spectroradiometer) CERES products. Maps of 1.24 and 1.6 μm are being used as the background to help retrieve cloud properties (e.g., effective particle size, optical depth) in CERES cloud retrievals in both snow-free and snow-covered conditions.

Typhoon Usagi approaching China

NASA Image and Video Library

2013-09-23

The Moderate Resolution Imaging Spectroradiometer or MODIS instrument that flies aboard NASA's Terra satellite captured this image of Typhoon Usagi on Sept. 22 at 02:45 UTC/Sept. 21 at 10:45 p.m. EDT on its approach to a landfall in China. Credit: NASA Goddard MODIS Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Wildfires, smoke, and burn scars, near Yakutsk, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

The Lena River in central Siberia is hidden beneath a veil of smoke from multiple wildfires burning around the city of Yakutsk, Russia. Fires have been burning in the region off and on since late May 2002, and may be agricultural in cause. This image was acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite on July 23, 2002. In the false=-color image, vegetation is bright green, smoke is blueish-white, and burned areas are reddish-brown. In both images, fire detections are marked with red outlines. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Cloud vortices

NASA Image and Video Library

2017-12-08

Cloud vortices off Heard Island, south Indian Ocean. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image of sea ice off Heard Island on Nov 2, 2015 at 5:02 AM EST (09:20 UTC). Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

Simulating the directional, spectral and textural properties of a large-scale scene at high resolution using a MODIS BRDF product

NASA Astrophysics Data System (ADS)

Rengarajan, Rajagopalan; Goodenough, Adam A.; Schott, John R.

2016-10-01

Many remote sensing applications rely on simulated scenes to perform complex interaction and sensitivity studies that are not possible with real-world scenes. These applications include the development and validation of new and existing algorithms, understanding of the sensor's performance prior to launch, and trade studies to determine ideal sensor configurations. The accuracy of these applications is dependent on the realism of the modeled scenes and sensors. The Digital Image and Remote Sensing Image Generation (DIRSIG) tool has been used extensively to model the complex spectral and spatial texture variation expected in large city-scale scenes and natural biomes. In the past, material properties that were used to represent targets in the simulated scenes were often assumed to be Lambertian in the absence of hand-measured directional data. However, this assumption presents a limitation for new algorithms that need to recognize the anisotropic behavior of targets. We have developed a new method to model and simulate large-scale high-resolution terrestrial scenes by combining bi-directional reflectance distribution function (BRDF) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data, high spatial resolution data, and hyperspectral data. The high spatial resolution data is used to separate materials and add textural variations to the scene, and the directional hemispherical reflectance from the hyperspectral data is used to adjust the magnitude of the MODIS BRDF. In this method, the shape of the BRDF is preserved since it changes very slowly, but its magnitude is varied based on the high resolution texture and hyperspectral data. In addition to the MODIS derived BRDF, target/class specific BRDF values or functions can also be applied to features of specific interest. The purpose of this paper is to discuss the techniques and the methodology used to model a forest region at a high resolution. The simulated scenes using this method for varying view angles show the expected variations in the reflectance due to the BRDF effects of the Harvard forest. The effectiveness of this technique to simulate real sensor data is evaluated by comparing the simulated data with the Landsat 8 Operational Land Image (OLI) data over the Harvard forest. Regions of interest were selected from the simulated and the real data for different targets and their Top-of-Atmospheric (TOA) radiance were compared. After adjusting for scaling correction due to the difference in atmospheric conditions between the simulated and the real data, the TOA radiance is found to agree within 5 % in the NIR band and 10 % in the visible bands for forest targets under similar illumination conditions. The technique presented in this paper can be extended for other biomes (e.g. desert regions and agricultural regions) by using the appropriate geographic regions. Since the entire scene is constructed in a simulated environment, parameters such as BRDF or its effects can be analyzed for general or target specific algorithm improvements. Also, the modeling and simulation techniques can be used as a baseline for the development and comparison of new sensor designs and to investigate the operational and environmental factors that affects the sensor constellations such as Sentinel and Landsat missions.

Rapid mapping of hurricane damage to forests

Treesearch

Erik M. Nielsen

2009-01-01

The prospects for producing rapid, accurate delineations of the spatial extent of forest wind damage were evaluated using Hurricane Katrina as a test case. A damage map covering the full spatial extent of Katrina?s impact was produced from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery using higher resolution training data. Forest damage...

White Sea - Russia

NASA Technical Reports Server (NTRS)

2002-01-01

At bottom center of this true-color Moderate Resolution Imaging Spectroradiometer (MODIS) image from April 13, 2001, the White Sea in western Russia is becoming free of ice in its southern extent. Meanwhile, the blue-green waters along the coast of the peninsula jutting out into the Barents Sea to the northeast could be due to a phytoplankton bloom.

Use of Normalized Difference Water Index for monitoring live fuel moisture

Treesearch

D.A. Roberts; P.E. Dennison; S.H. Peterson; J. Rechel

2006-01-01

Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were compared for monitoring live fuel moisture in a shrubland ecosystem. Both indices were calculated from 500m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data covering a 33-month period from 2000 to 2002. Both NDVI and NDWI were...

East Asian dust storm in May 2017: observations, modelling and its influence on Asia-Pacific region

USDA-ARS?s Scientific Manuscript database

A severe dust storm event originated from the Gobi Desert in Central and East Asia during 2-7 May, 2017. Based on moderate resolution imaging spectroradiometer (MODIS) satellite products, hourly environmental monitoring measurements from 367 Chinese cities and more than 2000 East Asian meteorologica...

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Molthan, Andrew L.; Schultz, Kori A.; McGrath, Kevin M.; Burks, Jason E.

2015-01-01

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the MODIS sensor aboard the NASA Aqua satellite. Aqua was chosen due to an afternoon orbit over the United States when land surface temperatures are relatively warm and improve the contrast between damaged and undamaged areas. This orbit is also similar to the orbit of the Suomi-National Polar-orbiting Partnership (NPP) satellite. The Suomi NPP satellite hosts the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which is the next generation of a MODIS-like sensor in polar orbit.

Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI

USGS Publications Warehouse

Pervez, Md Shahriar; Budde, Michael; Rowland, James

2014-01-01

Agricultural production capacity contributes to food security in Afghanistan and is largely dependent on irrigated farming, mostly utilizing surface water fed by snowmelt. Because of the high contribution of irrigated crops (> 80%) to total agricultural production, knowing the spatial distribution and year-to-year variability in irrigated areas is imperative to monitoring food security for the country. We used 16-day composites of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to create 23-point time series for each year from 2000 through 2013. Seasonal peak values and time series were used in a threshold-dependent decision tree algorithm to map irrigated areas in Afghanistan for the last 14 years. In the absence of ground reference irrigated area information, we evaluated these maps with the irrigated areas classified from multiple snapshots of the landscape during the growing season from Landsat 5 optical and thermal sensor images. We were able to identify irrigated areas using Landsat imagery by selecting as irrigated those areas with Landsat-derived NDVI greater than 0.30–0.45, depending on the date of the Landsat image and surface temperature less than or equal to 310 Kelvin (36.9 ° C). Due to the availability of Landsat images, we were able to compare with the MODIS-derived maps for four years: 2000, 2009, 2010, and 2011. The irrigated areas derived from Landsat agreed well r2 = 0.91 with the irrigated areas derived from MODIS, providing confidence in the MODIS NDVI threshold approach. The maps portrayed a highly dynamic irrigated agriculture practice in Afghanistan, where the amount of irrigated area was largely determined by the availability of surface water, especially snowmelt, and varied by as much as 30% between water surplus and water deficit years. During the past 14 years, 2001, 2004, and 2008 showed the lowest levels of irrigated area (~ 1.5 million hectares), attesting to the severe drought conditions in those years, whereas 2009, 2012 and 2013 registered the largest irrigated area (~ 2.5 million hectares) due to record snowpack and snowmelt in the region. The model holds promise the ability to provide near-real-time (by the end of the growing seasons) estimates of irrigated area, which are beneficial for food security monitoring as well as subsequent decision making for the country. While the model is developed for Afghanistan, it can be adopted with appropriate adjustments in the derived threshold values to map irrigated areas elsewhere.

Iceberg Nursery

NASA Technical Reports Server (NTRS)

2002-01-01

Almost an iceberg 'nursery,' icebergs continue to break away from the Ross Ice Shelf in Antarctica. This image from the MODerate-resolution Imaging Spectroradiometer (MODIS) aboard the Terra spacecraft, shows the level of activity along the shelf near Ross Island on September 21, 2000. The B-15 fragments are remnants of the huge iceberg (nearly 4,250 sqare miles) which broke away from the Antarctic shelf in late March 2000. Slightly visible is the line where iceberg B-20 broke away from the shelf in the last week of September. Cracks in the Antarctic ice shelf are closely observed by satellite and are of interest to scientists studying the potential effects of global warming. This true-color image was produced using MODIS bands 1, 3, and 4. Image by Brian Montgomery, NASA GSFC; data courtesy MODIS Science Team

Global Space-Based Inter-Calibration System Reflective Solar Calibration Reference: From Aqua MODIS to S-NPP VIIRS

NASA Technical Reports Server (NTRS)

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

2016-01-01

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.

Evaluation and Intercomparison of MODIS and GEOV1 Global Leaf Area Index Products over Four Sites in North China

PubMed Central

Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping

2015-01-01

This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) 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 + Aqua MODIS and Terra MODIS 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 MODIS products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + Aqua MODIS (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra MODIS (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both MODIS and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than MODIS. MODIS anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and MODIS surface reflectances. This study suggests that further improvements of the MODIS LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of MODIS observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

NASA Astrophysics Data System (ADS)

Noble, Stephen R.; Hudson, James G.

2015-08-01

Vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (re). In situ COT, LWP, and re were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and re 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however, MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14-36%. MODIS in situ re correlations were strong, but MODIS 2.1 µm re exceeded in situ re, which contributed to LWP bias; in POST, MODIS re was 20-30% greater than in situ re. Maximum in situ re near cloud top showed comparisons nearer 1:1. Other MODIS re bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS re bias that propagates to LWP while still capturing variability.

Limb Correction of Polar-Orbiting Imagery for the Improved Interpretation of RGB Composites

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Elmer, Nicholas

2016-01-01

Red-Green-Blue (RGB) composite imagery combines information from several spectral channels into one image to aid in the operational analysis of atmospheric processes. However, infrared channels are adversely affected by the limb effect, the result of an increase in optical path length of the absorbing atmosphere between the satellite and the earth as viewing zenith angle increases. This paper reviews a newly developed technique to quickly correct for limb effects in both clear and cloudy regions using latitudinally and seasonally varying limb correction coefficients for real-time applications. These limb correction coefficients account for the increase in optical path length in order to produce limb-corrected RGB composites. The improved utility of a limb-corrected Air Mass RGB composite from the application of this approach is demonstrated using Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, the limb correction can be applied to any polar-orbiting sensor infrared channels, provided the proper limb correction coefficients are calculated. Corrected RGB composites provide multiple advantages over uncorrected RGB composites, including increased confidence in the interpretation of RGB features, improved situational awareness for operational forecasters, and the ability to use RGB composites from multiple sensors jointly to increase the temporal frequency of observations.

Sensitivity Study for Sensor Optical and Electric Crosstalk Based on Spectral Measurements: An Application to Developmental Sensors Using Heritage Sensors Such As MODIS

NASA Technical Reports Server (NTRS)

Butler, James J.; Oudrari, Hassan; Xiong, Sanxiong; Che, Nianzeng; Xiong, Xiaoxiong

2007-01-01

The process of developing new sensors for space flight frequently builds upon the designs and experience of existing heritage space flight sensors. Frequently in the development and testing of new sensors, problems are encountered that pose the risk of serious impact on successful retrieval of geophysical products. This paper describes an approach to assess the importance of optical and electronic cross-talk on retrieval of geophysical products using new MODIS-like sensors through the use of MODIS data sets. These approaches may be extended to any sensor characteristic and any sensor where that characteristic may impact the Level 1 products so long as validated geophysical products are being developed from the heritage sensor. In this study, a set of electronic and/or optical cross-talk coefficients are postulated. These coefficients are sender-receiver influence coefficients and represent a sensor signal contamination on any detector on a focal plane when another band's detectors on that focal plane are stimulated with a monochromatic light. The approach involves using the postulated cross-talk coefficients on an actual set of MODIS data granules. The original MODIS data granules and the cross-talk impacted granules are used with validated geophysical algorithms to create the derived products. Comparison of the products produced with the original and cross-talk impacted granules indicates potential problems, if any, with the characteristics of the developmental sensor that are being studied.

