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Sample records for aqua modis satellite

  1. Aqua satellite orbiting the Earth

    NASA Video Gallery

    This animation shows the Aqua satellite orbiting the Earth on August 27, 2005 by revealing MODIS true-color imagery for that day. This animation is on a cartesian map projection, so the satellite w...

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

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

    NASA Technical Reports Server (NTRS)

    King, Michael D.

    2005-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. 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.

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

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven

    2005-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    PubMed

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

    2015-04-01

    In situ datasets of nitrate, sea surface temperature (SST), and chlorophyll a (chl a) collected during the monthly coastal samplings and organized cruises along the Tamilnadu and Andhra Pradesh coast between 2009 and 2013 were used to develop seasonal nitrate algorithms. The nitrate algorithms have been built up based on the three-dimensional regressions between SST, chl a, and nitrate in situ data using linear, Gaussian, Lorentzian, and paraboloid function fittings. Among these four functions, paraboloid was found to be better with the highest co-efficient of determination (postmonsoon: R2=0.711, n=357; summer: R2=0.635, n=302; premonsoon: R2=0.829, n=249; and monsoon: R2=0.692, n=272) for all seasons. Based on these fittings, seasonal nitrate images were generated using the concurrent satellite data of SST from Moderate Resolution Imaging Spectroradiometer (MODIS) and chlorophyll (chl) from Ocean Color Monitor (OCM-2) and MODIS. The best retrieval of modeled nitrate (R2=0.527, root mean square error (RMSE)=3.72, and mean normalized bias (MNB)=0.821) was observed for the postmonsoon season due to the better retrieval of both SST MODIS (28 February 2012, R2=0.651, RMSE=2.037, and MNB=0.068) and chl OCM-2 (R2=0.534, RMSE=0.317, and MNB=0.27). Present results confirm that the chl OCM-2 and SST MODIS retrieve nitrate well than the MODIS-derived chl and SST largely due to the better retrieval of chl by OCM-2 than MODIS. PMID:25762424

  7. Trend Analysis of global AOT based on various Polar Orbiting Satellite Observations: MODIS (Terra), MISR (Terra), SeaWiFS (OrbView-2), and MODIS (Aqua)

    NASA Astrophysics Data System (ADS)

    Yoon, J.; Vountas, M.; von Hoyningen-Huene, W.; Chang, D. Y.; Burrows, J. P.

    2012-04-01

    Many studies have investigated temporal trends of cloud-free AOTs derived from polar orbiting satellite observations since aerosol retrieval accuracy has been improved substantially. However, only few studies have discussed the fundamental limitation of incomplete sampling originated from frequent cloud disturbance and restricted temporal coverage. Furthermore, the AOT trends derived from various polar orbiting satellite observations are hardly comparable due to different sensor calibration, retrieval accuracy, and cloud screening. Therefore, the present paper integrates various analyses of AOT trends derived from multiple observations (i.e. MODIS-Terra (MOD) from 2000/03 to 2009/12, MISR-Terra (MIS) from 2000/03 to 2010/12, SeaWiFS-OrbView-2 (SEA) from 1998/01 to 2007/12, and MODIS-Aqua (MYD) from 2003/01 to 2008/12) using a weighted least squares regression in order to minimize the above mentioned issues. With high statistical confidence, the weighted trends of MOD AOT (550 nm), MIS AOT (558 nm), SEA AOT (510 nm), and MYD AOT (550 nm) over OECD Europe showed a significant decrease (-0.00274±0.00126, -0.00303±0.00169, -0.00077±0.00044, and -0.00530±0.00304 per year respectively) while increasing over East Asia (+0.00727±0.00385, +0.00673±0.00401, +0.00342±0.00171, and +0.01939±0.00986 per year respectively).

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Meister, Gerhard; Franz, Bryan Alden

    2013-01-01

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

  10. 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

  11. Exploring the feasibility of using the MODIS 1 km by 1 km cloud mask product to generate a lower resolution product suitable for use with other instruments (e.g AIRS) on the EOS-Aqua satellite.

    NASA Astrophysics Data System (ADS)

    Gopalan, A.; Leptoukh, G.; Savtchenko, A.; Ouzounov, D.

    2003-12-01

    The MODIS Level-2 Cloud Mask Products MOD35_L2 (MODIS -TERRA) and MYD35_L2 (MODIS-AQUA) are available globally day and night at a pixel resolution of 1 km by 1 km. The cloud mask is based on a series of spectral cloud detection tests and estimates the probability of a pixel being clear with varying degrees of confidence (Platnick et al). We attempt to explore the possibility of adapting the MODIS Cloud Mask Product to other instruments on the Terra and Aqua Satellites that have a coarser pixel resolution as compared to the MODIS pixel. From a data center (e.g. GES-DAAC) perspective, this could potentially have a positive impact on the distribution system and better serve end users who require a lower resolution cloud mask product for their applications.

  12. Vicarious calibration of Aqua and Terra MODIS

    NASA Astrophysics Data System (ADS)

    Thome, Kurtis J.; Czapla-Myers, Jeffrey S.; Biggar, Stuart F.

    2003-11-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) is onboard both the Terra and Aqua platforms. An important aspect of the use of MODIS, and other Earth Science Enterprise sensors, has been the characterization and calibration of the sensors and validation of their data products. The Remote Sensing Group at the University of Arizona has been active in this area through the use of ground- based test sites. This paper presents the results from the reflectance-base approach using the Railroad Valley Playa test site in Nevada for both Aqua and Terra MODIS. The key to the approach is the measurement of surface reflectance over a 1-km2 area of the playa and results from this method shows agreement with both MODIS sensors to better than 5%. Early results indicate that while the two sensors both agree with the ground-based measurements to within the uncertainties of the reflectance-based approach, there were significant differences between the Aqua and Terra MODIS for data prior to September 2002. Recent results indicate that this bias, if any, is now within the uncertainties of the reflectance-based method of calibration.

  13. 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.

  14. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM3-MODIS_Edition2A)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  15. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition2A)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  16. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Ed2A-NoSW)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  17. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  18. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM3-MODIS_Edition1B)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  19. Aqua MODIS 8-Year On-Orbit Operation and Calibration

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Angal, Amit; Madhavan, Sriharsha; Choi, Taeyoung; Dodd, Jennifer; Geng, Xu; Wang, Zhipeng; Toller, Gary; Barnes, William

    2010-01-01

    Launched in May 2002, the NASA EOS Aqua MODIS has successfully operated for more than 8 years. Observations from Aqua MODIS and its predecessor, Terra MODIS, have generated an unprecedented amount of data products and made significant contributions to studies of changes in the Earth s system of land, oceans, and atmosphere. MODIS collects data in 36 spectral bands: 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). It has a set of on-board calibrators (OBC), providing sensor on-orbit radiometric, spectral, and spatial calibration and characterization. This paper briefly summarizes Aqua MODIS on-orbit operation and calibration activities and illustrates instrument on-orbit performance from launch to present. Discussions are focused on OBC functions and changes in detector radiometric gains, spectral responses, and spatial registrations. With ongoing calibration effort, Aqua MODIS will continue serving the science community with high quality data products

  20. Calibration Adjustments to the MODIS Aqua Ocean Color Bands

    NASA Technical Reports Server (NTRS)

    Meister, Gerhard

    2012-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  3. 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

  4. Status of Terra and Aqua MODIS Instrument Operation and Calibration

    NASA Astrophysics Data System (ADS)

    Xiong, X.; Wenny, B. N.; Sun, J.; Angal, A.; Salomonson, V. V.

    2013-12-01

    Terra and Aqua MODIS have successfully operated for more than 13 and 11 years since their respective launches in 1999 and 2002. Nearly 40 data products, developed for studies of the earth's land, ocean, and atmosphere, have been routinely generated from calibrated and geo-located MODIS observations and widely distributed to the science and user community. MODIS on-orbit calibration is performed by a set of on-board calibrators, which include a solar diffuser for the reflective solar bands calibration and a blackbody for the thermal emissive bands calibration. MODIS on-board calibrators are regularly operated to monitor on-orbit changes in sensor responses and key performance parameters, such as radiometric calibration coefficients. Since launch, extensive instrument calibration and characterization activities have been scheduled and executed by the MODIS Characterization Support Team (MCST). This presentation provides an overview of both Terra and Aqua MODIS instrument status, their on-orbit operation and calibration activities, and overall long-term performance. It reports calibration improvements (algorithms and look-up tables) made in the latest MODIS data collection (C6). Lessons learned from both Terra and Aqua MODIS and their applications to the S-NPP VIIRS on-orbit calibration are also discussed.

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  6. The regime of aerosol asymmetry parameter and Angstrom exponent over Europe, Mediterranean and Middle East based on MODIS satellite data. Intercomparison of MODIS-Aqua C051 and C006 retrievals

    NASA Astrophysics Data System (ADS)

    Korras-Carraca, Marios Bruno; Hatzianastassiou, Nikolaos; Matsoukas, Christos; Gkikas, Antonis; Papadimas, Christos; Sayers, Andy

    2015-04-01

    Atmospheric aerosols, both natural and anthropogenic, can cause climate change through their direct, indirect, and semi-direct effects on the radiative energy budget of the Earth-atmosphere system. In the present work, we study two of the most important optical properties of aerosols, the asymmetry parameter (gaer) and the Angstrom exponent (α). Both gaer and α are related with aerosol size, which is a very important parameter for climate and human health. The study region comprises North Africa, the Arabian peninsula, Europe, and the Mediterranean basin. These areas are of great interest, because of the variety of aerosol types they host, both anthropogenic and natural. Urban, industrial or biomass-burning aerosols are usually fine, while desert dust or sea-salt are basically coarse, making thus possible the establishment of a relationship between the type and the size of aerosols. Using satellite data from the collection 051 of MODIS (MODerate resolution Imaging Spectroradiometer, Aqua), we investigate the spatio-temporal characteristics of the asymmetry parameter and Angstrom exponent. We generally find significant spatial variability, with larger gaer values over regions dominated by larger size particles, e.g. outside the Atlantic coasts of north-western Africa, where desert-dust outflow is taking place. The gaer values tend to decrease with increasing wavelength, especially over areas dominated by small particulates. The intra-annual variability is found to be small in desert-dust areas, with maximum values during summer, while in all other areas larger values are reported during the cold season and smaller during the warm. Significant intra-annual and inter-annual variability is observed around the Black Sea. However, the inter-annual trends of gaer are found to be generally small. The geographical distributions for α (given for the pair of wavelengths 550-865 nm) affirm the conclusions drawn from the asymmetry parameter as regards the aerosol size over

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. Early on-orbit calibration results from Aqua MODIS

    NASA Astrophysics Data System (ADS)

    Xiong, Xiaoxiong; Barnes, William L.

    2003-04-01

    Aqua MODIS, also known as the MODIS Flight Model 1 (FM1), was launched on May 4, 2002. It opened its nadir aperture door (NAD) on June 24, 2002, beginning its Earth observing mission. In this paper, we present early results from Aqua MODIS on-orbit calibration and characterization and assess the instrument's overall performance. MODIS has 36 spectral bands located on four focal plane assemblies (FPAs). Bands 1-19, and 26 with wavelengths from 0.412 to 2.1 microns are the reflective solar bands (RSB) that are calibrated on-orbit by a solar diffuser (SD). The degradation of the SD is tracked using a solar diffuser stability monitor (SDSM). The bands 20-25, and 27-36 with wavelengths from 3.75 to 14.5 microns are the thermal emissive bands (TEB) that are calibrated on-orbit by a blackbody (BB). Early results indicate that the on-orbit performance has been in good agreement with the predications determined from pre-launch measurements. Except for band 21, the low gain fire band, band 6, known to have some inoperable detectors from pre-launch characterization, and one noisy detector in band 36, all of the detectors' noise characterizations are within their specifications. Examples of the sensor's short-term and limited long-term responses in both TEB and RSB will be provided to illustrate the sensor's on-orbit stability. In addition, we will show some of the improvements that Aqua MODIS made over its predecessor, Terra MODIS (Protoflight Model - PFM), such as removal of the optical leak into the long-wave infrared (LWIR) photoconductive (PC) bands and reduction of electronic crosstalk and out-of-band (OOB) thermal leak into the short-wave infrared (SWIR) bands.

  9. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  11. 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.

  12. MODIS Cloud Products Derived from Terra and Aqua During CRYSTAL-FACE

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, S.; Riedi, J. C.; Ackerman, S. A.; Menzel, W. P.

    2003-01-01

    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. During the CRYSTAL-FACE experiment, numerous aircraft coordinated both in situ and remote sensing observations with the Terra and Aqua spacecraft. In this paper we will emphasize the optical, microphysical, and physical properties of both liquid water and ice clouds obtained from an analysis of the satellite observations over Florida and the Gulf of Mexico during July 2002. We will present the frequency distribution of liquid water and ice cloud microphysical properties throughout the region, separating the results over land and ocean. Probability distributions of effective radius and cloud optical thickness will also be shown.

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

    NASA Astrophysics Data System (ADS)

    Glantz, P.; Tesche, M.

    2012-04-01

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

  14. A Comparison of Cirrus Clouds Retrieved From POLDER-3/PARASOL and MODIS/Aqua

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Yang, P.; Riedi, J.; Kattawar, G.

    2007-12-01

    MODIS on board Aqua and POLDER-3 on board PARASOL are two key instruments in the A-Train constellation of satellites. MODIS has 36 spectral bands with wavelength ranging from 0.41 to 14.5 μm, but makes measurement at only one direction without information about polarization. POLDER performs multidirectional measurements, of both reflectance and polarization, at nine spectral channels (from 443 to 1020 nm). The two instruments offer different, and somehow complementary, advantages for the remote sensing of microphysical and optical properties of cirrus clouds. In this study, a comparison of cirrus clouds retrieved from the two instruments is made to obtain understanding of the possibility, advantages and limitations of synergetic retrieval. First, the comparison is made between the single scattering properties of "Inhomogeneous Hexagonal Monocrystals" (IHM) used in POLDER retrieval algorithm and the ice-crystal ensemble model used for MODIS. Substantial differences are found in the scattering phase matrix. Co-located cloud mask and cloud top height retrievals are compared, with the emphasis on high and thin cirrus clouds. The optical thicknesses of cirrus clouds retrieved by POLDER are compared with those by MODIS, with and without the constraint that the cloud effective particle size retrieved by MODIS must be similar to that of IHM.

  15. Seasonal and Diurnal Tropical Forest Greenness Observed and Modeled Using MODIS Terra and Aqua Sensors

    NASA Astrophysics Data System (ADS)

    Huete, A. R.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.; Sun, Q.; Saleska, S. R.; Schaaf, C.

    2014-12-01

    Recent studies on satellite measures of Amazon forest greening suggest that observed seasonalities are optical artefacts resulting from shifting sun- sensor view geometries between solstice and equinox periods. The degree and extent of sun geometry influences on satellite observations have important implications on the utility of multi-sensor time series for generating accurate long-term data records. Here we investigate sun angle interactions on tropical forest greening using Terra- and Aqua-MODIS, and combined Terra-Aqua Nadir BRDF Adjusted Reflectance (NBAR) vegetation index (VI) time series, with distinct seasonal and daily sun angle conditions for 10:30 a.m., 1:30 p.m. overpasses, and local solar noon times, respectively. This was compared with modeled, sun angle corrected data from the MODIS MCD43A1 product for fixed sun angles. The interactions between sun angle and forest greening were analyzed along an equatorial forest transect of constant sun-earth geometry but variable annual rainfall and dry season length, as well as a latitudinal transect ranging from equatorial to dry southern forests. In equatorial forests, seasonality in sun angle geometry was synchronous with drought seasonality and resulted in broad scale, forest greening consistent with the duration of the dry season and light availability. The sun angle corrected data showed a reduction in the magnitude of seasonal greening, but also revealed an extended greening period well beyond the equinox. On the other hand, across the latitudinal gradient there were shifts in the start and duration of the dry season that resulted in greening patterns that were asynchronous with sun angle geometries. Sun angle influences became significant and were more pronounced at greater latitudes, demonstrating need to normalize cross-sensor satellite data for sun geometry effects, especially with the recent and upcoming launches of new satellite systems.

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

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Wu, A.

    2012-01-01

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

  17. NPP VIIRS and Aqua MODIS RSB comparison using observations from simultaneous nadir overpasses (SNO)

    NASA Astrophysics Data System (ADS)

    Wu, Aisheng; Xiong, Xiaoxiong

    2012-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  19. 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.

  20. Status of Aqua MODIS Instrument On-Orbit Operation and Calibration

    NASA Technical Reports Server (NTRS)

    Xiong, Jack; Angal, Amit; Madhaven, Sri; Choi, Jason; Wenny, Brian; Sun, Junqiang; Wu, Aisheng; Chen, Hongda; Salomonson, Vincent; Barnes, William

    2011-01-01

    The Aqua MOderate resolution Imaging Spectroradiometer (MODIS) has successfully operated for nearly a decade, since its launch in May 2002. MODIS was developed and designed with improvements over its heritage sensors in terms of its overall spectral, spatial, and temporal characteristics, and with more stringent calibration requirements. MODIS carries a set of on-board calibrators that can be used to track and monitor its on-orbit radiometric, spectral, and spatial performance. Since launch, extensive instrument calibration and characterization activities have been scheduled and executed by the MODIS Characterization Support Team (MCST). These efforts are made to assure the quality of instrument calibration and L 1B data products, as well as support all science disciplines (land, ocean, and atmospheric) for continuous improvements of science data product quality. MODIS observations from both Terra and Aqua have significantly contributed to the science and user community over a wide range of research activities and applications. This paper provides an overview of Aqua MODIS on-orbit operation and calibration activities, instrument health status, and on-board calibrators (OBC) performance. On-orbit changes of key sensor parameters, such as spectral band radiometric responses, center wavelengths, and bandwidth, are illustrated and compared with those derived from its predecessor, Terra MODIS. Lessons and challenges identified from Aqua MODIS performance are also discussed in this paper. These lessons are not only critical to future improvements of Aqua MODIS on-orbit operation and calibration but also beneficial to its follow-on instrument, the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched on NPOESS Preparatory Project (NPP) spacecraft.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Banerjee, Subhasis; Ghosh, Sanjay

    2016-07-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2012-10-15

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

  7. Urban vegetation land covers change detection using multi-temporal MODIS Terra/Aqua data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Dida, Adrian I.; Ionescu, Ovidiu M.

    2013-10-01

    Urban vegetation land cover change is a direct measure of quantitative increase or decrease in sources of urban pollution and the dimension of extreme climate events and changes that determine environment quality. Spatio- temporal monitoring of urban vegetation land cover changes is a very important task for establishing the links between policy decisions, regulatory actions and subsequent land use activities. Former studies incorporating two-date change detection using Landsat TM/ETM data had limited performance for urban biophysically complex systems applications. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer and NOAA/AVHRR satellite to study urban vegetation land cover dynamics. This study explored the use of time-series MODIS Terra/Aqua Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI), data to provide change detection information for metropolitan area of Bucharest in Romania. Training and validation are based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2002- 2012 was assessed to be of 89%, with a reasonable balance between change commission errors (21.7%), change omission errors (28.5%), and Kappa coefficient of 0.69. Annual change detection rates across the urban/periurban areas over the study period (2002-2012) were estimated at 0.78% per annum in the range of 0.45% (2002) to 0.75% (2012).Vegetation dynamics in urban areas at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system.

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  10. An Assessment of Diurnal and Seasonal Cloud Cover Changes Over the Hawaiian Islands Using Terra and Aqua MODIS

    NASA Astrophysics Data System (ADS)

    Barnes, M.; Miura, T.; Giambelluca, T. W.; Chen, Q.

    2012-12-01

    To date, there has not yet been a spatial and temporal analysis of cloud cover over the Hawaiian Islands using high spatial resolution data. An understanding of patterns in cloud cover is essential to analyzing and understanding atmospheric and hydrologic processes, including evapotranspiration. The MODIS instruments aboard the Terra and Aqua satellites provide observations with the high spatial resolution necessary to determine patterns of cloud cover over the Hawaiian Islands. The objective of this study was to determine how spatial patterns of cloudiness change diurnally and seasonally over the Hawaiian Islands using high resolution cloud cover data generated from the Terra and Aqua MODIS satellite sensors. The MODIS cloud mask products (MOD35 and MYD35) were obtained for the entire MODIS time series over the major Hawaiian Islands. Monthly statistics including mean cloud cover probability at the daytime and nighttime overpasses for each instrument were generated from the daily MOD35 and MYD35 cloudiness time series. The derived monthly statistics for January and June (the wet and dry season, respectively) were analyzed for diurnal (morning vs. afternoon and late evening vs. early morning) changes in total amount and spatial patterns of cloudiness. They were also compared to analyze seasonal changes in cloudiness. Cloud probability generally increased with elevation until the elevation of the inversion layer. The lowest cloud cover probability was observed above the inversion layer on the islands of Maui and Hawaii. This elevational gradient varied in relation to the facings of slopes; cloud cover probability was higher on the windward (northeastern) sides than on the leeward (southwestern) sides of the mountains. Both morning and afternoon observations indicate that the Hawaiian Islands were cloudier in June than in January. This is the opposite of what we might expect as January is in the wet season and June is in the dry season. Both late evening and early

  11. Aerosol Characterisitics Over Alberta Using Modis and OMI Satellite Data

    NASA Astrophysics Data System (ADS)

    Marey, H. S.; Hashisho, Z., Sr.; Fu, L.; Gille, J. C.

    2015-12-01

    We present the first detailed analysis of optical aerosol characterization over Alberta based on satellite data analysis. Aerosol optical depth (AOD) at 550 nm for 11 years (2003-2013), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Aqua satellite, was analyzed. Additionally, UV aerosol index (AI) data for 9 years (2005-2013) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite was used to examine absorbing aerosols. Comparing AERONET to MODIS 3 km and 10 km products indicated a stronger correlation (r=0.9 for the latter vs 0.7 for the former) thus 10 km product has been utilized for this study. Overall, gridded seasonal maps (0.1 deg.) of the 11 yr averaged AOD illustrate the highest AOD during summer, followed by spring, with the lowest observed values during fall (there is no enough valid MODIS data in winter due to cloud cover). Aerosol optical properties exhibited large spatio-temporal heterogeneity in the summer with mean AOD of 0.25, followed by spring, while the fall had less variability with mean AOD below 0.1 for the entire region. However, the spatial analysis indicated hot spots around Edmonton and Calgary cities even in the fall when AODs are very low (close to background). All of the datasets showed interannual variability with no significant trend. The AI values ranged from 0.5 during winter to as high as 5 during summer suggesting mid- and long range transport of boreal fire emissions. Map correlation between AOD and UV AI showed large variability (0.2 to 0.7) indicating presence of different types of aerosols. These low correlations imply the presence of non-absorbing particles (e.g. sulfate) that comprise a relatively large mass fraction of AOD and/or low altitude particles.

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

    NASA Technical Reports Server (NTRS)

    2002-01-01

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

  13. Evaluation of Terra and Aqua MODIS thermal emissive band response versus scan angle

    NASA Astrophysics Data System (ADS)

    Wenny, B. N.; Wu, A.; Madhavan, S.; Xiong, X.

    2014-10-01

    Terra and Aqua MODIS have operated near-continuously for over 14 and 12 years, respectively, and are key instruments for NASA's Earth Observing System. Observations from the 16 thermal emissive bands (TEB), covering wavelengths from 3.5 to 14.4 μm with a nadir spatial resolution of 1 km are used to regularly generate a variety of atmosphere, ocean and land science products. The TEB detectors are calibrated using scan-by-scan observations of an on-board blackbody (BB). The current response versus scan angle (RVS) of the scan mirror was derived using a spacecraft deep-space pitch maneuver for Terra MODIS and characterized during prelaunch for Aqua MODIS. Earth view (EV) data over the complete range of angles of incidence (AOI) can be used to evaluate the on-orbit performance of the TEB RVS over the mission lifetime. Three approaches for tracking the TEB RVS on-orbit using EV observations are formulated. The first approach uses the multiple daily observations of Dome C BT at different AOI and their trend relative to coincident measurements from a ground temperature sensor. The second approach uses brightness temperatures (BT) retrieved over the cloud-free ocean to derive the trends at 13 AOI over the mission lifetime. The third approach tracks the dn response (normalized to the BB AOI) across the full swath width for Antarctic granules with the Dome C site at nadir. The viability of the three approaches is assessed and the long-term stability of the TEB RVS for both MODIS instruments is determined.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  16. 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

  17. Identifying false rain in satellite precipitation products using CloudSat and MODIS

    NASA Astrophysics Data System (ADS)

    Nasrollahi, N.; Hsu, K.; Sorooshian, S.

    2012-12-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA Earth Observing System Aqua and Terra platform with 36 spectral bands provides valuable information about cloud microphysical characteristics. Additionally, CloudSat, selected as a NASA Earth Sciences Systems Pathfinder (ESSP) satellite mission, is designed to measure vertical structure of clouds. The CloudSat radar flies in formation with Aqua with only an average of 60 second delay. In this study, the application of MODIS multispectral images and CloudSat Level 2-C Precipitation Column Algorithm in false rain identification is investigated. Using a machine learning technique, the presence of precipitation will be assigned to textural and spectral features of clouds observed by the MODIS satellite, whenever CloudSat surface rainfall retrieval is available. This information for different regions and seasons create a training data set. The training database will then be used as a reference to find if any pixel in the MODIS retrieval window is falsely identified as rainy pixel for the times that CloudSat data is not available. The input to the Artificial Neural Networks (ANN) model is a combination of 8 MODIS visible, water vapor and infrared channels. The performance of model with combination of different MODIS channels is estimated. The results of ANN model are used to filter out false rainy pixels from satellite precipitation estimates (e.g. PERSIANN). The outcome of the new corrected precipitation data is compared to ground based radar measurements (Stage IV radar data). The results show a 64 percent reduction in false rain in PERSIANN satellite data for 100 cases investigated in summer 2008 and 24 percent false rain reduction in more than 50 cases studied in winter 2010.