Retrieving Land Surface Temperature and Emissivity from Multispectral and Hyperspectral Thermal Infrared Instruments

NASA Astrophysics Data System (ADS)

Hook, Simon; Hulley, Glynn; Nicholson, Kerry

2017-04-01

Land Surface Temperature and Emissivity (LST&E) data are critical variables for studying a variety of Earth surface processes and surface-atmosphere interactions such as evapotranspiration, surface energy balance and water vapor retrievals. LST&E have been identified as an important Earth System Data Record (ESDR) by NASA and many other international organizations Accurate knowledge of the LST&E is a key requirement for many energy balance models to estimate important surface biophysical variables such as evapotranspiration and plant-available soil moisture. LST&E products are currently generated from sensors in low earth orbit (LEO) such as the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites as well as from sensors in geostationary Earth orbit (GEO) such as the Geostationary Operational Environmental Satellites (GOES) and airborne sensors such as the Hyperspectral Thermal Emission Spectrometer (HyTES). LST&E products are generated with varying accuracies depending on the input data, including ancillary data such as atmospheric water vapor, as well as algorithmic approaches. NASA has identified the need to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. We will discuss the different approaches that can be used to retrieve surface temperature and emissivity from multispectral and hyperspectral thermal infrared sensors using examples from a variety of different sensors such as those mentioned, and planned new sensors like the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and the Hyperspectral Infrared Imager (HyspIRI). We will also discuss a project underway at NASA to develop a single unified product from some the individual sensor products and assess the errors associated with the product.

Sensitivity of Aerosol Multi-Sensor Daily Data Intercomparison to the Level 3 Dataday Definition

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Lary, David; Shen, Suhung; Lynnes, Christopher

2010-01-01

Topics include: why people use Level 3 products, why someone might go wrong with Level 3 products, differences in L3 from different sensors, Level 3 data day definition, MODIS vs. MODIS, AOD MODIS Terra vs. Aqua in Pacific, AOD Aqua MODIS vs. MISR correlation map, MODIS vs MISR on Terra, MODIS atmospheric data day definition, orbit time difference for Terra and Aqua 2009-01-06, maximum time difference for Terra (Calendar day), artifact explains, data day definitions, local time distribution, spatial (local time) data day definition, maximum time difference between Terra and Aqua, Removing the artifact in 16-day AOD correlation, MODIS cloud top pressure, and MODIS Terra and Aqua vs. AIRS cloud top pressure.

SeaWiFS technical report series. Volume 21: The heritage of SeaWiFS. A retrospective on the CZCS NIMBUS Experiment Team (NET) program

NASA Technical Reports Server (NTRS)

Acker, James G.; Hooker, Stanford B.; Firestone, Elaine R.

1994-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission is based on the scientific heritage of the Coastal Zone Color Scanner (CZCS), a proof-of-concept instrument carried on the National Aeronautics and Space Administration (NASA) NIMBUS-7 environmental satellite for the purpose of measuring upwelling radiance from the ocean surface. The CZCS mission provided the first observations of ocean color from space, and over the mission lifetime of 1978-1986, allowed oceanographers an initial opportunity to observe the variable patterns of global biological productivity. One of the key elements of the CZCS mission was the formation of the CZCS NIMBUS Experiment Team (NET), a group of optical physicists and biological oceanographers. The CZCS NET was designated to validate the accuracy of the CZCS radiometric measurements and to connect the instrument's measurements to standard measures of oceanic biological productivity and optical seawater clarity. In the period following the cessation of CZCS observations, some of the insight and experience gained by the CZCS NET activity has dissipated as several proposed follow-on sensors failed to achieve active status. The Sea WiFS mission will be the first dedicated orbital successor to CZCS it in turn precedes observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Earth Observing System (EOS). Since the CZCS NET experience is an important model for Sea WiFS and MODIS surface truth efforts, this document is intended to provide a comprehensive review of the validation of oceanographic data for the first orbital ocean color sensor mission. This document also summarizes the history of the CZCS NET activities. The references listed in the Bibliography are a listing of published scientific research which relied upon the CZCS BET algorithms, or research which was conducted on the basis of CZCS mission elements.

Remote sensing of the ocean contributions from ultraviolet to near-infrared using the shortwave infrared bands: simulations.

PubMed

Wang, Menghua

2007-03-20

In the remote sensing of the ocean near-surface properties, it is essential to derive accurate water-leaving radiance spectra through the process of the atmospheric correction. The atmospheric correction algorithm for Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) uses two near-infrared (NIR) bands at 765 and 865 nm (748 and 869 nm for MODIS) for retrieval of aerosol properties with assumption of the black ocean at the NIR wavelengths. Modifications are implemented to account for some of the NIR ocean contributions for the productive but not very turbid waters. For turbid waters in the coastal regions, however, the ocean could have significant contributions in the NIR, leading to significant errors in the satellite-derived ocean water-leaving radiances. For the shortwave infrared (SWIR) wavelengths (approximately > 1000 nm), water has significantly larger absorption than those for the NIR bands. Thus the black ocean assumption at the SWIR bands is generally valid for turbid waters. In addition, for future sensors, it is also useful to include the UV bands to better quantify the ocean organic and inorganic materials, as well as for help in atmospheric correction. Simulations are carried out to evaluate the performance of atmospheric correction for nonabsorbing and weakly absorbing aerosols using the NIR bands and various combinations of the SWIR bands for deriving the water-leaving radiances at the UV (340 nm) and visible wavelengths. Simulations show that atmospheric correction using the SWIR bands can generally produce results comparable to atmospheric correction using the NIR bands. In particular, the water-leaving radiance at the UV band (340 nm) can also be derived accurately. The results from a sensitivity study for the required sensor noise equivalent reflectance, (NE Delta rho), [or the signal-to-noise ratio (SNR)] for the NIR and SWIR bands are provided and discussed.

Dust transport and deposition observed from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) spacecraft over the Atlantic Ocean

NASA Astrophysics Data System (ADS)

Kaufman, Y. J.; Koren, I.; Remer, L. A.; Tanré, D.; Ginoux, P.; Fan, S.

2005-05-01

Meteorological observations, in situ data, and satellite images of dust episodes were used already in the 1970s to estimate that 100 Tg of dust are transported from Africa over the Atlantic Ocean every year between June and August and are deposited in the Atlantic Ocean and the Americas. Desert dust is a main source of nutrients to oceanic biota and the Amazon forest, but it deteriorates air quality, as shown for Florida. Dust affects the Earth radiation budget, thus participating in climate change and feedback mechanisms. There is an urgent need for new tools for quantitative evaluation of the dust distribution, transport, and deposition. The Terra spacecraft, launched at the dawn of the last millennium, provides the first systematic well-calibrated multispectral measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument for daily global analysis of aerosol. MODIS data are used here to distinguish dust from smoke and maritime aerosols and to evaluate the African dust column concentration, transport, and deposition. We found that 240 ± 80 Tg of dust are transported annually from Africa to the Atlantic Ocean, 140 ± 40 Tg are deposited in the Atlantic Ocean, 50 Tg fertilize the Amazon Basin (four times as previous estimates, thus explaining a paradox regarding the source of nutrition to the Amazon forest), 50 Tg reach the Caribbean, and 20 Tg return to Africa and Europe. The results are compared favorably with dust transport models for maximum particle diameter between 6 and 12 μm. This study is a first example of quantitative use of MODIS aerosol for a geophysical research.

Developing a Validated Long-Term Satellite-Based Albedo Record in the Central Alaska Range to Improve Regional Hydroclimate Reconstructions

NASA Astrophysics Data System (ADS)

Kreutz, K. J.; Godaire, T. P.; Burakowski, E. A.; Winski, D.; Campbell, S. W.; Wang, Z.; Sun, Q.; Hamilton, G. S.; Birkel, S. D.; Wake, C. P.; Osterberg, E. C.; Schaaf, C.

2015-12-01

Mountain glaciers around the world, particularly in Alaska, are experiencing significant surface mass loss from rapid climatic shifts and constitute a large proportion of the cryosphere's contribution to sea level rise. Surface albedo acts as a primary control on a glacier's mass balance, yet it is difficult to measure and quantify spatially and temporally in steep, mountainous settings. During our 2013 field campaign in Denali National Park to recover two surface to bedrock ice cores, we used an Analytical Spectral Devices (ASD) FieldSpec4 Standard Resolution spectroradiometer to measure incoming solar radiation, outgoing surface reflectance and optical grain size on the Kahiltna Glacier and at the Kahiltna Base Camp. A Campbell Scientific automatic weather station was installed on Mount Hunter (3900m) in June 2013, complementing a longer-term (2008-present) station installed at Kahiltna Base Camp (2100m). Use of our in situ data aids in the validation of surface albedo values derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite imagery. Comparisons are made between ASD FieldSpec4 ground measurements and 500m MODIS imagery to assess the ability of MODIS to capture the variability of surface albedo across the glacier surface. The MODIS MCD43A3 BRDF/Albedo Product performs well at Kahiltna Base Camp (<5% difference from ASD shortwave broadband data), but low biases in MODIS albedo (10-28% relative to ASD data) appear to occur along the Kahiltna Glacier due to the snow-free valley walls being captured in the 500m MODIS footprint. Incorporating Landsat imagery will strengthen our interpretations and has the potential to produce a long-term (1982-present) validated satellite albedo record for steep and mountainous terrain. Once validation is complete, we will compare the satellite-derived albedo record to the Denali ice core accumulation rate, aerosol records (i.e. volcanics and biomass burning), and glacier mass balance data. This research will ultimately contribute to an improved understanding of the relationship between glacier albedo, surface processes, and regional glacier hydroclimate.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2014-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2015-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Verification and Validation of NASA-Supported Enhancements to PECAD's Decision Support Tools

NASA Technical Reports Server (NTRS)

McKellipo, Rodney; Ross, Kenton W.

2006-01-01

The NASA Applied Sciences Directorate (ASD), part of the Earth-Sun System Division of NASA's Science Mission Directorate, has partnered with the U.S. Department of Agriculture (USDA) to enhance decision support in the area of agricultural efficiency-an application of national importance. The ASD integrated the results of NASA Earth science research into USDA decision support tools employed by the USDA Foreign Agricultural Service (FAS) Production Estimates and Crop Assessment Division (PECAD), which supports national decision making by gathering, analyzing, and disseminating global crop intelligence. Verification and validation of the following enhancements are summarized: 1) Near-real-time Moderate Resolution Imaging Spectroradiometer (MODIS) products through PECAD's MODIS Image Gallery; 2) MODIS Normalized Difference Vegetation Index (NDVI) time series data through the USDA-FAS MODIS NDVI Database; and 3) Jason-1 and TOPEX/Poseidon lake level estimates through PECAD's Global Reservoir and Lake Monitor. Where possible, each enhanced product was characterized for accuracy, timeliness, and coverage, and the characterized performance was compared to PECAD operational requirements. The MODIS Image Gallery and the GRLM are more mature and have achieved a semi-operational status, whereas the USDA-FAS MODIS NDVI Database is still evolving and should be considered

Study on ice cloud optical thickness retrieval with MODIS IR spectral bands

NASA Astrophysics Data System (ADS)

Zhang, Hong; Li, Jun

2005-01-01

The operational Moderate-Resolution Imaging Spectroradiometer (MODIS) products for cloud properties such as cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), cloud optical thickness (COT), and cloud phase (CP) have been available for users globally. An approach to retrieve COT is investigated using MODIS infrared (IR) window spectral bands (8.5 mm, 11mm, and 12 mm). The COT retrieval from MODIS IR bands has the potential to provide microphysical properties with high spatial resolution during night. The results are compared with those from operational MODIS products derived from the visible (VIS) and near-infrared (NIR) bands during day. Sensitivity of COT to MODIS spectral brightness temperature (BT) and BT difference (BTD) values is studied. A look-up table is created from the cloudy radiative transfer model accounting for the cloud absorption and scattering for the cloud microphysical property retrieval. The potential applications and limitations are also discussed. This algorithm can be applied to the future imager systems such as Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-R.