  18. 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

  19. Aerosol Lidar and MODIS Satellite Comparisons for Future Aerosol Loading Forecast

    NASA Technical Reports Server (NTRS)

    DeYoung, Russell; Szykman, James; Severance, Kurt; Chu, D. Allen; Rosen, Rebecca; Al-Saadi, Jassim

    2006-01-01

    Knowledge of the concentration and distribution of atmospheric aerosols using both airborne lidar and satellite instruments is a field of active research. An aircraft based aerosol lidar has been used to study the distribution of atmospheric aerosols in the California Central Valley and eastern US coast. Concurrently, satellite aerosol retrievals, from the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra and Aqua satellites, were take over the Central Valley. The MODIS Level 2 aerosol data product provides retrieved ambient aerosol optical properties (e.g., optical depth (AOD) and size distribution) globally over ocean and land at a spatial resolution of 10 km. The Central Valley topography was overlaid with MODIS AOD (5x5 sq km resolution) and the aerosol scattering vertical profiles from a lidar flight. Backward air parcel trajectories for the lidar data show that air from the Pacific and northern part of the Central Valley converge confining the aerosols to the lower valley region and below the mixed layer. Below an altitude of 1 km, the lidar aerosol and MODIS AOD exhibit good agreement. Both data sets indicate a high presence of aerosols near Bakersfield and the Tehachapi Mountains. These and other results to be presented indicate that the majority of the aerosols are below the mixed layer such that the MODIS AOD should correspond well with surface measurements. Lidar measurements will help interpret satellite AOD retrievals so that one day they can be used on a routine basis for prediction of boundary layer aerosol pollution events.

  20. Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

    NASA Technical Reports Server (NTRS)

    Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.

    2012-01-01

    Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median

  1. Analysis of the influence of river discharge and wind on the Ebro turbid plume using MODIS-Aqua and MODIS-Terra data

    NASA Astrophysics Data System (ADS)

    Fernández-Nóvoa, D.; Mendes, R.; deCastro, M.; Dias, J. M.; Sánchez-Arcilla, A.; Gómez-Gesteira, M.

    2015-02-01

    The turbid plume formed at many river mouths influences the adjacent coastal area because it transports sediments, nutrients, and pollutants. The effects of the main forcings affecting the Ebro turbid plume were analyzed using data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua and Terra satellites over the period 2003-2011. Composite images were obtained for days under certain river discharge conditions (different flow regimes) and different types of wind (alongshore and cross-shore winds) in order to obtain a representative plume pattern for each situation. River discharge was the main driver of the Ebro River plume, followed by wind as the secondary force and regional oceanic circulation as the third one. Turbid plume extension increased monotonically with increased river discharge. Under high river discharge conditions (> 355 m3 s- 1), wind distributed the plume in the dominant wind direction. Seaward winds (mistral) produced the largest extension of the plume (1893 km2), whereas southern alongshore winds produced the smallest one (1325 km2). Northern alongshore winds induced the highest mean turbid value of the plume, and southern alongshore winds induced the lowest one. Regardless of the wind condition, more than 70% of the plume extension was located south of the river mouth influenced by the regional oceanic circulation.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  5. 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.

  6. Evaluation of cloud base height measurements from Ceilometer CL31 and MODIS satellite over Ahmedabad, India

    NASA Astrophysics Data System (ADS)

    Sharma, Som; Vaishnav, Rajesh; Shukla, Munn V.; Kumar, Prashant; Kumar, Prateek; Thapliyal, Pradeep K.; Lal, Shyam; Acharya, Yashwant B.

    2016-02-01

    Clouds play a tangible role in the Earth's atmosphere and in particular, the cloud base height (CBH), which is linked to cloud type, is one of the most important characteristics to describe the influence of clouds on the environment. In the present study, CBH observations from Ceilometer CL31 were extensively studied during May 2013 to January 2015 over Ahmedabad (23.03° N, 72.54° E), India. A detailed comparison has been performed with the use of ground-based CBH measurements from Ceilometer CL31 and CBH retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard Aqua and Terra satellite. CBH retrieved from MODIS is ˜ 1.955 and ˜ 1.093 km on 25 July 2014 and 1 January 2015 respectively, which matches well with ceilometer-measured CBH ( ˜ 1.92 and ˜ 1.097 km). Some interesting features of cloud dynamics viz. strong downdraft and updraft have been observed over Ahmedabad which revealed different cloud characteristics during monsoon and post-monsoon periods. CBH shows seasonal variation during the Indian summer monsoon and post-monsoon period. Results indicate that the ceilometer is an excellent instrument to precisely detect low- and mid-level clouds, and the MODIS satellite provides accurate retrieval of high-level clouds over this region. The CBH algorithm used for the MODIS satellite is also able to capture the low-level clouds.

  7. Use of spaceborne lidar for the evaluation of thin cirrus contamination and screening in the Aqua MODIS Collection 5 aerosol products

    NASA Astrophysics Data System (ADS)

    Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Liu, Zhaoyan; Jeong, Myeong-Jae; Hansell, Richard A.; Lee, Jaehwa

    2013-06-01

    Cloud contamination from subvisual thin cirrus clouds is still a challenging issue for operational satellite aerosol retrievals. In the A-Train constellation, concurrent high-sensitivity cirrus observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) provide us with an unprecedented opportunity to examine the susceptibility of the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol retrievals to thin cirrus contamination and to evaluate the robustness of various cirrus screening techniques. Quantitative evaluations indicate that the current cirrus screening schemes in the MODIS Dark Target and Deep Blue Collection 5 aerosol retrievals can effectively remove most cirrus signals while some residual thin cirrus signals still exist with strong spatial and seasonal variability. Results also show significant linkage between thin cirrus occurrence frequency and the susceptibility of aerosol retrievals to thin cirrus contamination. Using the CALIPSO cirrus observations as a reference, we also examined the effectiveness and robustness of eight MODIS-derived cirrus screening parameters. These parameters include apparent reflectance at 1.38 µm (R1.38), cirrus reflectance at 0.66 µm (CR0.66), CR0.66 cirrus flag (CF), reflectance ratio between 1.38 µm and 0.66 µm (RR1.38/0.66), reflectance ratio between 1.38 µm and 1.24 µm (RR1.38/1.24), brightness temperature difference between 8.6 µm and 11 µm (BTD8.6-11), brightness temperature difference between 11 µm and 12 µm (BTD11-12), and cloud phase infrared approach (CPIR). Among these parameters, RR1.38/0.66 achieves the best overall performance, followed by the BTD11-12. Results from several test cases suggest that the cirrus screening schemes in the operational MODIS aerosol retrieval algorithms can be further improved to reduce thin cirrus contamination.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Deng, Z.; Wang, J.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  11. Relative spectral response corrected calibration inter-comparison of S-NPP VIIRS and Aqua MODIS thermal emissive bands

    NASA Astrophysics Data System (ADS)

    Efremova, Boryana; Wu, Aisheng; Xiong, Xiaoxiong

    2014-09-01

    The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is built with strong heritage from EOS MODIS, and has very similar thermal emissive bands (TEB) calibration algorithm and on-board calibrating source - a V-grooved blackbody. The calibration of the two instruments can be assessed by comparing the brightness temperatures retrieved from VIIRS and Aqua MODIS simultaneous nadir observations (SNO) from their spectrally matched TEB. However, even though the VIIRS and MODIS bands are similar there are still relative spectral response (RSR) differences and thus some differences in the retrieved brightness temperatures are expected. The differences depend on both the type and the temperature of the observed scene, and contribute to the bias and the scatter of the comparison. In this paper we use S-NPP Cross-track Infrared Sounder (CrIS) data taken simultaneously with the VIIRS data to derive a correction for the slightly different spectral coverage of VIIRS and MODIS TEB bands. An attempt to correct for RSR differences is also made using MODTRAN models, computed with physical parameters appropriate for each scene, and compared to the value derived from actual CrIS spectra. After applying the CrIS-based correction for RSR differences we see an excellent agreement between the VIIRS and Aqua MODIS measurements in the studied band pairs M13-B23, M15-B31, and M16- B32. The agreement is better than the VIIRS uncertainty at cold scenes, and improves with increasing scene temperature up to about 290K.

  12. MODIS Rapid Response: On-the-ground, real time applications of scientific satellite imagery

    NASA Astrophysics Data System (ADS)

    Schmaltz, J. E.; Riebeek, H.; Kendall, J. D.

    2009-12-01

    Since 2001, NASA’s MODIS Rapid Response Project has been providing fire detections and imagery in near real time for a wide variety of application users. The project web site provides MODIS imagery in true color and false color band combinations, a vegetation index, and land surface temperature - in both uncorrected swath format and geographically corrected subset regions within a few hours of data acquisition. The uncorrected swath format data is available worldwide. Geographically corrected subset images cover the world's land areas and adjoining waters, as well as the entire Arctic and Antarctic. Images are available twice daily, in the morning from the Terra satellite and in the afternoon from the Aqua satellite. A wide range of user communities access this information to get a rapid, 250 meter-resolution overview of ground conditions for fire management, crop and famine monitoring and forecasting, disaster response (floods, storms), dust and aerosol monitoring, aviation (tracking volcanic ash), monitoring sea ice conditions, environmental monitoring, and more. The scientific community uses imagery to locate phenomena of interest prior to ordering and processing data and to support the day-to-day planning of field campaigns. Rapid Response imagery is used extensively to support education and public outreach, both by NASA and other organizations, and is frequently found in newspapers, books, TV, and the web. California wildfires, 26 October 2003, Terra MODIS

  13. The regime of aerosol optical depth over Central Asia based on MODIS Aqua Deep Blue data

    NASA Astrophysics Data System (ADS)

    Floutsi, Athina; KorrasCarraca, Marios; Matsoukas, Christos; Biskos, George

    2015-04-01

    Atmospheric aerosols, both natural and anthropogenic, can affect the regional and global climate through their direct, indirect, and semi-direct effects on the radiative energy budget of the Earth-atmosphere system. To quantify these effects it is therefore important to determine the aerosol load, and an effective way to do that is by measuring the aerosol optical depth (AOD). In this study we investigate the spatial and temporal variability of the AOD over the climatically sensitive region of Central Asia (36° N - 50° N, 46° E - 75° E), which has significant sources of both natural and anthropogenic particles. The primary source of anthropogenic particles is fossil fuel combustion occurring mainly at oil refineries in the Caspian Sea basin. Natural particles originate mostly from the two deserts in the region (namely Kara-Kum and Kyzyl-Kum), where persistent dust activity is observed. Another source is the Aral Sea region, which due to its phenomenal desertification also drives an intense salt and dust transport from the exposed sea-bed to the surrounding regions. This transport is of particular interest because of health-hazardous materials contained in the Aral Sea sea-bed. For our analysis we use Level-3 daily MODIS - Aqua Dark Target - Deep Blue combined product, from the latest MODIS collection (006), available in 1° x 1° resolution (about 100 km x 100 km) over the period 2002-2014.Our first results indicate a significant spatial variability of the aerosol load over the study region. The data also show a clear seasonal cycle, with large aerosol load being associated with strong dust activity during spring and summer (AOD up to 0.5), and low during autumn and winter (AOD up to 0.4). In spring and summer significant aerosol load is observed in the Garabogazköl basin, Northeast and South-southeast Caspian Sea (offshore North Iran and Azerbaijan), as well as southwest of the Aral Sea. In the later region, the high AOD values can be explained by export of

  14. An Emerging Global Aerosol Climatology from the MODIS Satellite Sensors

    NASA Technical Reports Server (NTRS)

    Remer, Lorraine A.; Kleidman, Richard G.; Levy, Robert C.; Kaufman, Yoram J.; Tanre, Didier; Mattoo, Shana; Martins, J. Vandelei; Ichoku, Charles; Koren, Ilan; Hongbin, Yu; Holben, Brent N.