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)

2001-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS 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. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS 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 MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

Statistical Analysis of SSMIS Sea Ice Concentration Threshold at the Arctic Sea Ice Edge during Summer Based on MODIS and Ship-Based Observational Data.

PubMed

Ji, Qing; Li, Fei; Pang, Xiaoping; Luo, Cong

2018-04-05

The threshold of sea ice concentration (SIC) is the basis for accurately calculating sea ice extent based on passive microwave (PM) remote sensing data. However, the PM SIC threshold at the sea ice edge used in previous studies and released sea ice products has not always been consistent. To explore the representable value of the PM SIC threshold corresponding on average to the position of the Arctic sea ice edge during summer in recent years, we extracted sea ice edge boundaries from the Moderate-resolution Imaging Spectroradiometer (MODIS) sea ice product (MOD29 with a spatial resolution of 1 km), MODIS images (250 m), and sea ice ship-based observation points (1 km) during the fifth (CHINARE-2012) and sixth (CHINARE-2014) Chinese National Arctic Research Expeditions, and made an overlay and comparison analysis with PM SIC derived from Special Sensor Microwave Imager Sounder (SSMIS, with a spatial resolution of 25 km) in the summer of 2012 and 2014. Results showed that the average SSMIS SIC threshold at the Arctic sea ice edge based on ice-water boundary lines extracted from MOD29 was 33%, which was higher than that of the commonly used 15% discriminant threshold. The average SIC threshold at sea ice edge based on ice-water boundary lines extracted by visual interpretation from four scenes of the MODIS image was 35% when compared to the average value of 36% from the MOD29 extracted ice edge pixels for the same days. The average SIC of 31% at the sea ice edge points extracted from ship-based observations also confirmed that choosing around 30% as the SIC threshold during summer is recommended for sea ice extent calculations based on SSMIS PM data. These results can provide a reference for further studying the variation of sea ice under the rapidly changing Arctic.

Near Surface Thermal Stratification during Summer at Summit, Greenland, and its Impact on MODIS-derived Surface Temperatures

NASA Astrophysics Data System (ADS)

Adolph, A. C.; Albert, M. R.; Hall, D. K.

2017-12-01

As rapid warming of the Arctic occurs, it is imperative that we monitor climate parameters such as temperature over large areas to understand and predict the extent of climate changes. Temperatures are often tracked using in-situ 2 m air temperatures, but in remote locations such as on the Greenland Ice Sheet, temperature can be studied more comprehensively using remote sensing techniques. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and skin temperature can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign at Summit Station in Greenland to study surface temperature using the following measurements: skin temperature measured by IR sensors, thermochrons, and thermocouples; 2 m air temperature measured by a NOAA meteorological station; and two different MODerate-resolution Imaging Spectroradiometer (MODIS) surface temperature products. We confirm prior findings that in-situ 2 m air temperature is often significantly higher in the summer than in-situ skin temperature when incoming solar radiation and wind speed are low. This inversion may account for biases in previous MODIS surface temperature studies that used 2 m air temperature for validation. As compared to the in-situ IR skin temperature measurements, the MOD/MYD11 Collection 6 surface-temperature standard product has an RMSE of 1.0°C, and that the MOD29 Collection 6 product has an RMSE of 1.5°C, spanning a range of temperatures from -35°C to -5°C. For our study area and time series, MODIS surface temperature products agree with skin temperatures better than many previous studies have indicated, especially at temperatures below -20°C where other studies found a significant cold bias. Further investigation at temperatures below -35°C is warranted to determine if this bias does indeed exist.

Estimating trace gas and aerosol emissions over South America: Relationship between fire radiative energy released and aerosol optical depth observations

NASA Astrophysics Data System (ADS)

Pereira, Gabriel; Freitas, Saulo R.; Moraes, Elisabete Caria; Ferreira, Nelson Jesus; Shimabukuro, Yosio Edemir; Rao, Vadlamudi Brahmananda; Longo, Karla M.

2009-12-01

Contemporary human activities such as tropical deforestation, land clearing for agriculture, pest control and grassland management lead to biomass burning, which in turn leads to land-cover changes. However, biomass burning emissions are not correctly measured and the methods to assess these emissions form a part of current research area. The traditional methods for estimating aerosols and trace gases released into the atmosphere generally use emission factors associated with fuel loading and moisture characteristics and other parameters that are hard to estimate in near real-time applications. In this paper, fire radiative power (FRP) products were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Geostationary Operational Environmental Satellites (GOES) fire products and new South America generic biomes FRE-based smoke aerosol emission coefficients were derived and applied in 2002 South America fire season. The inventory estimated by MODIS and GOES FRP measurements were included in Coupled Aerosol-Tracer Transport model coupled to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) and evaluated with ground truth collected in Large Scale Biosphere-Atmosphere Smoke, Aerosols, Clouds, rainfall, and Climate (SMOCC) and Radiation, Cloud, and Climate Interactions (RaCCI). Although the linear regression showed that GOES FRP overestimates MODIS FRP observations, the use of a common external parameter such as MODIS aerosol optical depth product could minimize the difference between sensors. The relationship between the PM 2.5μm (Particulate Matter with diameter less than 2.5 μm) and CO (Carbon Monoxide) model shows a good agreement with SMOCC/RaCCI data in the general pattern of temporal evolution. The results showed high correlations, with values between 0.80 and 0.95 (significant at 0.5 level by student t test), for the CATT-BRAMS simulations with PM 2.5μm and CO.

Spatiotemporal variability and contribution of different aerosol types to the aerosol optical depth over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-11-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is ˜ 0.22 ± 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for ˜ 51, ˜ 34 and ˜ 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account ˜ 40, ˜ 34 and ˜ 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

Characterization of east Asian dust outbreaks in the spring of 2001 using ground-based and satellite data

NASA Astrophysics Data System (ADS)

Darmenova, Kremena; Sokolik, Irina N.; Darmenov, Anton

2005-01-01

This study presents a detailed examination of east Asian dust events during March-April of 2001, by combining satellite multisensor observation (Total Ozone Mapping Spectrometer (TOMS), Moderate-Resolution Imaging Spectroradiometer (MODIS), and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS)) meteorological data from weather stations in China and Mongolia and the Pennsylania State University/National Center for Atmospheric Research Mesoscale Modeling System (MM5) driven by the National Centers for Environmental Prediction Reanalysis data. The main goal is to determine the extent to which the routine surface meteorological observations (including visibility) and satellite data can be used to characterize the spatiotemporal distribution of dust plumes at a range of scales. We also examine the potential of meteorological time series for constraining the dust emission schemes used in aerosol transport models. Thirty-five dust events were identified in the source region during March and April of 2001 and characterized on a case-by-case basis. The midrange transport routes were reconstructed on the basis of visibility observations and observed and MM5-predicted winds with further validation against satellite data. We demonstrate that the combination of visibility data, TOMS aerosol index, MODIS aerosol optical depth over the land, and a qualitative analysis of MODIS and SeaWiFS imagery enables us to constrain the regions of origin of dust outbreaks and midrange transport, though various limitations of individual data sets were revealed in detecting dust over the land. Only two long-range transport episodes were found. The transport routes and coverage of these dust episodes were reconstructed by using MODIS aerosol optical depth and TOMS aerosol index. Our analysis reveals that over the oceans the presence of persistent clouds poses a main problem in identifying the regions affected by dust transport, so only partial reconstruction of dust transport routes reaching the west coast of the United States was possible.

Spatiotemporal Variability and Contribution of Different Aerosol Types to the Aerosol Optical Depth over the Eastern Mediterranean

NASA Technical Reports Server (NTRS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Poeschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1deg × 0.1deg gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is approx. 0.22 +/- 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for approx. 51, approx. 34 and approx. 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account approx. 40, approx. 34 and approx. 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

Synergistic use of MODIS cloud products and AIRS radiance measurements for retrieval of cloud parameters

NASA Astrophysics Data System (ADS)

Li, J.; Menzel, W.; Sun, F.; Schmit, T.

2003-12-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS) Aqua satellite will enable global monitoring of the distribution of clouds. MODIS is able to provide at high spatial resolution (1 ~ 5km) the cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud water path (CWP). AIRS is able to provide CTP, ECA, CPS, and CWP within the AIRS footprint with much better accuracy using its greatly enhanced hyperspectral remote sensing capability. The combined MODIS / AIRS system offers the opportunity for cloud products improved over those possible from either system alone. The algorithm developed was applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS cloud products, as well as with the Geostationary Operational Environmental Satellite (GOES) sounder cloud products, to demonstrate the advantage of synergistic use of high spatial resolution MODIS cloud products and high spectral resolution AIRS sounder radiance measurements for optimal cloud retrieval. Data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma were used for the validation; results show that AIRS improves the MODIS cloud products in certain cases such as low-level clouds.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content.

PubMed

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-27

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness ( τ ), effective radius ( r eff ), and cloud-top height ( h ). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

A Cut in the Clouds

NASA Image and Video Library

2017-12-08

Like a ship carving its way through the sea, the South Georgia and South Sandwich Islands parted the clouds. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image on February 2, 2017. The ripples in the clouds are known as gravity waves. NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response #nasagoddard

Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection, Journal of Applied Remote Sensing Vol.3

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu

2009-01-01

In the southeastern United States, most wildland fires are of low intensity. A substantial number of these fires cannot be detected by the MODIS contextual algorithm. To improve the accuracy of fire detection for this region, the remote-sensed characteristics of these fires have to be...

A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Chatterjee, Abhishek; Michalak, Anna M.; Kahn, Ralph A.; Paradise, Susan R.; Braverman, Amy J.; Miller, Charles E.

2010-01-01

Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling of the varying AOD. These results demonstrate how the MISR and MODIS aerosol products are complementary. The underlying technique also provides one method for combining these products in such a way that takes advantage of the strengths of each, in the places and times when they are maximal, and in addition, yields an estimate of the associated uncertainties in space and time.

Use of In Situ and Airborne Multiangle Data to Assess MODIS- and Landsat-based Estimates of Surface Albedo

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Shuai, Yanmin; Wang, Zhuosen; Gao, Feng; Masek, Jeff; Schaaf, Crystal B.

2012-01-01

The quantification of uncertainty of global surface albedo data and products is a critical part of producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A current challenge in validating satellite retrievals of surface albedo is the ability to overcome the spatial scaling errors that can contribute on the order of 20% disagreement between satellite and field-measured values. Here, we present the results from an uncertain ty analysis of MODerate Resolution Imaging Spectroradiometer (MODIS) and Landsat albedo retrievals, based on collocated comparisons with tower and airborne multi-angular measurements collected at the Atmospheric Radiation Measurement Program s (ARM) Cloud and Radiation Testbed (CART) site during the 2007 Cloud and Land Surface Interaction Campaign (CLAS33 IC 07). Using standard error propagation techniques, airborne measurements obtained by NASA s Cloud Absorption Radiometer (CAR) were used to quantify the uncertainties associated with MODIS and Landsat albedos across a broad range of mixed vegetation and structural types. Initial focus was on evaluating inter-sensor consistency through assessments of temporal stability, as well as examining the overall performance of satellite-derived albedos obtained at all diurnal solar zenith angles. In general, the accuracy of the MODIS and Landsat albedos remained under a 10% margin of error in the SW(0.3 - 5.0 m) domain. However, results reveal a high degree of variability in the RMSE (root mean square error) and bias of albedos in both the visible (0.3 - 0.7 m) and near-infrared (0.3 - 5.0 m) broadband channels; where, in some cases, retrieval uncertainties were found to be in excess of 20%. For the period of CLASIC 07, the primary factors that contributed to uncertainties in the satellite-derived albedo values include: (1) the assumption of temporal stability in the retrieval of 500 m MODIS BRDF values over extended periods of cloud-contaminated observations; and (2) the assumption of spatial 45 and structural uniformity at the Landsat (30 m) pixel scale.