    2008-01-01

    The recently released Collection 5 MODIS aerosol products provide a consistent record of the Earth's aerosol system. Comparison with ground-based AERONET observations of aerosol optical depth (AOD) we find that Collection 5 MODIS aerosol products estimate AOD to within expected accuracy more than 60% of the time over ocean and more than 72% of the time over land. This is similar to previous results for ocean, and better than the previous results for land. However, the new Collection introduces a 0.01 5 offset between the Terra and Aqua global mean AOD over ocean, where none existed previously. Aqua conforms to previous values and expectations while Terra is high. The cause of the offset is unknown, but changes to calibration are a possible explanation. We focus the climatological analysis on the better understood Aqua retrievals. We find that global mean AOD at 550 nm over oceans is 0.13 and over land 0.19. AOD in situations with 80% cloud fraction are twice the global mean values, although such situations occur only 2% of the time over ocean and less than 1% of the time over land. There is no drastic change in aerosol particle size associated with these very cloudy situations. Regionally, aerosol amounts vary from polluted areas such as East Asia and India, to the cleanest regions such as Australia and the northern continents. In almost all oceans fine mode aerosol dominates over dust, except in the tropical Atlantic downwind of the Sahara and in some months the Arabian Sea.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  16. New Satellite Measurements of Aerosol Direct Radiative Forcing from MODIS, MISR, and POLDER

    NASA Technical Reports Server (NTRS)

    Kaufman, Y.

    2000-01-01

    New set of satellites, MODIS and MISR launched on EOS-Terra and POLDER launched on ADEOS-1, and scheduled for ADEOS-II and PARASOL in orbit with EOS-AQUA, open exciting opportunities to measure aerosol and their radiative forcing of climate. Each of these instruments has a different approach to invert remote sensing data to derive the aerosol properties. MODIS is using wide spectral range 0.47-2.1 micron. MISR is using narrower spectral range (0.44 to 0.87 micron) but observing the same spot from 9 different angles along the satellite track. POLDER using similar wavelengths, uses two dimensional view with a wide angle optics and adds polarization to the inversion process. Among these instruments, we expect to measure the global distribution of aerosol, to distinguish small pollution particles from large particles from deserts and ocean spray. We shall try to measure the aerosol absorption of solar radiation, and their refractive index that indicates the effect of liquid water on the aerosol size and interaction with sunlight. The radiation field measured by these instruments in variety of wavelengths and angles, is also used to derive the effect of the aerosol on reflection of sunlight spectral fluxes to space. When combined with flux measurements at the ground, it gives a complete characterization of the effect of aerosol on solar illumination, heating in the atmosphere and reflection to space.

  17. Feasibility of anomaly occurrence in aerosols time series obtained from MODIS satellite images during hazardous earthquakes

    NASA Astrophysics Data System (ADS)

    Akhoondzadeh, Mehdi; Jahani Chehrebargh, Fatemeh

    2016-09-01

    Earthquake is one of the most devastating natural disasters that its prediction has not materialized comprehensive. Remote sensing data can be used to access information which is closely related to an earthquake. The unusual variations of lithosphere, atmosphere and ionosphere parameters before the main earthquakes are considered as earthquake precursors. To date the different precursors have been proposed. This paper examines one of the parameters which can be derived from satellite imagery. The mentioned parameter is Aerosol Optical Depth (AOD) that this article reviews its relationship with earthquake. Aerosol parameter can be achieved through various methods such as AERONET ground stations or using satellite images via algorithms such as the DDV (Dark Dense Vegetation), Deep Blue Algorithm and SYNTAM (SYNergy of Terra and Aqua Modis). In this paper, by analyzing AOD's time series (derived from MODIS sensor on the TERRA platform) for 16 major earthquakes, seismic anomalies were observed before and after earthquakes. Before large earthquakes, rate of AOD increases due to the pre-seismic changes before the strong earthquake, which produces gaseous molecules and therefore AOD increases. Also because of aftershocks after the earthquake there is a significant change in AOD due to gaseous molecules and dust. These behaviors suggest that there is a close relationship between earthquakes and the unusual AOD variations. Therefore the unusual AOD variations around the time of earthquakes can be introduced as an earthquake precursor.

  18. Inter-annual variability of aerosol optical depth over the tropical Atlantic Ocean based on MODIS-Aqua observations over the period 2002-2012

    NASA Astrophysics Data System (ADS)

    Gkikas, Antonis; Hatzianastassiou, Nikolaos

    2013-04-01

    The tropical Atlantic Ocean is affected by dust and biomass burning aerosol loads transported from the western parts of the Saharan desert and the sub-Sahel regions, respectively. The spatial and temporal patterns of this transport are determined by the aerosol emission rates, their deposition (wet and dry), by the latitudinal shift of the Intertropical Convergence Zone (ITCZ) and the prevailing wind fields. More specifically, in summer, Saharan dust aerosols are transported towards the Atlantic Ocean, even reaching the Gulf of Mexico, while in winter the Atlantic Ocean transport takes place in more southern latitudes, near the equator, sometimes reaching the northern parts of South America. In the later case, dust is mixed with biomass burning aerosols originating from agricultural activities in the sub-Sahel, associated with prevailing north-easterly airflow (Harmattan winds). Satellite observations are the appropriate tool for describing this African aerosol export, which is important to atmospheric, oceanic and climate processes, offering the advantage of complete spatial coverage. In the present study, we use satellite measurements of aerosol optical depth at 550nm (AOD550nm), on a daily and monthly basis, derived from MODIS-Aqua platform, at 1ox1o spatial resolution (Level 3), for the period 2002-2012. The primary objective is to determine the pixel-level and regional mean anomalies of AOD550nm over the entire study period. The regime of the anomalies of African export is interpreted in relation to the aerosol source areas, precipitation, wind patterns and temporal variability of the North Atlantic Oscillation Index (NAOI). In order to ensure availability of AOD over the Sahara desert, MODIS-Aqua Deep Blue products are also used. As for precipitation, Global Precipitation Climatology Project (GPCP) data at 2.5ox2.5o are used. The wind fields are taken from the National Center for Environmental Prediction (NCEP). Apart from the regime of African aerosol export

  19. Earth System Science Research Using Datra and Products from Terra, Aqua, and ACRIM Satellites

    NASA Technical Reports Server (NTRS)

    Hutchison, Keith D.

    2007-01-01

    The report describes the research conducted at CSR to extend MODIS data and products to the applications required by users in the State of Texas. This research presented in this report was completed during the timeframe of August 2004 - December 31, 2007. However, since annual reports were filed in December 2005 and 2006, results obtained during calendar year 2007 are emphasized in the report. The stated goals of the project were to complete the fundamental research needed to create two types of new, Level 3 products for the air quality community in Texas from data collected by NASA s EOS Terra and Aqua missions.

  20. Aerosol-cloud relations over Eastern Mediterranean as seen from MODIS satellite observations

    NASA Astrophysics Data System (ADS)

    Georgoulias, Aristeidis K.; Kourtidis, Konstantinos; Zanis, Prodromos; Alexandri, Georgia; Pöschl, Ulrich

    2014-05-01

    In this work, the aerosol-cloud relations over the region of Eastern Mediterranean are investigated at a spatial resolution of 0.1 degrees (~10km). Within the QUADIEEMS project, a 13-year gridded dataset with several aerosol and cloud related parameters has been compiled using level-2 single pixel measurements from MODIS TERRA and MODIS AQUA satellite sensors. The aerosol gridded dataset has been successfully validated against ground-based measurements from 12 AERONET sites. The high spatial resolution of the dataset allows for the investigation of local phenomena. In addition, the combined use of MODIS data with data from the Earth Probe TOMS and OMI satellite sensors, data from the ERA-interim reanalysis, data from the GOCART chemical-aerosol-transport model and the MACC reanalysis, allows for the quantification of the relative contribution of different aerosol types to the total aerosol optical depth (AOD550). Using these results, we calculate the relations of AOD550 with the cloud effective particle radius, the cloud droplet number concentration, the cloud cover and the cloud water path. Further, we repeat this procedure taking into account each time days characterized by a dominant aerosol type (e.g. anthropogenic, dust) and different types of clouds (e.g. liquid, ice, low, high, etc). We present here selected results from this ongoing research. This work is funded by QUADIEEMS project which is co-financed by the European Social Fund (ESF) and national resources under the operational programme Education and Lifelong Learning (EdLL) within the framework of the Action "Supporting Postdoctoral Researchers".

  1. Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

    NASA Technical Reports Server (NTRS)

    Pittman, Jasna; Robertson, Franklin; Blankenship, Clay

    2008-01-01

    Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  4. Investigating Correlations Between Satellite-Derived Aerosol Optical Depth And Ground PM2.5 Measurements in Californias San Joaquin Valley with MODIS Deep Blue

    NASA Astrophysics Data System (ADS)

    Justice, E.; Huston, L.; Krauth, D.; Mack, J.; Oza, S.; Strawa, A.; Legg, M.; Schmidt, C.; Skiles, J.

    2008-12-01

    Air quality in the San Joaquin Valley has failed to meet state and federal particulate matter (PM) attainment standards for the past several years. Air quality agencies currently use ground sensors to monitor the region's air. While this method provides accurate information at specific locations, it does not provide a clear indication of conditions over large regions. Measurements from satellite imagery have the potential to provide timely air quality data for large swaths of land. While previous studies show strong correlations between MODIS-derived Aerosol Optical Depth (AOD) and surface PM measurements on the East Coast of the United States, only weak correlations have been found in the West. Specific causes of this discrepancy have not been identified, nor has a solution been found. This study compares hourly and daily surface PM measurements to both traditional and Deep Blue-derived Aqua MODIS AOD data. Deep Blue is a newly developed algorithm that was recently applied to all Aqua MODIS data. Additionally, we analyzed the effects of relative humidity, surface reflectance, and aerosol vertical distribution, from CALIPSO's CALIOP sensor, on differences in PM and AOD measurements. Results show hourly PM2.5 data improved correlations with satellite AOD values. Also PM2.5 data, corresponding to sites in Bakersfield and Fresno, correlate better with Deep Blue-derived AOD values than with traditional MODIS AOD. Further investigation into the affects of seasonal variation, particle distribution and speciation is needed.

  5. Comparison Between NPP-VIIRS Aerosol Data Products and the MODIS AQUA Deep Blue Collection 6 Dataset Over Land

    NASA Technical Reports Server (NTRS)

    Sayer, Andrew M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Kondragunta, S.

    2013-01-01

    Aerosols are small particles suspended in the atmosphere and have a variety of natural and man-made sources. Knowledge of aerosol optical depth (AOD), which is a measure of the amount of aerosol in the atmosphere, and its change over time, is important for multiple reasons. These include climate change, air quality (pollution) monitoring, monitoring hazards such as dust storms and volcanic ash, monitoring smoke from biomass burning, determining potential energy yields from solar plants, determining visibility at sea, estimating fertilization of oceans and rainforests by transported mineral dust, understanding changes in weather brought upon by the interaction of aerosols and clouds, and more. The Suomi-NPP satellite was launched late in 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine AOD. This study compares the VIIRS dataset to ground-based measurements of AOD, along with a state-of-the-art satellite AOD dataset (the new version of the Moderate Resolution Imaging Spectrometer Deep Blue algorithm) to assess its reliability. The Suomi-NPP satellite was launched late in 2011, carrying several instruments designed to continue the biogeophysical data records of current and previous satellite sensors. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine aerosol optical depth (AOD), and related activities since launch have been focused towards validating and understanding this new dataset through comparisons with other satellite and ground-based products. The operational VIIRS AOD product is compared over land with AOD derived from Moderate Resolution Imaging Spectrometer (MODIS) observations using the Deep Blue (DB) algorithm from the forthcoming Collection 6 of MODIS data

  6. Contribution of MODIS Derived Snow Cover Satellite Data into Artificial Neural Network for Streamflow Estimation

    NASA Astrophysics Data System (ADS)

    Uysal, Gokcen; Arda Sorman, Ali; Sensoy, Aynur

    2014-05-01

    Contribution of snowmelt and correspondingly snow observations are highly important in mountainous basins for modelers who deal with conceptual, physical or soft computing models in terms of effective water resources management. Long term archived continuous data are needed for appropriate training and testing of data driven approaches like artificial neural networks (ANN). Data is scarce at the upper elevations due to the difficulty of installing sufficient automated SNOTEL stations; thus in literatures many attempts are made on the rainfall dominated basins for streamflow estimation studies. On the other hand, optical satellites can easily detect snow because of its high reflectance property. MODIS (Moderate Resolution Imaging Spectroradiometer) satellite that has two platforms (Terra and Aqua) provides daily and 8-daily snow images for different time periods since 2000, therefore snow cover data (SCA) may be useful as an input layer for ANN applications. In this study, a multi-layer perceptron (MLP) model is trained and tested with precipitation, temperature, radiation, previous day discharges as well as MODIS daily SCA data. The weights and biases are optimized with fastest and robust Levenberg-Marquardt backpropagation algorithm. MODIS snow cover images are removed from cloud coverage using certain filtering techniques. The Upper Euphrates River Basin in eastern part of Turkey (10 250 km2) is selected as the application area since it is fed by snowmelt approximately 2/3 of total annual volume during spring and early summer. Several input models and ANN structures are investigated to see the effect of the contributions using 10 years of data (2001-2010) for training and validation. The accuracy of the streamflow estimations is checked with statistical criteria (coefficient of determination, Nash-Sutcliffe model efficiency, root mean square error, mean absolute error) and the results seem to improve when SCA data is introduced. Furthermore, a forecast study is

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

    Abstract Radiative forcing due to linear-shaped jet contrails is calculated over the Northern Hemisphere for four seasonal months using 2006 <span class="hlt">Aqua</span> Moderate-resolution Imaging Spectroradiometer cloud and contrail property retrieval data in a radiative transfer model. The 4 month mean shortwave, longwave, and net radiative forcings normalized to 100% contrail cover are -5.7, 14.2, and 8.5 Wm-2. Mean total net forcing over the northern half of the globe varies from 9.1 mW m-2 during October to 12.1 mW m-2 in January and is only representative at 01:30 and 13:30 LT in nonpolar regions. In some dense flight traffic corridors, the mean net forcing approaches 80 mW m-2. Scaling the 4 month average of 10.6 mW m-2 to the Southern Hemisphere air traffic yields global mean net forcing of 5.7 mW m-2, which is smaller than most model estimates. Nighttime net forcing is 3.6 times greater than during daytime, when net forcing is greatest over low clouds. Effects from contrail cirrus clouds that evolve from linear contrails are not considered in these results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013ACP....13.5945T&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013ACP....13.5945T&link_type=ABSTRACT"><span id="translatedtitle">Volcanic SO2 fluxes derived from <span class="hlt">satellite</span> data: a survey using OMI, GOME-2, IASI and <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Theys, N.; Campion, R.; Clarisse, L.; Brenot, H.; van Gent, J.; Dils, B.; Corradini, S.; Merucci, L.; Coheur, P.-F.; Van Roozendael, M.; Hurtmans, D.; Clerbaux, C.; Tait, S.; Ferrucci, F.</p> <p>2013-06-01</p> <p>Sulphur dioxide (SO2) fluxes of active degassing volcanoes are routinely measured with ground-based equipment to characterize and monitor volcanic activity. SO2 of unmonitored volcanoes or from explosive volcanic eruptions, can be measured with <span class="hlt">satellites</span>. However, remote-sensing methods based on absorption spectroscopy generally provide integrated amounts of already dispersed plumes of SO2 and <span class="hlt">satellite</span> derived flux estimates are rarely reported. Here we review a number of different techniques to derive volcanic SO2 fluxes using <span class="hlt">satellite</span> measurements of plumes of SO2 and investigate the temporal evolution of the total emissions of SO2 for three very different volcanic events in 2011: Puyehue-Cordón Caulle (Chile), Nyamulagira (DR Congo) and Nabro (Eritrea). High spectral resolution <span class="hlt">satellite</span> instruments operating both in the ultraviolet-visible (OMI/Aura and GOME-2/MetOp-A) and thermal infrared (IASI/MetOp-A) spectral ranges, and multispectral <span class="hlt">satellite</span> instruments operating in the thermal infrared (<span class="hlt">MODIS/Terra-Aqua</span>) are used. We show that <span class="hlt">satellite</span> data can provide fluxes with a sampling of a day or less (few hours in the best case). Generally the flux results from the different methods are consistent, and we discuss the advantages and weaknesses of each technique. Although the primary objective of this study is the calculation of SO2 fluxes, it also enables us to assess the consistency of the SO2 products from the different sensors used.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1231349T&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1231349T&link_type=ABSTRACT"><span id="translatedtitle">Volcanic SO2 fluxes derived from <span class="hlt">satellite</span> data: a survey using OMI, GOME-2, IASI and <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Theys, N.; Campion, R.; Clarisse, L.; Brenot, H.; van Gent, J.; Dils, B.; Corradini, S.; Merucci, L.; Coheur, P.-F.; Van Roozendael, M.; Hurtmans, D.; Clerbaux, C.; Tait, S.; Ferrucci, F.</p> <p>2012-12-01</p> <p>Sulphur dioxide (SO2) fluxes of active degassing volcanoes are routinely measured with ground-based equipment to characterize and monitor volcanic activity. SO2 of unmonitored volcanoes or from explosive volcanic eruptions, can be measured with <span class="hlt">satellites</span>. However, remote-sensing methods based on absorption spectroscopy generally provide integrated amounts of already dispersed plumes of SO2 and <span class="hlt">satellite</span> derived flux estimates are rarely reported. Here we review a number of different techniques to derive volcanic SO2 fluxes using <span class="hlt">satellite</span> measurements of dispersed and large-scale plumes of SO2 and investigate the temporal evolution of the total emissions of SO2 for three very different volcanic events in 2011: Puyehue-Cordón Caulle (Chile), Nyamulagira (DR Congo) and Nabro (Eritrea). High spectral resolution <span class="hlt">satellite</span> instruments operating both in the UV-visible (OMI/Aura and GOME-2/MetOp-A) and thermal infrared (IASI/MetOp-A) spectral ranges, and multispectral <span class="hlt">satellite</span> instruments operating in the thermal infrared (<span class="hlt">MODIS/Terra-Aqua</span>) are used. We show that <span class="hlt">satellite</span> data can provide fluxes with a sampling of a day or less (few hours in the best case). Generally the flux results from the different methods are consistent, and we discuss the advantages and weaknesses of each technique. Although the primary objective of this study is the calculation of SO2 fluxes, it also enables to assess the consistency of the SO2 products from the different sensors used.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.youtube.com/watch?v=2iSQcqRErHc','SCIGOVIMAGE-NASA'); return false;" href="http://www.youtube.com/watch?v=2iSQcqRErHc"><span id="translatedtitle"><span class="hlt">Satellites</span> View Growing Gulf Oil Spill (Update)</span></a></p> <p><a target="_blank" href="http://www.nasa.gov/multimedia/videogallery/index.html">NASA Video Gallery</a></p> <p></p> <p></p> <p>On April 30, 2010, the Deepwater Horizon oil rig exploded in the Gulf of Mexico, triggering the largest oil spill in U.S. history. The <span class="hlt">MODIS</span> instrument, on board NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, c...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.B41A0367B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.B41A0367B"><span id="translatedtitle">Predicting the Invasion Potential of a Puerto Rican Frog in Hawaii using <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bisrat, S. A.; White, M. A.</p> <p>2008-12-01</p> <p>The Puerto Rican coqui frog (Eleutherodactylus coqui, hereafter coqui), which was introduced into Hawaii accidentally via commercial nurseries, is an aggressive invasive species in Hawaii. The coqui threatens Hawaii's unique ecological communities because it predates upon endemic invertebrates, which comprise the large majority of Hawaii's endemic fauna. Coqui frogs also affect real estate valuations because of their loud mating calls. Despite this widespread problem, the potential coqui range in Hawaii is currently unknown, making control and management efforts difficult. We fitted linear discriminant analysis (LDA), logistic regression (LR) via generalized linear models (GLMs), generalized additive models (GAMs), classification trees (CTs), random forests (RF), and support vector machine (SVM) to model the species distribution and map their invasion potential. We used five <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery-derived biophysical variables as explanatory variables: leaf area index (LAI), fraction of photosynthetically active radiation absorbed by vegetation (FPAR), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and land surface temperature (LST) from three <span class="hlt">MODIS</span> products: MOD11 (LST), MOD13 (LAI and FPAR), and MOD15 (Vegetation Index) (collection 4). We used 2000-2005 <span class="hlt">MODIS</span> data from <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span> to generate monthly climatologies for each biophysical variable. We collected presence/absence data from Puerto Rico and Hawaii using a 1 km grid overlaid over the entire islands of Puerto Rico and the Island of Hawaii by sampling every other pixel of the grid intersecting with the road network. We then used the dataset from Puerto Rico to train the six models while the Hawaii dataset was used as a test set. All six models predicted the invasion potential of coqui frogs in Hawaii with a moderate success with mean Kappa value of 0.31, mean area under the curve of receiver operating characteristics (AUC) of 0.75 and mean classification</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMIN21C1489H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMIN21C1489H"><span id="translatedtitle">Community Access to <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Reprojection and Reduction Pipeline and Data Sets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hendrix, V.; Li, J.; Jackson, K.; Ramakrishnan, L.; Ryu, Y.; Beattie, K.; Morin, C.; Skinner, D.; van Ingen, C.; Agarwal, D.</p> <p>2012-12-01</p> <p>Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), the key instrument aboard NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, continuously generates data as the <span class="hlt">satellites</span> cover the entire surface of earth every one to two days. This data is important to many scientific analyses, however, data procurement and processing can be challenging and cumbersome for user communities. Our current work is focused on enabling calculations using a combination of land and atmosphere products over land. Before performing the calculation the data must be downloaded and transformed, from a swath space and time system to a sinusoidal tiling system. Downloading data for a single product for an entire year can take several days for a single product and involves downloading via FTP many small files (on average ~83,000 files) in hierarchical data format (HDF4). The data processing, a swath-to-sinusoidal reprojection, is computationally intensive and currently available community tools only work for single sinusoidal tiles. We have developed a data-processing pipeline that downloads the <span class="hlt">MODIS</span> products and reprojects them on HPC systems. HPC systems do not traditionally run these high-throughput data-intensive jobs and hence we need to address unique challenges for our pipeline. The first stage in the pipeline uses a catalog to determine what files need to be downloaded and downloads identified data sets. The downloaded files will in the future trigger an event that causes the reprojection job to be entered into a job queue. The output data is stored in an archival system. The resulting reprojected data will soon be widely available to the community through a front-end web portal. The portal will allow users to download reprojected data (~1 TB/year) for the following land and atmosphere products: MODO4_L2 (Aerosol), MOD05_L2 (Water Vapor), MOD06_L2 (Cloud), MOD07_L2 (Atmosphere Profile) and MOD11_L2 (Land Surface Temperature Emissivity). In this talk we will describe the architecture of the overall</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9644E..1SZ','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9644E..1SZ"><span id="translatedtitle">Impact of climate and anthropogenic changes on urban surface albedo assessed from time-series <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zoran, Maria A.; Dida, Adrian I.; Zoran, Liviu Florin V.</p> <p>2015-10-01</p> <p>Urbanization may be considered the most significant anthropogenic force that has brought about fundamental changes in urban land cover and landscape pattern around the globe, being one of the crucial issues of global change in the 21st century affecting urban ecosystem. In the physical climate system, land surface albedo determines the radiation balance of the surface and affects the surface temperature and boundary-layer structure of the atmosphere. Due to anthropogenic and natural factors, urban land covers changes result is the land surfaces albedo changes. The main aim of this paper is to investigate the albedo patterns dynamics due to the impact of atmospheric pollution and climate variations on land cover of Bucharest metropolitan area, Romania based on <span class="hlt">satellite</span> remote sensing <span class="hlt">MODIS</span> Terra/<span class="hlt">Aqua</span> (Moderate Imaging Spectroradiometer) data over 2000-2014 time period. This study is based on <span class="hlt">MODIS</span> derived biogeophysical parameters land surface BRDF/albedo products and in-situ monitoring ground data (as air temperature, aerosols distribution, relative humidity, etc.). For urban land cover changes over the same investigated period have been used also IKONOS <span class="hlt">satellite</span> data. Due to deforestation in the periurban areas albedo changes appear to be the most significant biogeophysical effect in temperate forests. As the physical climate system is very sensitive to surface albedo, urban/periurban vegetation systems could significantly feedback to the projected climate change modeling scenarios through albedo changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010SPIE.7807E..0GD','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010SPIE.7807E..0GD"><span id="translatedtitle">Space environment's effect on <span class="hlt">MODIS</span> calibration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dodd, J. L.; Wenny, B. N.; Chiang, K.; Xiong, X.</p> <p>2010-09-01</p> <p>The MODerate resolution Imaging Spectroradiometer flies on board the Earth Observing System (EOS) <span class="hlt">satellites</span> Terra and <span class="hlt">Aqua</span> in a sun-synchronous orbit that crosses the equator at 10:30 AM and 2:30 PM, respectively, at a low earth orbit (LEO) altitude of 705 km. Terra was launched on December 18,1999 and <span class="hlt">Aqua</span> was launched on May 4, 2002. As the <span class="hlt">MODIS</span> instruments on board these <span class="hlt">satellites</span> continue to operate beyond the design lifetime of six years, the cumulative effect of the space environment on <span class="hlt">MODIS</span> and its calibration is of increasing importance. There are several aspects of the space environment that impact both the top of atmosphere (TOA) calibration and, therefore, the final science products of <span class="hlt">MODIS</span>. The south Atlantic anomaly (SAA), spacecraft drag, extreme radiative and thermal environment, and the presence of orbital debris have the potential to significantly impact both <span class="hlt">MODIS</span> and the spacecraft, either directly or indirectly, possibly resulting in data loss. Efforts from the Terra and <span class="hlt">Aqua</span> Flight Operations Teams (FOT), the <span class="hlt">MODIS</span> Instrument Operations Team (IOT), and the <span class="hlt">MODIS</span> Characterization Support Team (MCST) prevent or minimize external impact on the TOA calibrated data. This paper discusses specific effects of the space environment on <span class="hlt">MODIS</span> and how they are minimized.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1211733Z&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1211733Z&link_type=ABSTRACT"><span id="translatedtitle">A better understanding of cloud optical thickness derived from the passive sensors <span class="hlt">MODIS/AQUA</span> and POLDER/PARASOL in the A-train constellation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, S.; Cornet, C.; Parol, F.; Riedi, J.; Thieuleux, F.