Land Surface Microwave Emissivities Derived from AMSR-E and MODIS Measurements with Advanced Quality Control

NASA Technical Reports Server (NTRS)

Moncet, Jean-Luc; Liang, Pan; Galantowicz, John F.; Lipton, Alan E.; Uymin, Gennady; Prigent, Catherine; Grassotti, Christopher

2011-01-01

A microwave emissivity database has been developed with data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and with ancillary land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same Aqua spacecraft. The primary intended application of the database is to provide surface emissivity constraints in atmospheric and surface property retrieval or assimilation. An additional application is to serve as a dynamic indicator of land surface properties relevant to climate change monitoring. The precision of the emissivity data is estimated to be significantly better than in prior databases from other sensors due to the precise collocation with high-quality MODIS LST data and due to the quality control features of our data analysis system. The accuracy of the emissivities in deserts and semi-arid regions is enhanced by applying, in those regions, a version of the emissivity retrieval algorithm that accounts for the penetration of microwave radiation through dry soil with diurnally varying vertical temperature gradients. These results suggest that this penetration effect is more widespread and more significant to interpretation of passive microwave measurements than had been previously established. Emissivity coverage in areas where persistent cloudiness interferes with the availability of MODIS LST data is achieved using a classification-based method to spread emissivity data from less-cloudy areas that have similar microwave surface properties. Evaluations and analyses of the emissivity products over homogeneous snow-free areas are presented, including application to retrieval of soil temperature profiles. Spatial inhomogeneities are the largest in the vicinity of large water bodies due to the large water/land emissivity contrast and give rise to large apparent temporal variability in the retrieved emissivities when satellite footprint locations vary over time. This issue will be dealt with in the future by including a water fraction correction. Also note that current reliance on the MODIS day-night algorithm as a source of LST limits the coverage of the database in the Polar Regions. We will consider relaxing the current restriction as part of future development.

Validation of a Climate-Data Record of the "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Koenig, Lora S.; DiGirolamo, Nicolo E.; Comiso, Josefino C.; Shuman, Christopher A.

2011-01-01

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 since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR.

Reconstructed Solar-Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence

NASA Astrophysics Data System (ADS)

Gentine, P.; Alemohammad, S. H.

2018-04-01

Solar-induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment-2 (GOME-2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS-only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.

Stratifying Tropical Fires by Land Cover: Insights into Amazonian Fires, Aerosol Loading, and Regional Deforestation

NASA Technical Reports Server (NTRS)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

This study analyzes changes in the number of fires detected on forest, grass, and transition lands during the 2002-2009 biomass burning seasons using fire detection data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the total number of detected fires correlates well with MODIS mean aerosol optical depth (AOD) from year to year, in accord with other studies. However, we also show that the ratio of forest to savanna fires varies substantially from year to year. Forest fires have trended downward, on average, since the beginning of 2006 despite a modest increase in 2007. Our study suggests that high particulate matter loading detected in 2007 was likely due to a large number of savanna/agricultural fires that year. Finally, we illustrate that the correlation between annual Brazilian deforestation estimates and MODIS fires is considerably higher when fires are stratified by MODIS-derived land cover classifications.

Satellite Data Used to Combat Fires

NASA Technical Reports Server (NTRS)

2002-01-01

This visible light/infrared composite image over Montana and Idaho was acquired by the Moderate-resolution Imaging Spectroradiometer on Aug. 23, 2000. The image shows the locations of actively burning wildfires (red pixels) and the thick shroud of smoke they produced (grey-blue pixels). There were 57 wildfires burning across both states. A single MODIS image can be up to 2,330 kilometers wide, allowing fire scientists to monitor a much larger area than can be covered on the ground or by aircraft. Also, because MODIS has detectors that are sensitive to thermal infrared wavelengths of 3.70 and 3.90 micrometers, it can detect fires on the surface even through heavy smoke. For more information, see: NASA Satellite Data Used Operationally to Help Combat Fires in the West Image courtesy MODIS Science Team, Reto Stockli, and Robert Simmon.

Volcanic Activity at Shiveluch and Plosky Tolbachik

NASA Image and Video Library

2017-12-08

On March 7, 2013 the Terra satellite passed over eastern Russia, allowing the Moderate Resolution Imaging Spectroradiometer (MODIS) flying aboard to capture volcanic activity at Shiveluch and Plosky Tolbachik, on the Kamchatka Peninsula, in eastern Russia. This image was captured at 0050 UTC. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Fires in Chile

NASA Technical Reports Server (NTRS)

2002-01-01

On February 5, 2002, the dense smoke from numerous forest fires stretched out over the Pacific Ocean about 400 miles south of Santiago, Chile. This true-color Moderate-resolution Imaging Spectroradiometer (MODIS) image shows the fires, which are located near the city of Temuco. The fires are indicated with red dots (boxes in the high-resolution imagery). The fires were burning near several national parks and nature reserves in an area of the Chilean Andes where tourism is very popular. Southeast of the fires, the vegetation along the banks of the Rio Negro in Argentina stands out in dark green. Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

Typhoon Chataan off Japan

NASA Technical Reports Server (NTRS)

2002-01-01

Slowly winding its way down, Typhoon Chataan had dropped to tropical storm status by Thursday, July 11, 2002, when this image from the Moderate Resolution Imaging Spectroradiometer (MODIS) was captured. In the image, the storm is located off the east coast of central Japan in the Pacific Ocean. The storm is much less organized than it was in the previous day's image. Through a gap in the clouds to the southwest of the storm's eye, Tokyo can be seen as a grayish cluster of pixels surrounding a small bay or inlet that protrudes into the island of Honshu. Credit: Image courtesy Jesse Allen, NASA Earth Observatory; data provided by the MODIS Land Rapid Response Team

Intercomparison of 30+ years of AVHRR and Landsat-5 TM Surface Reflectance using Multiple Pseudo-Invariant Calibration Sites

NASA Astrophysics Data System (ADS)

Santamaría-Artigas, A. E.; Franch, B.; Vermote, E.; Roger, J. C.; Justice, C. O.

2017-12-01

The 30+ years daily surface reflectance long term data record (LTDR) from the Advanced Very High Resolution Radiometer (AVHRR) is a valuable source of information for long-term studies of the Earth surface. This LTDR was generated by combining observations from multiple AVHRR sensors aboard different NOAA satellites starting from the early 1980s, and due to the lack of on-board calibration its quality should be evaluated. Previous studies have used observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) over pseudo-invariant calibration sites (PICS) as a calibrated reference to assess the performance of AVHRR products. However, this limits the evaluation to the period after MODIS launch. In this work, the AVHRR surface reflectance LTDR was evaluated against Landsat-5 Thematic Mapper (TM) data using observations from 4 well known pseudo-invariant calibration sites (i.e. Sonoran, Saharan, Sudan1, and Libya4) over an extended time period (1984-2011). For the intercomparison, AVHRR and TM observations of each site were extracted and averaged over a 20 km x 20 km area and aggregated to monthly mean values. In order to account for the spectral differences between sensors, Hyperion hyperspectral data from the Sonoran and Libya4 sites were convolved with sensor-specific relative spectral responses, and used to compute spectral band adjustment factors (SBAFs). Results of the intercomparison are reported in terms of the root mean square difference (RMSD) and determination coefficient (r2). In general, there is good agreement between the surface reflectance products from both sensors. The overall RMSD and r2 for all the sites and AVHRR/TM combinations were 0.03 and 0.85 for the red band, and 0.04 and 0.81 for the near-infrared band. These results show the strong performance of the AVHRR surface reflectance LTDR through all of the considered period. Thus, remarking its usefulness and value for long term Earth studies. Figure 1 shows the red (filled markers) and near-infrared (empty markers) surface reflectance from AVHRR and TM for the complete evaluation period over the Saharan (diamond), Libya4 (square), Sudan1 (triangle), and Sonoran (circle) PICS.

The Effect of Spatial and Spectral Resolution in Determining NDVI

NASA Astrophysics Data System (ADS)

Boelman, N. T.

2003-12-01

We explore the impact that varying spatial and spectral resolutions of several sensors (a field portable spectroradiometer, Landsat, MODIS and AVHRR) has in determining the average Normalized Difference Vegetation Index (NDVI) at Imnavait Creek, a small arctic tundra watershed located on the north slope of Alaska. We found that at the field-of-views (FOVs) of less than 20 m2 that were sampled, the average NDVI value for this watershed is 0.65, compared to 0.77 at FOVs equal to and greater than 20 m2. In addition, we found that at FOVs less than 20 m2, the average NDVI value calculated according to each of Landsat, MODIS and AVHRR band definitions (controlled by spectral resolution) was similar. However, at FOVs equal to and greater than 20 m2, the average NDVI value calculated according to AVHRR's broad-band definitions was significantly and consistently higher than that from both Landsat and MODIS's narrow-band NDVI values. We speculate that these differences in NDVI exist because high leaf-area-index vegetation communities associated with watertracks are commonly spaced between 10 and 20 m apart in arctic tundra landscapes and are often only included when spectral sampling is conducted at FOVs greater than tens of square meters. These results suggest that both spatial resolution alone and its interaction with spectral resolution have to be considered when interpreting commonly used global-scale NDVI datasets. This is because traditionally, the fundamental relationships established between NDVI and ecosystem parameters, such as CO2 fluxes, aboveground biomass and net primary productivity, have been established at scales less than 20 m2. Other ecosystems, such as landscapes with isolated tree islands in boreal forest-tundra ecotones, may exhibit similar scaling patterns that need to be considered when interpreting global-scale NDVI datasets.

How Well Will MODIS Measure Top of Atmosphere Aerosol Direct Radiative Forcing?

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.; Levin, Zev; Ghan, Stephen; Einaudi, Franco (Technical Monitor)

2000-01-01

The new generation of satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) will be able to detect and characterize global aerosols with an unprecedented accuracy. The question remains whether this accuracy will be sufficient to narrow the uncertainties in our estimates of aerosol radiative forcing at the top of the atmosphere. Satellite remote sensing detects aerosol optical thickness with the least amount of relative error when aerosol loading is high. Satellites are less effective when aerosol loading is low. We use the monthly mean results of two global aerosol transport models to simulate the spatial distribution of smoke aerosol in the Southern Hemisphere during the tropical biomass burning season. This spatial distribution allows us to determine that 87-94% of the smoke aerosol forcing at the top of the atmosphere occurs in grid squares with sufficient signal to noise ratio to be detectable from space. The uncertainty of quantifying the smoke aerosol forcing in the Southern Hemisphere depends on the uncertainty introduced by errors in estimating the background aerosol, errors resulting from uncertainties in surface properties and errors resulting from uncertainties in assumptions of aerosol properties. These three errors combine to give overall uncertainties of 1.5 to 2.2 Wm-2 (21-56%) in determining the Southern Hemisphere smoke aerosol forcing at the top of the atmosphere. The range of values depend on which estimate of MODIS retrieval uncertainty is used, either the theoretical calculation (upper bound) or the empirical estimate (lower bound). Strategies that use the satellite data to derive flux directly or use the data in conjunction with ground-based remote sensing and aerosol transport models can reduce these uncertainties.

Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, Nai-Yung Christina; Sayer, Andrew Mark; Bettenhausen, Corey

2013-01-01

A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 µm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.

Assessment of Global Carbon Dioxide Concentration Using MODIS and GOSAT Data

PubMed Central

Guo, Meng; Wang, Xiufeng; Li, Jing; Yi, Kunpeng; Zhong, Guosheng; Tani, Hiroshi

2012-01-01

Carbon dioxide (CO2) is the most important greenhouse gas (GHG) in the atmosphere and is the greatest contributor to global warming. CO2 concentration data are usually obtained from ground observation stations or from a small number of satellites. Because of the limited number of observations and the short time series of satellite data, it is difficult to monitor CO2 concentrations on regional or global scales for a long time. The use of the remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) or Moderate Resolution Imaging Spectroradiometer (MODIS) data can overcome these problems, particularly in areas with low densities of CO2 concentration watch stations. A model based on temperature (MOD11C3), vegetation cover (MOD13C2 and MOD15A2) and productivity (MOD17A2) of MODIS (which we have named the TVP model) was developed in the current study to assess CO2 concentrations on a global scale. We assumed that CO2 concentration from the Thermal And Near infrared Sensor for carbon Observation (TANSO) aboard the Greenhouse gases Observing SATellite (GOSAT) are the true values and we used these values to check the TVP model accuracy. The results indicate that the accuracy of the TVP model is different in different continents: the greatest Pearson’s correlation coefficient (R2) was 0.75 in Eurasia (RMSE = 1.16) and South America (RMSE = 1.17); the lowest R2 was 0.57 in Australia (RMSE = 0.73). Compared with the TANSO-observed CO2 concentration (XCO2), we found that the accuracy throughout the World is between −2.56∼3.14 ppm. Potential sources of TVP model uncertainties were also analyzed and identified. PMID:23443383

A novel method for characterizing harmful algal blooms in the Persian Gulf using MODIS measurements

NASA Astrophysics Data System (ADS)

Ghanea, Mohsen; Moradi, Masoud; Kabiri, Keivan

2016-10-01

Biophysical properties of water undergo meaningful variations under red tide (RT) outbreak. A massive Cochlodinium polykrikoids RT began in the eastern Persian Gulf (PG) in October 2008 and extended to the northern PG in December 2008. It killed large fish and hampered marine industries and water desalination appliances. Yet monthly averages of satellite-derived Chl-a (Chlorophyll-a), nFLH (normalized Fluorescence Line Height), and Kd490 (diffuse attenuation coefficient at 490 nm) have not been compared in the PG. MODIS (MODerate Resolution Imaging Spectroradiometer) sensor provides global coverage, with short revisit time, and accessible, well validated ocean color products. This study compares the behavior of MODIS Chl-a, nFLH, and Kd490 in both normal and RT conditions. In doing so, their color maps are shown during normal and RT periods. Then, monthly variations of these products are shown as time-series between 2002 and 2008. HOCI (Hybrid Ocean Color Index) is defined by integrating these products to detect RT affected areas. The results gained from 100 locations in the PG show that HOCI >0.18 mW cm-2 μm-1 sr-1 mg m-4 and nFLH >0.04 mW cm-2 μm-1 sr-1 discriminates non-bloom waters from algal blooms. Rrs(443)/Rrs(412) > 1 is a proper statement to separate Trichodesmium erythtraeum from Noctiluca millaris, Noctiluca scintillans, and diatoms. Rrs(667)/Rrs(443) > 1 can differentiate Cochlodinium polykrikoids from T. erythtraeum, N. millaris, N. scintillans, and diatoms as well. So, the combination of HOCI and Rrs(667)/Rrs(443) ratio is useful for detection and quantization of C. polykrikoids.

Time-series MODIS satellite and in-situ data for spatio-temporal distribution of aerosol pollution assessment over Bucharest metropolitan area

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.

2015-10-01

With the increasing industrialization and urbanization, especially in the metropolis regions, aerosol pollution has highly negative effects on environment. Urbanization is responsible of three major changes that may have impact on the urban atmosphere: replacement of the natural surfaces with buildings and impermeable pavements, heat of anthropogenic origin and air pollution. The importance of aerosols for radiative and atmospheric chemical processes is widely recognized. They can scatter and/or absorb solar radiation leading to changes of the radiation budget. Also, the so-called indirect effect of aerosols describes the cloud-aerosol interactions, which can modify the chemical and physical processes in the atmosphere. Their high spatial variability and short lifetime make spaceborne sensors especially well suited for their observation. Remote sensing is a key application in global-change science and urban climatology. Since the launch of the MODerate resolution Imaging Spectroradiometer (MODIS) there is detailed global aerosol information available, both over land and oceans The aerosol parameters can be measured directly in situ or derived from satellite remote sensing observations. All these methods are important and complementary. The objective of this work was to document the seasonal and inter-annual patterns of the aerosol pollution particulate matter in two size fractions (PM10 and PM2.5) loading and air quality index (AQI) over Bucharest metropolitan area in Romania based on in-situ and MODIS (Terra-Moderate Resolution Imaging Spectoradiometer) satellite time series data over 2010-2012 period. Accurate information of urban air pollution is required for environmental and health policy, but also to act as a basis for designing and stratifying future monitoring networks.

Prototype Global Burnt Area Algorithm Using a Multi-sensor Approach

NASA Astrophysics Data System (ADS)

López Saldaña, G.; Pereira, J.; Aires, F.

2013-05-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05Deg spatial resolution and is available for the 1981-1999 time period. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has been on orbit in the Terra platform since late 1999 and in Aqua since mid 2002; surface reflectance products, MYD09CMG and MOD09CMG, are available at 0.05Deg spatial resolution. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR and the aforementioned MODIS products, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for years 1998 to 2002, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

Development of a Low Cost Microcontroller-Enabled Handheld Sunphotometer and Comparison with NASA AERONET and MODIS

NASA Astrophysics Data System (ADS)

Krintz, I. A.; Ruble, W.; Sherman, J. P.

2017-12-01

Satellite-based measurements of aerosol optical depth (AOD), such as those made by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the TERRA and AQUA spacecraft, are often used in studies of aerosol direct radiative forcing (DRF) on regional to global scales due to daily near-global coverage. However, these measurements require validation by ground-based instrumentation, which is limited due to the cost of research-grade instrumentation. Furthermore, satellite-based AOD agreement with "ground-truth" instruments is weaker over mountainous regions (Levy et al., 2010). To aid in satellite validation, a low cost handheld sunphotometer has been developed which will be suitable for deployment to multiple sites to form a citizen science network as part of an upcoming proposal. A microcontroller, along with temperature and pressure sensors, has been included in this design to ease the process of taking measurements and transferring data for processing. Although LED-based sunphotometers have been used for a number of years (Brooks and Mims, 2001), this design uses filtered photodiodes which appear to have less of a temperature dependence. The interface has been designed to be intuitive to citizen scientists of all ages, nationalities, and backgrounds, so that deployment to primary schools and international sites will be as seamless as possible. Presented here is the instrument design, as well as initial results of a comparison with NASA Aerosol Robotic Network (AERONET) and MODIS-measured AOD. Future revisions to the instrument design, such as incorporation of surface-mount devices to cut down on circuit board size, will allow for an even smaller and more cost effective solution suitable for a global sunphotometer network.

Estimating Evaporative Fraction From Readily Obtainable Variables in Mangrove Forests of the Everglades, U.S.A.

NASA Technical Reports Server (NTRS)

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John; Barr, Jordan

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) the ratio of latent heat (LE; energy equivalent of evapotranspiration -ET-) to total available energy from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micro-meteorological and flux tower observations, or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature [T(sub s)] normalized difference vegetation index (NDVI)and daily maximum air temperature [T(sub a)]. The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using T(sub s) and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the T(sub s) from Landsat relative to the T(sub s) from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Estimating evaporative fraction from readily obtainable variables in mangrove forests of the Everglades, U.S.A.

USGS Publications Warehouse

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John W.; Barr, Jordan G.

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) – the ratio of latent heat (LE; energy equivalent of evapotranspiration –ET–) to total available energy – from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micrometeorological and flux tower observations or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature (Ts) normalized difference vegetation index (NDVI) and daily maximum air temperature (Ta). The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using Ts and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the Ts from Landsat relative to the Ts from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Tsunami Damage in Northwest Sumatra

NASA Technical Reports Server (NTRS)

2005-01-01

The island of Sumatra suffered from both the rumblings of the submarine earthquake and the tsunamis that were generated on December 26, 2004. Within minutes of the quake, the sea surged ashore, bringing destruction to the coasts of the northern Sumatra. This pair of images from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite shows the Aceh province of northern Sumatra, Indonesia, on December 17, 2004, before the quake (bottom), and on December 29, 2004 (top), three days after the catastrophe. Although MODIS was not specifically designed to make the very detailed observations that are usually necessary for mapping coastline changes, the sensor nevertheless observed obvious differences in the Sumatran coastline. On December 17, the green vegetation along the west coast appears to reach all the way to the sea, with only an occasional thin stretch of white that is likely sand. After the earthquake and tsunamis, the entire western coast is lined with a noticeable purplish-brown border. The brownish border could be deposited sand, or perhaps exposed soil that was stripped bare of vegetation when the large waves rushed ashore and then raced away. Another possibility is that parts of the coastline may have sunk as the sea floor near the plate boundary rose. On a moderate-resolution image such as this, the affected area may seem small, but each pixel in the full resolution image is 250 by 250 meters. In places the brown strip reaches inland roughly 13 pixels, equal to a distance of 3.25 kilometers, or about 2 miles. On the northern tip of the island (shown in the large image), the incursion is even larger. NASA images created by Jesse Allen, Earth Observatory, using data obtained from the MODIS Rapid Response team and the Goddard Earth Sciences DAAC.

Assessment of global carbon dioxide concentration using MODIS and GOSAT data.

PubMed

Guo, Meng; Wang, Xiufeng; Li, Jing; Yi, Kunpeng; Zhong, Guosheng; Tani, Hiroshi

2012-11-26

Carbon dioxide (CO(2)) is the most important greenhouse gas (GHG) in the atmosphere and is the greatest contributor to global warming. CO(2) concentration data are usually obtained from ground observation stations or from a small number of satellites. Because of the limited number of observations and the short time series of satellite data, it is difficult to monitor CO(2) concentrations on regional or global scales for a long time. The use of the remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) or Moderate Resolution Imaging Spectroradiometer (MODIS) data can overcome these problems, particularly in areas with low densities of CO(2) concentration watch stations. A model based on temperature (MOD11C3), vegetation cover (MOD13C2 and MOD15A2) and productivity (MOD17A2) of MODIS (which we have named the TVP model) was developed in the current study to assess CO(2) concentrations on a global scale. We assumed that CO(2) concentration from the Thermal And Near infrared Sensor for carbon Observation (TANSO) aboard the Greenhouse gases Observing SATellite (GOSAT) are the true values and we used these values to check the TVP model accuracy. The results indicate that the accuracy of the TVP model is different in different continents: the greatest Pearson's correlation coefficient (R2) was 0.75 in Eurasia (RMSE = 1.16) and South America (RMSE = 1.17); the lowest R2 was 0.57 in Australia (RMSE = 0.73). Compared with the TANSO-observed CO(2) concentration (XCO(2)), we found that the accuracy throughout the World is between -2.56~3.14 ppm. Potential sources of TVP model uncertainties were also analyzed and identified.

A new bio-optical algorithm for the remote sensing of algal blooms in complex ocean waters

NASA Astrophysics Data System (ADS)

Shanmugam, Palanisamy

2011-04-01

A new bio-optical algorithm has been developed to provide accurate assessments of chlorophyll a (Chl a) concentration for detection and mapping of algal blooms from satellite data in optically complex waters, where the presence of suspended sediments and dissolved substances can interfere with phytoplankton signal and thus confound conventional band ratio algorithms. A global data set of concurrent measurements of pigment concentration and radiometric reflectance was compiled and used to develop this algorithm that uses the normalized water-leaving radiance ratios along with an algal bloom index (ABI) between three visible bands to determine Chl a concentrations. The algorithm is derived using Sea-viewing Wide Field-of-view Sensor bands, and it is subsequently tuned to be applicable to Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua data. When compared with large in situ data sets and satellite matchups in a variety of coastal and ocean waters the present algorithm makes good retrievals of the Chl a concentration and shows statistically significant improvement over current global algorithms (e.g., OC3 and OC4v4). An examination of the performance of these algorithms on several MODIS/Aqua images in complex waters of the Arabian Sea and west Florida shelf shows that the new algorithm provides a better means for detecting and differentiating algal blooms from other turbid features, whereas the OC3 algorithm has significant errors although yielding relatively consistent results in clear waters. These findings imply that, provided that an accurate atmospheric correction scheme is available to deal with complex waters, the current MODIS/Aqua, MERIS and OCM data could be extensively used for quantitative and operational monitoring of algal blooms in various regional and global waters.