</p> <p>2012-05-01</p> <p>Cloud optical thickness (COT) is one of the most important parameter for the characterization of cloud in the Earth radiative budget. Its retrieval strongly depends on instrument characteristics and on many cloud and environment factors. Using coincident observations from POLDER/PARASOL and <span class="hlt">MODIS/AQUA</span> in the A-train constellation, geographical distributions and seasonal changes of COT are presented, in good agreement with general cloud climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial resolution, cloud inhomogeneity and microphysical assumptions are also discussed. Comparisons of COT derived from POLDER and <span class="hlt">MODIS</span> illustrate that as the primary factor, the sensor spatial resolution impacts COT retrievals and statistics through both cloud detection and sub-pixel cloud inhomogeneity sensitivity. The uncertainties associated to cloud microphysics assumptions, namely cloud phase, particle size and shape, also impact significantly COT retrievals. For clouds with unambiguous cloud phase, strong correlations exist between the two COTs, with <span class="hlt">MODIS</span> values comparable to POLDER ones for liquid clouds and <span class="hlt">MODIS</span> values larger than POLDER ones for ice clouds. The large differences observed in ice phase cases are due to the use of different microphysical models in the two retrieval schemes. In cases when the two sensors disagree on cloud phase decision, COT retrieved assuming liquid phase are systematically larger. The angular biases related to specific observation geometries are also quantified and discussed in particular based on POLDER observations. Those exhibit a clear increase of COT with decreasing sun elevation and a decrease of COT in forward scattering directions due to sub-pixel inhomogeneities and shadowing effects, this especially for lower sun. It also demonstrates unrealistic COT variations in the rainbow and backward directions due to inappropriate cloud optical properties representation and an important increase of COT in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9218E..1PG','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9218E..1PG"><span id="translatedtitle">Status of time-dependent response versus scan-angle (RVS) for Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> reflective solar bands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Geng, Xu; Angal, Amit; Sun, Junqiang; Chen, Hongda; Wu, Aisheng; Li, Yonghong; Link, Daniel; Xiong, Xiaoxiong</p> <p>2014-09-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) has 20 reflective solar bands (RSB), which are calibrated using a solar diffuser (SD) and near-monthly scheduled lunar observations via a space view (SV) port. The sensor responses observed at two different angles of incidence (AOI) from the SD and lunar measurements are used to track the on-orbit RSB gain changes as well as the response versus scan-angle (RVS) changes. The <span class="hlt">MODIS</span> RSB have experienced wavelength dependent degradation since launch with the larger degradation observed at the shorter wavelengths. In addition to the SD and lunar observations, the <span class="hlt">MODIS</span> Characterization Support Team (MCST) regularly monitors the response trending at multiple AOI over selected desert sites. In Collection 6 (C6), a new algorithm using the EV measurements from pseudoinvariant desert sites was developed to better characterize the <span class="hlt">MODIS</span> scan-angle dependence and it led to a significant improvement in the long-term calibration consistency of the <span class="hlt">MODIS</span> Level 1B (L1B) products. This approach is formulated for all RSB, and its application was recently extended to Terra band 10, leading to a significant improvement in the ocean-color products. This paper discusses the current status and performance of the on-orbit RVS characterization as applied in C6. Also, the various challenges and future improvement strategies associated with trending the EV response for the high-gain ocean bands are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H34A..07M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H34A..07M"><span id="translatedtitle">Detection of Harmful Algal Blooms in the Optically Complex Coastal Waters of the Kuwait Bay using <span class="hlt">Aqua-MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manche, C. J.; Sultan, M.; Uddin, S.; Al-Dousari, A.; Chouinard, K.</p> <p>2013-12-01</p> <p>In the optically complex coastal marine waters of the Kuwait Bay, the propagation of Harmful Algal Blooms (HABs) has become a severe issue over the last decade affecting aquaculture a primary component of the Kuwaiti economy. Although several remote sensing based methods of algal bloom detection exist today, few may accurately detect the concentration and identify the type of HABs in Case II waters. The purpose of this study is: (1) assessment of the method that best detects and identifies algal blooms in general and HABs in particular, in the Kuwait Bay, and (2) identification of the factors controlling the occurrence of HABs. Fluorescence Line Height (FLH), Empirical, Bio-Optical, and Operational Methods as well as Ocean Colour 3 Band Ratio (OC3M), Garver-Siegel-Maritorena Model (GSM), and General Inherent Optical Property (GIOP) Chlorophyll-a (Chl-a) algorithms were applied to Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) images acquired (07/2002 to 07/2012) over the Kuwait Bay and areas as far east as Shatt Al-Arab and as far south as N. 29.284 (Lat.), E. 50.047 (Long.) decimal degrees. In-situ data (bloom days: 50; sampling locations: 64) collected (09/1999 to 07/2011) from the Kuwait Bay was provided by the Kuwait Institute for Scientific Research and was used to test the reliability of the <span class="hlt">satellite</span>-based inferences. Tasks accomplished and findings reached include: (1) comparison of in situ to estimated OC3M, GSM, and GIOP chlorophyll concentrations over the sampling locations for the time period 2002 to 2009 showed that OC3M outperformed the two other techniques in predicting the observed distribution and in replicating the measured concentration of the in-situ Chl-a data; (2) applying the OC3M algorithm to a total of 4039 scenes and using threshold values of 3, 4, and 5 mg/m3 Chl-a concentrations we inferred 371, 202, and 124 occurrences in the Kuwait Bay that met their respective threshold; (3) applying the operational method we successfully</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT.......118L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT.......118L"><span id="translatedtitle">Evaluation of Aerosol Pollution Determination From <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Retrievals for Semi-Arid Reno, NV, USA with In-Situ Measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Loria-Salazar, S. Marcela</p> <p></p> <p>The aim of the present work is to carry out a detailed analysis of ground and columnar aerosol properties obtained by in-situ Photoacoustic and Integrated Nephelometer (PIN), Cimel CE-318 sunphotometer and <span class="hlt">MODIS</span> instrument onboard <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span>, for semi-arid Reno, Nevada, USA in the local summer months of 2012. <span class="hlt">Satellite</span> determination of local aerosol pollution is desirable because of the potential for broad spatial and temporal coverage. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from <span class="hlt">satellite</span> measurements is challenging because of the underlying surface albedo being heterogeneous in space and time. Therefore, comparisons of <span class="hlt">satellite</span> retrievals with measurements from ground-based sun photometers are crucial for validation, testing, and further development of instruments and retrieval algorithms. Ground-based sunphotometry and in-situ ground observations show that seasonal weather changes and fire plumes have great influence on the atmosphere aerosol optics. The Apparent Optical Height (AOH) follows the shape of the development of the Convective Boundary Layer (CBL) when fire conditions were not present. However, significant fine particle optical depth was inferred beyond the CBL thereby complicating the use of remote sensing measurements for near-ground aerosol pollution measurements. A meteorological analysis was performed to help diagnose the nature of the aerosols above Reno. The calculation of a Zephyr index and back trajectory analysis demonstrated that a local circulation often induces aerosol transport from Northern CA over the Sierra Nevada Mountains that doubles the Aerosol Optical Depth (AOD) at 500 nm. Sunphotometer measurements were used as a `ground truth' for <span class="hlt">satellite</span> retrievals to evaluate the current state of the science retrievals in this challenging location. <span class="hlt">Satellite</span> retrieved for AOD showed the presence of wild fires in Northern CA during August. AOD retrieved using the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..11.2680P&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..11.2680P&link_type=ABSTRACT"><span id="translatedtitle">Evaluating <span class="hlt">MODIS</span> <span class="hlt">satellite</span> versus terrestrial data driven productivity estimates in Austria</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Petritsch, R.; Boisvenue, C.; Pietsch, S. A.; Hasenauer, H.; Running, S. W.</p> <p>2009-04-01</p> <p>Sensors, such as the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on NASA's Terra <span class="hlt">satellite</span>, 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 <span class="hlt">satellite</span> 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 <span class="hlt">MODIS</span> and available on the internet; (ii) estimates resulting from the off-line version of the <span class="hlt">MODIS</span> 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 <span class="hlt">satellite</span>-driven and ground-based predictions, only latitude and longitude for each site were used to obtain <span class="hlt">MODIS</span> estimates. Along with the comparison of the different methods, we discuss problems like the differing dates of field campaigns (<1999) and acquisition of <span class="hlt">satellite</span> images (2000-2005) or incompatible productivity definitions within the methods and come up with a framework for combining terrestrial and <span class="hlt">satellite</span> data based productivity estimates. On average <span class="hlt">MODIS</span> 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 <span class="hlt">satellite</span>-derived versus terrestrial estimates are relatively poor. Considering the different scales as they are 9km² from <span class="hlt">MODIS</span> and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008SPIE.7081E..0AC','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008SPIE.7081E..0AC"><span id="translatedtitle">On-orbit <span class="hlt">aqua</span> <span class="hlt">MODIS</span> modulation transfer function trending in along-scan from the Spectro-Radiometric Calibration Assembly</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Choi, Taeyoung; Che, Nianzeng; Xiong, Xiaoxiong</p> <p>2008-08-01</p> <p>The Spectro-Radiometric Calibration Assembly (SRCA) is one of the on-board calibrators for the <span class="hlt">MODIS</span> instrument. The SRCA is operated in three modes: spectral, spatial, and radiometric. The spatial mode is used to track the changes in band-to-band registration both along-scan (band and detector) and along-track (band) and the MTF in the along-scan direction for all 36 <span class="hlt">MODIS</span> bands over the <span class="hlt">MODIS</span> lifetime. In the SRCA spatial mode, a rectangular knife-edge reticle, located at the focus of the SRCA collimator, is imaged onto four <span class="hlt">MODIS</span> Focal Plane Assemblies (FPA). The reticle is illuminated by a spherical integration sphere and a glow-bar so that all bands can have an appropriate signal level. When the <span class="hlt">MODIS</span> scan mirror rotates, the illuminated knife-edge scans across the bands/detectors. In addition, there are five electronic phase-delays so that the sampling spacing is reduced to 1/5 of the detector size, which results in dense data points. After combining detector responses from all phase-delays, a combined bell-shaped response profile is formed. The derivative of the detector response to the knife-edge is the Line Spread Function (LSF). In the frequency domain, the Modulation Transfer Functions (MTF) are calculated from the normalized Fourier transform of the LSF. The MTF results from the SRCA are validated by the pre-launch results from the Integrated Alignment Collimator (IAC) and a SRCA collection performed in the Thermal Vacuum (TV). The six-year plus on-orbit MTF trending results show very stable responses in the VIS and NIR FPAs, and meet the design specifications. Although there are noticeable MTF degradations over the instrument lifetime in bands 1 and 2, they are negligible with the large specification margins. In addition, a similar relationship is found between the band locations in the VIS and NIR FPAs versus MTF values.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26878641','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26878641"><span id="translatedtitle">Climatology and trends of aerosol optical depth over the Mediterranean basin during the last 12years (2002-2014) based on Collection 006 <span class="hlt">MODIS-Aqua</span> data.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Floutsi, A A; Korras-Carraca, M B; Matsoukas, C; Hatzianastassiou, N; Biskos, G</p> <p>2016-05-01</p> <p>The Mediterranean basin is a region of particular interest for studying atmospheric aerosols due to the large variety of air masses it receives, and its sensitivity to climate change. In this study we use the newest collection (C006) of aerosol optical depth from <span class="hlt">MODIS-Aqua</span>, from which we also derived the fine-mode fraction and Ångström exponent over the last 12years (i.e., from 2002 to 2014), providing the longest analyzed dataset for this region. The long-term regional optical depth average is 0.20±0.05, with the indicated uncertainty reflecting the inter-annual variability. Overall, the aerosol optical depth exhibits a south-to-north decreasing gradient and an average decreasing trend of 0.0030 per year (19% total decrease over the study period). The correlation between the reported AOD observations with measurements from the ground AERONET stations is high (R=0.76-0.80 depending on the wavelength), with the <span class="hlt">MODIS-Aqua</span> data being slightly overestimated. Both fine-fraction and Ångström exponent data highlight the dominance of anthropogenic aerosols over the northern, and of desert aerosols over the southern part of the region. Clear intrusions of desert dust over the Eastern Mediterranean are observed principally in spring, and in some cases in winter. Dust intrusions dominate the Western Mediterranean in the summer (and sometimes in autumn), whereas anthropogenic aerosols dominate the sub-region of the Black Sea in all seasons but especially during summer. Fine-mode optical depth is found to decrease over almost all areas of the study region during the 12-year period, marking the decreasing contribution of anthropogenic particulate matter emissions over the study area. Coarse-mode aerosol load also exhibits an overall decreasing trend. However, its decrease is smaller than that of fine aerosols and not as uniformly distributed, underlining that the overall decrease in the region arises mainly from reduced anthropogenic emissions. PMID:26878641</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171846','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171846"><span id="translatedtitle">The EOS <span class="hlt">Aqua</span>/Aura Experience: Lessons Learned on Design, Integration, and Test of Earth-Observing <span class="hlt">Satellites</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nosek, Thomas P.