Satellite retrievals of dust aerosol over the Red Sea and the Persian Gulf (2005-2015)

NASA Astrophysics Data System (ADS)

Banks, Jamie R.; Brindley, Helen E.; Stenchikov, Georgiy; Schepanski, Kerstin

2017-03-01

The inter-annual variability of the dust aerosol presence over the Red Sea and the Persian Gulf is analysed over the period 2005-2015. Particular attention is paid to the variation in loading across the Red Sea, which has previously been shown to have a strong, seasonally dependent latitudinal gradient. Over the 11 years considered, the July mean 630 nm aerosol optical depth (AOD) derived from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) varies between 0.48 and 1.45 in the southern half of the Red Sea. In the north, the equivalent variation is between 0.22 and 0.66. The temporal and spatial pattern of variability captured by SEVIRI is also seen in AOD retrievals from the MODerate Imaging Spectroradiometer (MODIS), but there is a systematic offset between the two records. Comparisons of both sets of retrievals with ship- and land-based AERONET measurements show a high degree of correlation with biases of < 0.08. However, these comparisons typically only sample relatively low aerosol loadings. When both records are stratified by AOD retrievals from the Multi-angle Imaging SpectroRadiometer (MISR), opposing behaviour is revealed at high MISR AODs ( > 1), with offsets of +0.19 for MODIS and -0.06 for SEVIRI. Similar behaviour is also seen over the Persian Gulf. Analysis of the scattering angles at which retrievals from the SEVIRI and MODIS measurements are typically performed in these regions suggests that assumptions concerning particle sphericity may be responsible for the differences seen.

An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data

USGS Publications Warehouse

Tan, B.; Morisette, J.T.; Wolfe, R.E.; Gao, F.; Ederer, G.A.; Nightingale, J.; Pedelty, J.A.

2011-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates. ?? 2010 IEEE.

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

NASA Technical Reports Server (NTRS)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

USGS Publications Warehouse

Selkowitz, D.J.

2010-01-01

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000-2009.

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

PubMed Central

Noble, Stephen R.

2015-01-01

Abstract Vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however, MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability. PMID:27708990

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

DOE PAGES

Noble, Stephen R.; Hudson, James G.

2015-07-22

Here, vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however,more » MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability.« less

Coordinated Airborne, Spaceborne, and Ground-Based Measurements of Massive, Thick Aerosol Layers During the Dry Season in Southern Africa

NASA Technical Reports Server (NTRS)

Schmid, B.; Redemann, J.; Russell, P. B.; Hobbs, P. V.; Hlavka, D. L.; McGill, M. J.; Holben, B. N.; Welton, E. J.; Campbell, J.; Torres, O.;

A multi-sensor burned area algorithm for crop residue burning in northwestern India: validation and sources of error

NASA Astrophysics Data System (ADS)

Liu, T.; Marlier, M. E.; Karambelas, A. N.; Jain, M.; DeFries, R. S.

2017-12-01

A leading source of outdoor emissions in northwestern India comes from crop residue burning after the annual monsoon (kharif) and winter (rabi) crop harvests. Agricultural burned area, from which agricultural fire emissions are often derived, can be poorly quantified due to the mismatch between moderate-resolution satellite sensors and the relatively small size and short burn period of the fires. Many previous studies use the Global Fire Emissions Database (GFED), which is based on the Moderate Resolution Imaging Spectroradiometer (MODIS) burned area product MCD64A1, as an outdoor fires emissions dataset. Correction factors with MODIS active fire detections have previously attempted to account for small fires. We present a new burned area classification algorithm that leverages more frequent MODIS observations (500 m x 500 m) with higher spatial resolution Landsat (30 m x 30 m) observations. Our approach is based on two-tailed Normalized Burn Ratio (NBR) thresholds, abbreviated as ModL2T NBR, and results in an estimated 104 ± 55% higher burned area than GFEDv4.1s (version 4, MCD64A1 + small fires correction) in northwestern India during the 2003-2014 winter (October to November) burning seasons. Regional transport of winter fire emissions affect approximately 63 million people downwind. The general increase in burned area (+37% from 2003-2007 to 2008-2014) over the study period also correlates with increased mechanization (+58% in combine harvester usage from 2001-2002 to 2011-2012). Further, we find strong correlation between ModL2T NBR-derived burned area and results of an independent survey (r = 0.68) and previous studies (r = 0.92). Sources of error arise from small median landholding sizes (1-3 ha), heterogeneous spatial distribution of two dominant burning practices (partial and whole field), coarse spatio-temporal satellite resolution, cloud and haze cover, and limited Landsat scene availability. The burned area estimates of this study can be used to build a new agricultural fire emissions inventory to re-evaluate the contributions of winter agricultural fires to rural and urban air quality degradation.

Validation of a Climate-Data Record of the "Clear-Kky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Koenig, Lora S.; DiGirolamo, Nicolo E.; Comiso, Josefino C.; Shuman, Christopher A.

2011-01-01

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 since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR. The Greenland Ice Sheet 1ST CDR will be useful for monitoring surface-temperature trends and can be used as input or for validation of climate models. The CDR can be extended into the future using MODIS Terra, Aqua and NPOESS Preparatory Project Visible Infrared Imager Radiometer Suite (VII RS) data.

Monitoring the state of vegetation in Hungary using 15 years long MODIS Data

NASA Astrophysics Data System (ADS)

Kern, Anikó; Bognár, Péter; Pásztor, Szilárd; Barcza, Zoltán; Timár, Gábor; Lichtenberger, János; Ferencz, Csaba

2015-04-01

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 (MODIS) sensor onboard the NASA EOS-AM1/Terra and EOS-PM1/Aqua satellites (since 1999 and 2002 respectively). Based on the available, 15 years long MODIS data (2000-2014) the vegetation characteristics of Hungary was investigated in our research, primarily using vegetation indices. The MODIS 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 Aqua respectively). The accuracy, the spatial resolution and temporal continuity of the MODIS products makes these datasets highly valuable despite of its relatively short temporal coverage. NDVI is also calculated routinely from the raw MODIS 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 emphasis on drought and heat waves. Te relationship between anomalies of vegetation characteristics and crop yield decrease in agricultural regions were characterised as well. The mean NDVI values of Hungary during the 15 years reveal the behaviour of the vegetation in the country, where the main land cover types (forest, agriculture and grassland) were distinguished as well. NDVI anomalies are analyzed separately for the main land cover types. Deviations from the potential maximum vegetation greenness are also calculated for the entire time period.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noble, Stephen R.; Hudson, James G.

Here, vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however,more » MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability.« less

Validation of MODIS aerosol optical depth product over China using CARSNET measurements

NASA Astrophysics Data System (ADS)

Xie, Yong; Zhang, Yan; Xiong, Xiaoxiong; Qu, John J.; Che, Huizheng

2011-10-01

This study evaluates Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) retrievals with ground measurements collected by the China Aerosol Remote Sensing NETwork (CARSNET). In current stage, the MODIS Collection 5 (C5) AODs are retrieved by two distinct algorithms: the Dark Target (DT) and the Deep Blue (DB). The CARSNET AODs are derived with measurements of Cimel Electronique CE-318, the same instrument deployed by the AEROsol Robotic Network (AEROENT). The collocation is performed by matching each MODIS AOD pixel (10 × 10 km 2) to CARSNET AOD mean within 7.5 min of satellite overpass. Four-year comparisons (2005-2008) of MODIS/CARSNET at ten sites show the performance of MODIS AOD retrieval is highly dependent on the underlying land surface. The MODIS DT AODs are on average lower than the CARSNET AODs by 6-30% over forest and grassland areas, but can be higher by up to 54% over urban area and 95% over desert-like area. More than 50% of the MODIS DT AODs fall within the expected error envelope over forest and grassland areas. The MODIS DT tends to overestimate for small AOD at urban area. At high vegetated area it underestimates for small AOD and overestimates for large AOD. Generally, its quality reduces with the decreasing AOD value. The MODIS DB is capable of retrieving AOD over desert but with a significant underestimation at CARSNET sites. The best retrieval of the MODIS DB is over grassland area with about 70% retrievals within the expected error. The uncertainties of MODIS AOD retrieval from spatial-temporal collocation and instrument calibration are discussed briefly.

Top-down estimates of biomass burning emissions of black carbon in the western United States

Treesearch

Y. H. Mao; Q. B. Li; D. Chen; L. Zhang; W. -M. Hao; K.-N. Liou

2014-01-01

We estimate biomass burning and anthropogenic emissions of black carbon (BC) in the western US for May-October 2006 by inverting surface BC concentrations from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using a global chemical transport model. We first use active fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS...

Accuracy assessment of the vegetation continuous field tree cover product using 3954 ground plots in the southwestern USA

Treesearch

M. A. White; J. D. Shaw; R. D. Ramsey

2005-01-01

An accuracy assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field (VCF) tree cover product using two independent ground-based tree cover databases was conducted. Ground data included 1176 Forest Inventory and Analysis (FIA) plots for Arizona and 2778 Southwest Regional GAP (SWReGAP) plots for Utah and western Colorado....

Geospatiotemporal data mining in an early warning system for forest threats in the United States

Treesearch

F.M. Hoffman; R.T. Mills; J. Kumar; S.S. Vulli; W.W. Hargrove

2010-01-01

We investigate the potential of geospatiotemporal data mining of multi-year land surface phenology data (250 m Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study) for the conterminous United States as part of an early warning system to identify threats to forest ecosystems. Cluster...

Calibration Challenges and Improvements for Terra and Aqua MODIS Level-1B Data Product Qualit

NASA Astrophysics Data System (ADS)

Xiong, X.; Angal, A.; Chen, H.; Geng, X.; Li, Y.; Link, D.; Salomonson, V.; Twedt, K.; Wang, Z.; Wilson, T.; Wu, A.

2017-12-01

Terra and Aqua MODIS instruments launched in 1999 and 2002, respectively, have provided the remote sensing community and users worldwide a series of high quality long-term data records. They have enabled a broad range of scientific studies of the Earth's system and changes in its key geophysical and environmental parameters. To date, both MODIS instruments continue to operate nominally with all on-board calibrators (OBC) functioning properly. MODIS reflective solar bands (RSB) are currently calibrated by a solar diffuser (SD) and solar diffuser stability monitor (SDSM) system, coupled with regularly scheduled lunar observations and trending results from selected ground reference targets. The thermal emissive bands (TEB) calibration is performed using an on-board blackbody (BB) on a scan-by-scan basis. The sensor's spectral and spatial characteristics are periodically tracked by the on-board spectroradiometric calibration assembly (SRCA). On-orbit changes in sensor responses or performance characteristics, often in non-deterministic ways, underscore the need for dedicated calibration efforts to be made over the course of the sensor's entire mission. For MODIS instruments, this task has been undertaken by the MODIS Characterization Support Team (MCST). In this presentation, we provide an overview of MODIS instrument operation and calibration activities with a focus on recent challenging issues. We describe the efforts made and methodologies developed to address various challenging issues, including on-orbit characterization of sensor response versus scan angle (RVS) and polarization sensitives in the reflective solar spectral region, and electronic crosstalk impact on sensor calibration. Also discussed are the latest improvements made into the MODIS Level-1B data products as well as lessons that could benefit other instruments (e.g. VIIRS) for their on-orbit calibration and characterization.

Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes.

PubMed

Prasad, Dilip K; Agarwal, Krishna

2016-03-22

We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds). The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS), moderate-resolution imaging spectroradiometer (MODIS), sea-viewing wide field-of-view sensor (SeaWiFS), coastal zone color scanner (CZCS), ocean and land colour instrument (OLCI), and visible infrared imaging radiometer suite (VIIRS) sensors. Results are also shown for CIMEL's SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

Assessment of the short-term radiometric stability between Terra MODIS and Landsat 7 ETM+ sensors

USGS Publications Warehouse

Choi, Taeyoung; Xiong, Xiaoxiong; Chander, Gyanesh; Angal, A.

2009-01-01

Short-term radiometric stability was evaluated using continuous ETM+ scenes within a single orbit (contact period) and the corresponding MODIS scenes for the four matching solar reflective visible and near-infrared (VNIR) band pairs between the two sensors. The near-simultaneous earth observations were limited by the smaller swath size of ETM+ (183 km) compared to MODIS (2330 km). Two sets of continuous granules for Terra MODIS and Landsat 7 ETM+ were selected and mosaicked based on pixel geolocation information for noncloudy pixels over the African continent. The matching pixel pairs were resampled from a fine to a coarse pixel resolution, and the at-sensor spectral radiance values for a wide dynamic range of the sensors were compared and analyzed, covering various surface types. The following study focuses on radiometric stability analysis from the VNIR band-pairs of ETM+ and MODIS. The Libya-4 desert target was included in the path of this continuous orbit, which served as a verification point between the short-term and the long-term trending results from previous studies. MODTRAN at-sensor spectral radiance simulation is included for a representative desert surface type to evaluate the consistency of the results.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS 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 micrometers 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 I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions

PubMed Central

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-01-01

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions. PMID:24811079

Multispectral Cloud Retrievals from MODIS on Terra and Aqua

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each 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). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS 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 (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

PubMed

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-05-07

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

NASA Technical Reports Server (NTRS)

Li, Yonghong; Angal, Amit; Wu, Aisheng; Geng, Xu; Link, Daniel; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

MODIS Views the Middle-East

NASA Technical Reports Server (NTRS)

2002-01-01

To paraphrase English author T.H. White, borders are the one thing a man sees that a bird cannot see as it flies high overhead. For the 15th consecutive day, differences in ideology have sparked violence and tension in the middle-east as the rest of the world watches, concerned. This true-color image of the region was taken on September 10, 2000, by the MODerate-resolution Imaging Spectroradiometer (MODIS) flying aboard NASA's Terra spacecraft. The image shows the lands of Israel along the eastern shore of the Mediterranean Sea, with the countries of Jordan to the southeast and Syria to the Northeast. Jerusalem, labeled, is Israel's capital city and Aman, labeled, is the capital of Jordan. The region known as the West Bank lies between the two countries. Running from north to south, the Jordan River links the Sea of Galilee to the Dead Sea. Image courtesy Jacques Descloitres, MODIS Land Group, NASA GSFC

Greenland Ice Sheet Melt from MODIS and Associated Atmospheric Variability

NASA Technical Reports Server (NTRS)

Hakkinen, Sirpa; Hall, Dorothy K.; Shuman, Christopher A.; Worthen, Denise L.; DiGirolamo, Nicolo E.

2014-01-01

Daily June-July melt fraction variations over the Greenland Ice Sheet (GIS) derived from the MODerate-resolution Imaging Spectroradiometer (MODIS) (2000-2013) are associated with atmospheric blocking forming an omega-shape ridge over the GIS at 500hPa height (from NCEPNCAR). Blocking activity with a range of time scales, from synoptic waves breaking poleward ( 5 days) to full-fledged blocks (5 days), brings warm subtropical air masses over the GIS controlling daily surface temperatures and melt. The temperature anomaly of these subtropical air mass intrusions is also important for melting. Based on the largest MODIS melt years (2002 and 2012), the area-average temperature anomaly of 2 standard deviations above the 14-year June-July mean, results in a melt fraction of 40 or more. Summer 2007 had the most blocking days, however atmospheric temperature anomalies were too small to instigate extreme melting.

Flooding in Central China

NASA Technical Reports Server (NTRS)

2002-01-01

During the summer of 2002, frequent, heavy rains gave rise to floods and landslides throughout China that have killed over 1,000 people and affected millions. This false-color image of the western Yangtze River and Dongting Lake in central China was acquired on August 21, 2002, by the Moderate-resolution Imaging Spectroradiometer (MODIS), flying aboard NASA's Terra spacecraft. (right) The latest flooding crisis in China centers on Dingtong Lake in the center of the image. Heavy rains have caused it to swell over its banks and swamp lakefront towns in the province of Hunan. As of August 23, 2002, more than 250,000 people have been evacuated, and over one million people have been brought in to fortify the dikes around the lake. Normally the lake would appear much smaller and more defined in the MODIS image. Credit: Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC.

Validation of MODIS Aerosol Optical Depth Retrieval Over Land

NASA Technical Reports Server (NTRS)

Chu, D. A.; Kaufman, Y. J.; Ichoku, C.; Remer, L. A.; Tanre, D.; Holben, B. N.; Einaudi, Franco (Technical Monitor)

2001-01-01

Aerosol optical depths are derived operationally for the first time over land in the visible wavelengths by MODIS (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 reflectance. The excellent fit was achieved despite the ongoing improvements in instrument characterization and calibration. This results show that MODIS-derived aerosol optical depths can be used quantitatively in many applications with cautions for residual clouds, snow/ice, and water contamination.

A Simple Technique for Creating Regional Composites of Sea Surface Temperature from MODIS for Use in Operational Mesoscale NWP

NASA Technical Reports Server (NTRS)

Knievel, Jason C.; Rife, Daran L.; Grim, Joseph A.; Hahmann, Andrea N.; Hacker, Joshua P.; Ge, Ming; Fisher, Henry H.

2010-01-01

This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) for use in operational numerical weather prediction (NWP). The composites are based on observations from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra. The data used typically are available nearly in real time, are applicable anywhere on the globe, and are capable of roughly representing the diurnal cycle in SST. The composites resolution is much higher than that of many other standard SST products used for operational NWP, including the low- and high-resolution Real-Time Global (RTG) analyses. The difference in resolution is key because several studies have shown that highly resolved SSTs are important for driving the air sea interactions that shape patterns of static stability, vertical and horizontal wind shear, and divergence in the planetary boundary layer. The MODIS-based composites are compared to in situ observations from buoys and other platforms operated by the National Data Buoy Center (NDBC) off the coasts of New England, the mid-Atlantic, and Florida. Mean differences, mean absolute differences, and root-mean-square differences between the composites and the NDBC observations are all within tenths of a degree of those calculated between RTG analyses and the NDBC observations. This is true whether or not one accounts for the mean offset between the skin temperatures of the MODIS dataset and the bulk temperatures of the NDBC observations and RTG analyses. Near the coast, the MODIS-based composites tend to agree more with NDBC observations than do the RTG analyses. The opposite is true away from the coast. All of these differences in point-wise comparisons among the SST datasets are small compared to the 61.08C accuracy of the NDBC SST sensors. Because skin-temperature variations from land to water so strongly affect the development and life cycle of the sea breeze, this phenomenon was chosen for demonstrating the use of the MODIS-based composite in an NWP model. A simulated sea breeze in the vicinity of New York City and Long Island shows a small, net, but far from universal improvement when MODIS-based composites are used in place of RTG analyses. The timing of the sea breeze s arrival is more accurate at some stations, and the near-surface temperature, wind, and humidity within the breeze are more realistic.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content

PubMed Central

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2018-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available. PMID:29707470

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nikolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

2012-01-01

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

Discrepancy Between ASTER- and MODIS- Derived Land Surface Temperatures: Terrain Effects

PubMed Central

Liu, Yuanbo; Noumi, Yousuke; Yamaguchi, Yasushi

2009-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) are onboard the same satellite platform NASA TERRA. Both MODIS and ASTER offer routine retrieval of land surface temperatures (LSTs), and the ASTER- and MODIS-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 MODIS 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-MODIS emissivity suggested that the terrain correction was included in the generalized split window (GSW) based approach used to rectify MODIS LSTs. Further study should include the classification-induced uncertainty in emissivity for reliable use of satellite-retrieved LSTs over relief areas. PMID:22399955

MODIS Global Sea Surface Temperature

NASA Technical Reports Server (NTRS)

2002-01-01

Every day the Moderate-resolution Imaging Spectroradiometer (MODIS) 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 MODIS 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. MODIS was launched in December 1999 aboard NASA's Terra satellite. For more details on this and other MODIS data products, please see NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Ocean Group, NASA GSFC, and the University of Miami

MODIS Snow and Ice Products from the NSIDC DAAC

NASA Technical Reports Server (NTRS)

Scharfen, Greg R.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized.

A Technique for Remote Sensing of Suspended Sediments and Shallow Coastal Waters Using MODIS Visible and Near-IR Channels

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram J.

2002-01-01

We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (MODIS). The MODIS instruments on board the NASA Terra and Aqua 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 MODIS channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. 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. MODIS 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.

Clear-sky narrowband albedos derived from VIRS and MODIS

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Arduini, Robert F.

2004-02-01

The Clouds and Earth"s Radiant Energy System (CERES) project is using multispectral imagers, the Visible Infrared Scanner (VIRS) on the tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra, operating since spring 2000, and Aqua, operating since summer 2002, to provide cloud and clear-sky properties at various wavelengths. This paper presents the preliminary results of an analysis of the CERES clear-sky reflectances to derive a set top-of-atmosphere clear sky albedo for 0.65, 0.86, 1.6, 2.13 μm, for all major surface types using the combined MODIS and VIRS datasets. The variability of snow albedo with surface type is examined using MODIS data. Snow albedo was found to depend on the vertical structure of the vegetation. At visible wavelengths, it is least for forested areas and greatest for smooth desert and tundra surfaces. At 1.6 and 2.1-μm, the snow albedos are relatively insensitive to the underlying surface because snow decreases the reflectance. Additional analyses using all of the MODIS results will provide albedo models that should be valuable for many remote sensing, simulation and radiation budget studies.

A Technique For Remote Sensing Of Suspended Sediments And Shallow Coastal Waters Using MODIS Visible and Near-IR Channels

NASA Astrophysics Data System (ADS)

Li, R.; Kaufman, Y.

2002-12-01

ABSTRACT We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (MODIS). The MODIS instruments on board the NASA Terra and Aqua 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 MODIS channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 æm that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS 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.

Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS

NASA Astrophysics Data System (ADS)

Hong, Gi Hoon; Yang, Dong Beom; Lee, Hyun-Mi; Yang, Sung Ryull; Chung, Hee Woon; Kim, Chang Joon; Kim, Young-Il; Chung, Chang Soo; Ahn, Yu-Hwan; Park, Young-Je; Moon, Jeong-Eon

2012-09-01

Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.

MODIS Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

2002-01-01

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 MODIS 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. MODIS 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). MODIS 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 MODIS Science Teams. MODIS/Terra Level 1, and all MODIS/Terra 11 micron SST products are announced as validated. At the time of this publication, the MODIS Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of MODIS/Terra Ocean products. MODIS/Aqua Level 1 and cloud mask products are released with provisional maturity.

Design, Development and Testing of Web Services for Multi-Sensor Snow Cover Mapping

NASA Astrophysics Data System (ADS)

Kadlec, Jiri

This dissertation presents the design, development and validation of new data integration methods for mapping the extent of snow cover based on open access ground station measurements, remote sensing images, volunteer observer snow reports, and cross country ski track recordings from location-enabled mobile devices. The first step of the data integration procedure includes data discovery, data retrieval, and data quality control of snow observations at ground stations. The WaterML R package developed in this work enables hydrologists to retrieve and analyze data from multiple organizations that are listed in the Consortium of Universities for the Advancement of Hydrologic Sciences Inc (CUAHSI) Water Data Center catalog directly within the R statistical software environment. Using the WaterML R package is demonstrated by running an energy balance snowpack model in R with data inputs from CUAHSI, and by automating uploads of real time sensor observations to CUAHSI HydroServer. The second step of the procedure requires efficient access to multi-temporal remote sensing snow images. The Snow Inspector web application developed in this research enables the users to retrieve a time series of fractional snow cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) for any point on Earth. The time series retrieval method is based on automated data extraction from tile images provided by a Web Map Tile Service (WMTS). The average required time for retrieving 100 days of data using this technique is 5.4 seconds, which is significantly faster than other methods that require the download of large satellite image files. The presented data extraction technique and space-time visualization user interface can be used as a model for working with other multi-temporal hydrologic or climate data WMTS services. The third, final step of the data integration procedure is generating continuous daily snow cover maps. A custom inverse distance weighting method has been developed to combine volunteer snow reports, cross-country ski track reports and station measurements to fill cloud gaps in the MODIS snow cover product. The method is demonstrated by producing a continuous daily time step snow presence probability map dataset for the Czech Republic region. The ability of the presented methodology to reconstruct MODIS snow cover under cloud is validated by simulating cloud cover datasets and comparing estimated snow cover to actual MODIS snow cover. The percent correctly classified indicator showed accuracy between 80 and 90% using this method. Using crowdsourcing data (volunteer snow reports and ski tracks) improves the map accuracy by 0.7--1.2%. The output snow probability map data sets are published online using web applications and web services. Keywords: crowdsourcing, image analysis, interpolation, MODIS, R statistical software, snow cover, snowpack probability, Tethys platform, time series, WaterML, web services, winter sports.

Navy Exploitation of SeaWiFS and MODIS Satellite Imagery for Detection of Desert Dust Storms Over Land and Water

NASA Astrophysics Data System (ADS)

Miller, S. D.

2002-12-01

The United States Navy gives serious consideration to the subject of dust detection. In a recent study of Naval aviation mishaps over the period 1990-1998 (Cantu, 2001), it was found that 70% were associated with visibility problems and accounted for annual equipment losses of nearly 50 million dollars. This figure does not include the tax dollars lost in jettisoned or off-target ordnance owing to obscured targets or failure of laser-guided systems in the presence of significant dust. Nor can it account for the loss of life during a subset of these mishaps. As such, a strong research emphasis has been placed on detecting and quantifying dust over data-sparse/denied parts of the world. The prolific and complex dust climatology of Southwest Asia has posed considerable challenges to Navy operations over the course of Operation Enduring Freedom. In an effort to support the ongoing needs of the Meteorology/Oceanography (METOC) officers afloat, the Satellite Applications Section of the Naval Research Laboratory (NRL) Marine Meteorology Division has developed a novel approach to enhancing significant dust events that appeals to high spatial and spectral resolution satellite data currently available from state of the art ocean/atmospheric radiometers. This paper summarizes progress made on daytime enhancements of desert dust storms over both land and ocean using multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS; aboard Earth Observing System Terra and Aqua platforms) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; aboard the NASA/Orbimage SeaStar platform). The approach leverages the multi-spectral visible capability of these sensors to distinguish dust from clouds over water bodies, and the high spatial resolution required to refine the fine-scale structures that often accompany these events. The MODIS algorithm combines this information with that of several near-to-far infrared channels, taking advantage of unique spectral properties of dust found in these regimes, to extend the capability to detection of dust over land (bright backgrounds). An account for enhancement contamination in the presence of sun glint is also provided in these products. The SeaWiFS and MODIS telemetries are made available to NRL in near real-time, with product turn-around ranging from 3-6 hours from initial capture. An unprecedented intra-agency collaboration forged between NOAA, NASA (Goddard Space Flight Center), and the Department of Defense has resulted in the recent availability of a global Terra MODIS data stream, with the companion Aqua telemetry soon to follow. Preliminary METOC feedback regarding these products has been overwhelmingly positive, and provides the impetus for continued refinement. Examples of the current product's capabilities and limitations will be presented.

Haze in central China

NASA Image and Video Library

2014-01-24

The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image of central China on January 23, 2013 at 04:05 UTC. The image shows extensive haze over the region. In areas where the ground is visible, some of the landscape is covered with lingering snow. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

MODIS Solar Diffuser: Modelled and Actual Performance

NASA Technical Reports Server (NTRS)

Waluschka, Eugene; Xiong, Xiao-Xiong; Esposito, Joe; Wang, Xin-Dong; Krebs, Carolyn (Technical Monitor)

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument's solar diffuser is used in its radiometric calibration for the reflective 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.

Using the OMI Aerosol Index and Absorption Aerosol Optical Depth to evaluate the NASA MERRA Aerosol Reanalysis

NASA Astrophysics Data System (ADS)

Buchard, V.; da Silva, A. M.; Colarco, P. R.; Darmenov, A.; Randles, C. A.; Govindaraju, R.; Torres, O.; Campbell, J.; Spurr, R.

2014-12-01

A radiative transfer interface has been developed to simulate the UV Aerosol Index (AI) from the NASA Goddard Earth Observing System version 5 (GEOS-5) aerosol assimilated fields. The purpose of this work is to use the AI and Aerosol Absorption Optical Depth (AAOD) derived from the Ozone Monitoring Instrument (OMI) measurements as independent validation for the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Since AI is dependent on aerosol concentration, optical properties and altitude of the aerosol layer, we make use of complementary observations to fully diagnose the model, including AOD from the Multi-angle Imaging SpectroRadiometer (MISR), aerosol retrievals from the Aerosol Robotic Network (AERONET) and attenuated backscatter coefficients from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission to ascertain potential misplacement of plume height by the model. By sampling dust, biomass burning and pollution events in 2007 we have compared model produced AI and AAOD with the corresponding OMI products, identifying regions where the model representation of absorbing aerosols was deficient. As a result of this study over the Saharan dust region, we have obtained a new set of dust aerosol optical properties that retains consistency with the MODIS AOD data that were assimilated, while resulting in better agreement with aerosol absorption measurements from OMI. The analysis conducted over the South African and South American biomass burning regions indicates that revising the spectrally-dependent aerosol absorption properties in the near-UV region improves the modeled-observed AI comparisons. Finally, during a period where the Asian region was mainly dominated by anthropogenic aerosols, we have performed a qualitative analysis in which the specification of anthropogenic emissions in GEOS-5 is adjusted to provide insight into discrepancies observed in AI comparisons.

Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis

NASA Astrophysics Data System (ADS)

Buchard, V.; da Silva, A. M.; Colarco, P. R.; Darmenov, A.; Randles, C. A.; Govindaraju, R.; Torres, O.; Campbell, J.; Spurr, R.

2015-05-01

A radiative transfer interface has been developed to simulate the UV aerosol index (AI) from the NASA Goddard Earth Observing System version 5 (GEOS-5) aerosol assimilated fields. The purpose of this work is to use the AI and aerosol absorption optical depth (AAOD) derived from the Ozone Monitoring Instrument (OMI) measurements as independent validation for the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Since AI is dependent on aerosol concentration, optical properties and altitude of the aerosol layer, we make use of complementary observations to fully diagnose the model, including AOD from the Multi-angle Imaging SpectroRadiometer (MISR), aerosol retrievals from the AErosol RObotic NETwork (AERONET) and attenuated backscatter coefficients from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission to ascertain potential misplacement of plume height by the model. By sampling dust, biomass burning and pollution events in 2007 we have compared model-produced AI and AAOD with the corresponding OMI products, identifying regions where the model representation of absorbing aerosols was deficient. As a result of this study over the Saharan dust region, we have obtained a new set of dust aerosol optical properties that retains consistency with the MODIS AOD data that were assimilated, while resulting in better agreement with aerosol absorption measurements from OMI. The analysis conducted over the southern African and South American biomass burning regions indicates that revising the spectrally dependent aerosol absorption properties in the near-UV region improves the modeled-observed AI comparisons. Finally, during a period where the Asian region was mainly dominated by anthropogenic aerosols, we have performed a qualitative analysis in which the specification of anthropogenic emissions in GEOS-5 is adjusted to provide insight into discrepancies observed in AI comparisons.

Validation of MODIS aerosol optical depth over the Mediterranean Coast

NASA Astrophysics Data System (ADS)

Díaz-Martínez, J. Vicente; Segura, Sara; Estellés, Víctor; Utrillas, M. Pilar; Martínez-Lozano, J. Antonio

2013-04-01

Atmospheric aerosols, due to their high spatial and temporal variability, are considered one of the largest sources of uncertainty in different processes affecting visibility, air quality, human health, and climate. Among their effects on climate, they play an important role in the energy balance of the Earth. On one hand they have a direct effect by scattering and absorbing solar radiation; on the other, they also have an impact in precipitation, modifying clouds, or affecting air quality. The application of remote sensing techniques to investigate aerosol effects on climate has advanced significatively over last years. In this work, the products employed have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a sensor located onboard both Earth Observing Systems (EOS) Terra and Aqua satellites, which provide almost complete global coverage every day. These satellites have been acquiring data since early 2000 (Terra) and mid 2002 (Aqua) and offer different products for land, ocean and atmosphere. Atmospheric aerosol products are presented as level 2 products with a pixel size of 10 x 10 km2 in nadir. MODIS aerosol optical depth (AOD) is retrieved by different algorithms depending on the pixel surface, distinguishing between land and ocean. For its validation, ground based sunphotometer data from AERONET (Aerosol Robotic Network) has been employed. AERONET is an international operative network of Cimel CE318 sky-sunphotometers that provides the most extensive aerosol data base globally available of ground-based measurements. The ground sunphotometric technique is considered the most accurate for the retrieval of radiative properties of aerosols in the atmospheric column. In this study we present a validation of MODIS C051 AOD employing AERONET measurements over different Mediterranean coastal sites centered over an area of 50 x 50 km2, which includes both pixels over land and ocean. The validation is done comparing spatial statistics from MODIS with corresponding temporal statistics from AERONET, as proposed by Ichoku et al. (2002). Eight Mediterranean coastal sites (in Spain, France, Italy, Crete, Turkey and Israel) with available AERONET and MODIS data have been used. These stations have been selected following QA criteria (minimum 1000 days of level 2.0 data) and a maximum distance of 8 km from the coast line. Results of the validation over each site show analogous behaviour, giving similar results regarding to the accuracy of the algorithms. Greatest differences are found for the AOD obtained over land, especially for drier regions, where the surface tends to be brighter. In general, the MODIS AOD has better a agreement with AERONET retrievals for the ocean algorithm than the land algorithm when validated over coastal sites, and the agreement is within the expected uncertainty estimated for MODIS data. References: - C. Ichoku et al., "A spatio-temporal approach for global validation and analysis of MODIS aerosol products", Geophysical Research Letters, 219, 12, 10.1029/2001GL013206, 2002.

Aerosol polarization effects on atmospheric correction and aerosol retrievals in ocean color remote sensing.

PubMed

Wang, Menghua

2006-12-10

The current ocean color data processing system for the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and the moderate resolution imaging spectroradiometer (MODIS) uses the Rayleigh lookup tables that were generated using the vector radiative transfer theory with inclusion of the polarization effects. The polarization effects, however, are not accounted for in the aerosol lookup tables for the ocean color data processing. I describe a study of the aerosol polarization effects on the atmospheric correction and aerosol retrieval algorithms in the ocean color remote sensing. Using an efficient method for the multiple vector radiative transfer computations, aerosol lookup tables that include polarization effects are generated. Simulations have been carried out to evaluate the aerosol polarization effects on the derived ocean color and aerosol products for all possible solar-sensor geometries and the various aerosol optical properties. Furthermore, the new aerosol lookup tables have been implemented in the SeaWiFS data processing system and extensively tested and evaluated with SeaWiFS regional and global measurements. Results show that in open oceans (maritime environment), the aerosol polarization effects on the ocean color and aerosol products are usually negligible, while there are some noticeable effects on the derived products in the coastal regions with nonmaritime aerosols.

MODIS Retrieval of Dust Aerosol

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.; Tanre, Didier

2003-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, operationally, on a nearly global basis every day. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations. However, the validation in regions dominated by desert dust is less accurate than in regions dominated by fine mode aerosol or background marine sea salt. The discrepancy is most apparent in retrievals of aerosol size parameters over ocean. In dust situations, the MODIS algorithm tends to under predict particle size because the reflectances at top of atmosphere measured by MODIS exhibit the stronger spectral signature expected by smaller particles. This pattern is consistent with the angular and spectral signature of non-spherical particles. All possible aerosol models in the MODIS Look-Up Tables were constructed from Mie theory, assuming a spherical shape. Using a combination of MODIS and AERONET observations, in regimes dominated by desert dust, we construct phase functions, empirically, with no assumption of particle shape. These new phase functions are introduced into the MODIS algorithm, in lieu of the original options for large dust-like particles. The results will be analyzed and examined.