</p> <p>2004-01-01</p> <p>NASA and NOAA earth observing <span class="hlt">satellite</span> programs are flying a number of sophisticated scientific instruments which collect data on many phenomena and parameters of the earth's environment. The NASA Earth Observing System (EOS) Program originated the EOS Common Bus approach, which featured two spacecraft (<span class="hlt">Aqua</span> and Aura) of virtually identical design but with completely different instruments. Significant savings were obtained by the Common Bus approach and these lessons learned are presented as information for future program requiring multiple busses for new diversified instruments with increased capabilities for acquiring earth environmental data volume, accuracy, and type.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030053180&hterms=star+tracker&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dstar%2Btracker','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030053180&hterms=star+tracker&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dstar%2Btracker"><span id="translatedtitle">Performance of the Star Tracker Lightshades on the Earth Observing <span class="hlt">Satellite</span> (EOS) <span class="hlt">Aqua</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kenney, Thomas; Schroeder, Michael; Donnelly, Michael; McNally, Mark; Bauer, Frank H. (Technical Monitor)</p> <p>2003-01-01</p> <p>The TRW built EOS <span class="hlt">Aqua</span> spacecraft uses two Ball Aerospace CT-602 star trackers to provide attitude updates to the 3-axis, zero momentum, controller. Two months prior to the scheduled launch of <span class="hlt">Aqua</span>, Ball reported an error in the design of the star tracker lightshades. The lightshades, which had been designed specifically for the EOS Common spacecraft, were not expected to meet the stray light rejection requirements of the mission and thus impact the overall spacecraft pointing performance. What ensued was an effort to characterize the actual performance of the existing shade design, determine what could be done within the physical envelope available, and modify the hardware to meet requirements. Changes were made based on this review activity and <span class="hlt">Aqua</span> was launched on May 4, 2002. To date the spacecraft is meeting all of its science pointing requirements. Reported here are the lightshade design predictions, test results, and the measured on orbit performance of these shades.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030022762','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030022762"><span id="translatedtitle">Performance of the Star Tracker Lightshades on the Earth Observing <span class="hlt">Satellite</span> (EOS) <span class="hlt">Aqua</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kenny, Thomas; Lee, Albert; Donnelly, Michael; Schroder, Michael; McNally, Mark</p> <p>2003-01-01</p> <p>The TRW built EOS <span class="hlt">Aqua</span> spacecraft uses two Ball Aerospace CT-602 star trackers to provide attitude updates to the 3-axis, zero momentum, controller. Two months prior to the scheduled launch of <span class="hlt">Aqua</span>, Ball reported an error in the design of the star tracker lightshades. The lightshades, which had been designed specifically for the EOS Common spacecraft, were not expected to meet the stray light rejection requirements of the mission, thus impacting the overall spacecraft pointing performance. What ensued was an effort to characterize the actual performance of the existing shade design, determine what could be done within the physical envelope available, and modify the hardware to meet requirements. Changes were made based on this review activity and <span class="hlt">Aqua</span> was launched on May 4, 2002. To date the spacecraft is meeting all of its science pointing requirements. Reported here are the lightshade design predictions, test results, and the measured on orbit performance of these shades.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011581','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011581"><span id="translatedtitle">Recent Progress on Deep Blue Aerosol Algorithm as Applied TO <span class="hlt">MODIS</span>, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other <span class="hlt">Satellite</span> Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina; Bettenhausen, Corey; Sawyer, Andrew; Tsay, Si-Chee</p> <p>2012-01-01</p> <p>The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/<span class="hlt">MODIS</span> in 1999, and <span class="hlt">Aqua/MODIS</span> in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/<span class="hlt">MODIS</span> aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / <span class="hlt">MODIS</span> aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-reflecting surfaces into Sea WiFS / <span class="hlt">MODIS</span> as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/<span class="hlt">MODIS</span> retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other <span class="hlt">satellite</span> measurements. The trends observed in global aerosol</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005953&hterms=Earth+Day&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DEarth%2BDay','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005953&hterms=Earth+Day&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DEarth%2BDay"><span id="translatedtitle">Cross-Calibration of Earth Observing System Terra <span class="hlt">Satellite</span> Sensors <span class="hlt">MODIS</span> and ASTER</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>McCorkel, J.</p> <p>2014-01-01</p> <p>The Advanced Spaceborne Thermal Emissive and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) are two of the five sensors onboard the Earth Observing System's Terra <span class="hlt">satellite</span>. 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 <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span>. Despite differences in spectral band properties and spatial scales, ASTER-<span class="hlt">MODIS</span> 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 <span class="hlt">satellite</span> sensor pairs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040013011&hterms=orders+production&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dorders%2Bproduction','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040013011&hterms=orders+production&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dorders%2Bproduction"><span id="translatedtitle">Ocean Primary Production Estimates from Terra <span class="hlt">MODIS</span> and Their Dependency on <span class="hlt">Satellite</span> Chlorophyll Alpha Algorithms</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Essias, Wayne E.; Abbott, Mark; Carder, Kendall; Campbell, Janet; Clark, Dennis; Evans, Robert; Brown, Otis; Kearns, Ed; Kilpatrick, Kay; Balch, W.</p> <p>2003-01-01</p> <p>Simplistic models relating global <span class="hlt">satellite</span> ocean color, temperature, and light to ocean net primary production (ONPP) are sensitive to the accuracy and limitations of the <span class="hlt">satellite</span> estimate of chlorophyll and other input fields, as well as the primary productivity model. The standard <span class="hlt">MODIS</span> ONPP product uses the new semi-analytic chlorophyll algorithm as its input for two ONPP indexes. The three primary <span class="hlt">MODIS</span> chlorophyll Q estimates from <span class="hlt">MODIS</span>, as well as the SeaWiFS 4 chlorophyll product, were used to assess global and regional performance in estimating ONPP for the full mission, but concentrating on 2001. The two standard ONPP algorithms were examined with 8-day and 39 kilometer resolution to quantify chlorophyll algorithm dependency of ONPP. Ancillary data (MLD from FNMOC, <span class="hlt">MODIS</span> SSTD1, and PAR from the GSFC DAO) were identical. The standard <span class="hlt">MODIS</span> ONPP estimates for annual production in 2001 was 59 and 58 GT C for the two ONPP algorithms. Differences in ONPP using alternate chlorophylls were on the order of 10% for global annual ONPP, but ranged to 100% regionally. On all scales the differences in ONPP were smaller between <span class="hlt">MODIS</span> and SeaWiFS than between ONPP models, or among chlorophyll algorithms within <span class="hlt">MODIS</span>. Largest regional ONPP differences were found in the Southern Ocean (SO). In the SO, application of the semi-analytic chlorophyll resulted in not only a magnitude difference in ONPP (2x), but also a temporal shift in the time of maximum production compared to empirical algorithms when summed over standard oceanic areas. The resulting increase in global ONPP (6-7 GT) is supported by better performance of the semi-analytic chlorophyll in the SO and other high chlorophyll regions. The differences are significant in terms of understanding regional differences and dynamics of ocean carbon transformations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080008851','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080008851"><span id="translatedtitle">Mapping Historic Gypsy Moth Defoliation with <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data: Implications for Forest Threat Early Warning System</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spurce, Joseph P.; Hargrove, William; Ryan, Robert E.; Smooth, James C.; Prados, Don; McKellip, Rodney; Sader, Steven A.; Gasser, Jerry; May, George</p> <p>2008-01-01</p> <p>This viewgraph presentation reviews a project, the goal of which is to study the potential of <span class="hlt">MODIS</span> data for monitoring historic gypsy moth defoliation. A NASA/USDA Forest Service (USFS) partnership was formed to perform the study. NASA is helping USFS to implement <span class="hlt">satellite</span> data products into its emerging Forest Threat Early Warning System. The latter system is being developed by the USFS Eastern and Western Forest Threat Assessment Centers. The USFS Forest Threat Centers want to use <span class="hlt">MODIS</span> time series data for regional monitoring of forest damage (e.g., defoliation) preferably in near real time. The study's methodology is described, and the results of the study are shown.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007087','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007087"><span id="translatedtitle">Trends in <span class="hlt">MODIS</span> Geolocation Error Analysis</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wolfe, R. E.; Nishihama, Masahiro</p> <p>2009-01-01</p> <p>Data from the two <span class="hlt">MODIS</span> instruments have been accurately geolocated (Earth located) to enable retrieval of global geophysical parameters. The authors describe the approach used to geolocate with sub-pixel accuracy over nine years of data from M0DIS on NASA's E0S Terra spacecraft and seven years of data from <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> spacecraft. The approach uses a geometric model of the <span class="hlt">MODIS</span> instruments, accurate navigation (orbit and attitude) data and an accurate Earth terrain model to compute the location of each <span class="hlt">MODIS</span> pixel. The error analysis approach automatically matches <span class="hlt">MODIS</span> imagery with a global set of over 1,000 ground control points from the finer-resolution Landsat <span class="hlt">satellite</span> to measure static biases and trends in the MO0lS geometric model parameters. Both within orbit and yearly thermally induced cyclic variations in the pointing have been found as well as a general long-term trend.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A23A0931T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A23A0931T"><span id="translatedtitle">Estimation Accuracy of air Temperature and Water Vapor Amount Above Vegetation Canopy Using <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tomosada, M.</p> <p>2005-12-01</p> <p>Estimation accuracy of the air temperature and water vapor amount above vegetation canopy using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data is indicated at AGU fall meeting. The air temperature and water vapor amount which are satisfied the multilayer energy budget model from the ground surface to the atmosphere are estimated. Energy budget models are described the fluxes of sensible heat and latent heat exchange for the ground surface and the vegetated surface. Used <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data is the vegetated surface albedo which is calculated from visible and near infrared band data, the vegetated surface temperature, NDVI (Normalized Difference Vegetation Index), LAI (Leaf Area Index). Estimation accuracy of air temperature and water vapor amount above vegetation canopy is evaluated comparing with the value which is measured on a flux research tower in Tomakomai northern forest of Japan. Meteorological parameters such as temperature, wind speed, water vapor amount, global solar radiation are measured on a flux tower from the ground to atmosphere. Well, <span class="hlt">MODIS</span> <span class="hlt">satellite</span> observes at day and night, and it snows in Tomakomai in winter. Therefore, estimation accuracy is evaluated dividing on at daytime, night, snowfall day, and not snowfall day. There is the investigation of the undeveloped region such as dense forest and sea in one of feature of <span class="hlt">satellite</span> observation. Since there is almost no meteorological observatory at the undeveloped region so far, it is hard to get the meteorological parameters. Besides, it is the one of the subject of <span class="hlt">satellite</span> observation to get the amount of physical parameter. Although the amount of physical parameter such as surface temperature and concentration of chlorophyll-a are estimated by <span class="hlt">satellite</span>, air temperature and amount of water vapor above vegetation canopy have not been estimated by <span class="hlt">satellite</span>. Therefore, the estimation of air temperature and water vapor amount above vegetation canopy using <span class="hlt">satellite</span> data is significant. Further, a highly accurate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ThApC.124..461S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ThApC.124..461S"><span id="translatedtitle">Seasonal evaluation of evapotranspiration fluxes from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> and mesoscale model downscaled global reanalysis datasets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Petropoulos, George P.; Gupta, Manika; Dai, Qiang</p> <p>2016-04-01</p> <p>Reference evapotranspiration (ETo) is an important variable in hydrological modeling, which is not always available, especially for ungauged catchments. <span class="hlt">Satellite</span> data, such as those available from the MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), and global datasets via the European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis (ERA) interim and National Centers for Environmental Prediction (NCEP) reanalysis are important sources of information for ETo. This study explored the seasonal performances of <span class="hlt">MODIS</span> (MOD16) and Weather Research and Forecasting (WRF) model downscaled global reanalysis datasets, such as ERA interim and NCEP-derived ETo, against ground-based datasets. Overall, on the basis of the statistical metrics computed, ETo derived from ERA interim and <span class="hlt">MODIS</span> were more accurate in comparison to the estimates from NCEP for all the seasons. The pooled datasets also revealed a similar performance to the seasonal assessment with higher agreement for the ERA interim (r = 0.96, RMSE = 2.76 mm/8 days; bias = 0.24 mm/8 days), followed by <span class="hlt">MODIS</span> (r = 0.95, RMSE = 7.66 mm/8 days; bias = -7.17 mm/8 days) and NCEP (r = 0.76, RMSE = 11.81 mm/8 days; bias = -10.20 mm/8 days). The only limitation with downscaling ERA interim reanalysis datasets using WRF is that it is time-consuming in contrast to the readily available <span class="hlt">MODIS</span> operational product for use in mesoscale studies and practical applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2186332','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2186332"><span id="translatedtitle">Net primary productivity of forest stands in New Hampshire estimated from Landsat and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Potter, Christopher; Gross, Peggy; Genovese, Vanessa; Smith, Marie-Louise</p> <p>2007-01-01</p> <p>Background A simulation model that relies on <span class="hlt">satellite</span> observations of vegetation cover from the Landsat 7 sensor and from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was used to estimate net primary productivity (NPP) of forest stands at the Bartlett Experiment Forest (BEF) in the White Mountains of New Hampshire. Results Net primary production (NPP) predicted from the NASA-CASA model using 30-meter resolution Landsat inputs showed variations related to both vegetation cover type and elevational effects on mean air temperatures. Overall, the highest predicted NPP from the NASA-CASA model was for deciduous forest cover at low to mid-elevation locations over the landscape. Comparison of the model-predicted annual NPP to the plot-estimated values showed a significant correlation of R2 = 0.5. Stepwise addition of 30-meter resolution elevation data values explained no more than 20% of the residual variation in measured NPP patterns at BEF. Both the Landsat 7 and the 250-meter resolution <span class="hlt">MODIS</span> derived mean annual NPP predictions for the BEF plot locations were within ± 2.5% of the mean of plot estimates for annual NPP. Conclusion Although <span class="hlt">MODIS</span> imagery cannot capture the spatial details of NPP across the network of closely spaced plot locations as well as Landsat, the <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data as inputs to the NASA-CASA model does accurately predict the average annual productivity of a site like the BEF. PMID:17941989</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H54C..06P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H54C..06P"><span id="translatedtitle">Impacts of Reprojection and Sampling of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Images on Estimating Crop Evapotranspiration Using METRIC model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pun, M.; Kilic, A.; Allen, R.</p> <p>2014-12-01</p> <p>Landsat <span class="hlt">satellite</span> images have been used frequently to map evapotranspiration (ET) andbiophysical variables at the field scale with surface energy balance algorithms. Although Landsat images have high spatial resolution with 30m cell size, it has limitations for real time monitoring of crop ET by providing only two to four images per month for an area, which, when encountered with cloudy days, further deteriorates the availability of images and snapshots of ET behavior. Therefore real time monitoring essentially has to include near-daily thermal <span class="hlt">satellites</span> such as <span class="hlt">MODIS</span>/VIIRS into the time series. However, the challenge with field scale monitoring with these systems is the large size of the thermal band which is 375 m with VIIRS and 1000 meter with <span class="hlt">MODIS</span>. To maximize the accuracy of ET estimates during infusion of <span class="hlt">MODIS</span> products into land surface models for monitoring field scale ET, it is important to assess the geometric accuracy of the various <span class="hlt">MODIS</span> products, for example, spatial correspondence among the 250 m red and near-infrared bands, the 500 m reflectance bands; and the 1000 m thermal bands and associated products. METRIC model was used with <span class="hlt">MODIS</span> images to estimate ET from irrigated and rainfed fields in Nebraska. Our objective was to assess geometric accuracy of <span class="hlt">MODIS</span> image layers and how to correctly handle these data for highest accuracy of estimated ET at the individual field scale during the extensive drought of 2012. For example, the particular tool used to subset and reproject <span class="hlt">MODIS</span> swath images from level-1 and level-2 products (e.g., using the MRTSwath and other tools), the initial starting location (upper left hand corner), and the projection system all effect how pixel corners of the various resolution bands align. Depending on the approach used, origin of pixel corners can vary from image to image date and therefore impacts the pairing of ET information from multiple dates the consistency and accuracy of sampling ET from within field interiors</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMIN23C1439F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMIN23C1439F"><span id="translatedtitle"><span class="hlt">Satellite</span>DL - An IDL Toolkit for the Analysis of <span class="hlt">Satellite</span> Earth Observations - GOES, <span class="hlt">MODIS</span>, VIIRS and CERES</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fillmore, D. W.; Galloy, M. D.; Kindig, D.</p> <p>2013-12-01</p> <p><span class="hlt">Satellite</span>DL is an IDL toolkit for the analysis of <span class="hlt">satellite</span> Earth observations from a diverse set of platforms and sensors. The design features an abstraction layer that allows for easy inclusion of new datasets in a modular way. The core function of the toolkit is the spatial and temporal alignment of <span class="hlt">satellite</span> swath and geostationary data. IDL has a powerful suite of statistical and visualization tools that can be used in conjunction with <span class="hlt">Satellite</span>DL. Our overarching objective is to create utilities that automate the mundane aspects of <span class="hlt">satellite</span> data analysis, are extensible and maintainable, and do not place limitations on the analysis itself. Toward this end we have constructed <span class="hlt">Satellite</span>DL to include (1) HTML and LaTeX API document generation, (2) a unit test framework, (3) automatic message and error logs, (4) HTML and LaTeX plot and table generation, and (5) several real world examples with bundled datasets available for download. For ease of use, datasets, variables and optional workflows may be specified in a flexible format configuration file. Configuration statements may specify, for example, a region and date range, and the creation of images, plots and statistical summary tables for a long list of variables. <span class="hlt">Satellite</span>DL enforces data provenance; all data should be traceable and reproducible. The output NetCDF file metadata holds a complete history of the original datasets and their transformations, and a method exists to reconstruct a configuration file from this information. Release 0.1.0 of <span class="hlt">Satellite</span>DL is anticipated for the 2013 Fall AGU conference. It will distribute with ingest methods for GOES, <span class="hlt">MODIS</span>, VIIRS and CERES radiance data (L1) as well as select 2D atmosphere products (L2) such as aerosol and cloud (<span class="hlt">MODIS</span> and VIIRS) and radiant flux (CERES). Future releases will provide ingest methods for ocean and land surface products, gridded and time averaged datasets (L3 Daily, Monthly and Yearly), and support for 3D products such as temperature and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080023286','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080023286"><span id="translatedtitle"><span class="hlt">MODIS</span> Land Data Products: Generation, Quality Assurance and Validation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Masuoka, Edward; Wolfe, Robert; Morisette, Jeffery; Sinno, Scott; Teague, Michael; Saleous, Nazmi; Devadiga, Sadashiva; Justice, Christopher; Nickeson, Jaime</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) on-board NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> <span class="hlt">Satellites</span> are key instruments for providing data on global land, atmosphere, and ocean dynamics. Derived <span class="hlt">MODIS</span> land, atmosphere and ocean products are central to NASA's mission to monitor and understand the Earth system. NASA has developed and generated on a systematic basis a suite of <span class="hlt">MODIS</span> products starting with the first Terra <span class="hlt">MODIS</span> data sensed February 22, 2000 and continuing with the first <span class="hlt">MODIS-Aqua</span> data sensed July 2, 2002. The <span class="hlt">MODIS</span> Land products are divided into three product suites: radiation budget products, ecosystem products, and land cover characterization products. The production and distribution of the <span class="hlt">MODIS</span> Land products are described, from initial software delivery by the <span class="hlt">MODIS</span> Land Science Team, to operational product generation and quality assurance, delivery to EOS archival and distribution centers, and product accuracy assessment and validation. Progress and lessons learned since the first <span class="hlt">MODIS</span> data were in early 2000 are described.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040031528&hterms=Siri&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSiri','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040031528&hterms=Siri&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSiri"><span id="translatedtitle">Accessing and Understanding <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Leptoukh, Gregory; Jenkerson, Calli B.; Jodha, Siri</p> <p>2003-01-01</p> <p>The National Aeronautics and Space Administration (NASA) launched the Terra <span class="hlt">satellite</span> in December 1999, as part of the Earth Science Enterprise promotion of interdisciplinary studies of the integrated Earth system. <span class="hlt">Aqua</span>, the second <span class="hlt">satellite</span> from the series of EOS constellation, was launched in May 2002. Both <span class="hlt">satellites</span> carry the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument. <span class="hlt">MODIS</span> data are processed at the Goddard Space Flight Center, Greenbelt, MD, and then archived and distributed by the Distributed Active Archive Centers (DAACs). Data products from the <span class="hlt">MODIS</span> sensors present new challenges to remote sensing scientists due to specialized production level, data format, and map projection. <span class="hlt">MODIS</span> data are distributed as calibrated radiances and as higher level products such as: surface 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. <span class="hlt">MODIS</span> data are stored in HDF- EOS format in both swath format and in several different map projections. This tutorial guides users through data set characteristics as well as search and order interfaces, data unpacking, data subsetting, and potential applications of the data. A CD-ROM with sample data sets, and software tools for working with the data will be provided to the course participants.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A23G..02G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A23G..02G&link_type=ABSTRACT"><span id="translatedtitle">Investigating the impact of haze on cloud detection of passive <span class="hlt">satellite</span> by comparing <span class="hlt">MODIS</span>, CloudSat and CALIPSO</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gong, W.; Mao, F.</p> <p>2015-12-01</p> <p>The cloud detection algorithm for passive sensors is usually based on a fuzzy logic system with thresholds determined from previous observations. In recent years, haze and high aerosol concentrations with high AOD occur frequently in China and may critically impact the accuracy of the <span class="hlt">MODIS</span> cloud detection. Thus, we comprehensively explore this impact by comparing the results from <span class="hlt">MODIS/Aqua</span> (passive sensor), CALIOP/CALIPSO (lidar sensor), and CPR/CloudSat (microwave sensor) of the A-Train suite of instruments using an averaged AOD as an index for an aerosol concentration value. Case studies concerning the comparison of the three sensors indicate that <span class="hlt">MODIS</span> cloud detection is reduced during haze events. In addition, statistical studies show that an increase in AOD creates an increase in the percentage of uncertain flags and a decrease in hit rate, a consistency index between consecutive sets of cloud retrievals. Therefore, we can conclude that the ability of <span class="hlt">MODIS</span> cloud detection is weakened by large concentrations of aerosols. This suggests that use of the <span class="hlt">MODIS</span> cloud mask, and derived higher level products, in situations with haze requires caution. Further improvement of this retrieval algorithm, is desired as haze studies based on <span class="hlt">MODIS</span> products are of great interest in a number of related fields.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.usgs.gov/fs/2008/3061/','USGSPUBS'); return false;" href="http://pubs.usgs.gov/fs/2008/3061/"><span id="translatedtitle">Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Overview</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>U.S. Geological Survey</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is an instrument that collects remotely sensed data used by scientists for monitoring, modeling, and assessing the effects of natural processes and human actions on the Earth's surface. The continual calibration of the <span class="hlt">MODIS</span> instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make <span class="hlt">MODIS</span> images a valuable time series (2000-present) of geophysical and biophysical land-surface measurements. Carried on two National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) <span class="hlt">satellites</span>, <span class="hlt">MODIS</span> acquires morning (EOS-Terra) and afternoon (EOS-<span class="hlt">Aqua</span>) views almost daily. Terra data acquisitions began in February 2000 and <span class="hlt">Aqua</span> data acquisitions began in July 2002. Land data are generated only as higher-level products, removing the burden of common types of data processing from the user community. <span class="hlt">MODIS</span>-based products describing ecological dynamics, radiation budget, and land cover are projected onto a sinusoidal mapping grid and distributed as 10- by 10-degree tiles at 250-, 500-, or 1,000-meter spatial resolution. Some products are also created on a 0.05-degree geographic grid to support climate modeling studies. All <span class="hlt">MODIS</span> products are distributed in the Hierarchical Data Format-Earth Observing System (HDF-EOS) file format and are available through file transfer protocol (FTP) or on digital video disc (DVD) media. Versions 4 and 5 of <span class="hlt">MODIS</span> land data products are currently available and represent 'validated' collections defined in stages of accuracy that are based on the number of field sites and time periods for which the products have been validated. Version 5 collections incorporate the longest time series of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015IJAEO..36...94A&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015IJAEO..36...94A&link_type=ABSTRACT"><span id="translatedtitle"><span class="hlt">Satellite</span>-based automated burned area detection: A performance assessment of the <span class="hlt">MODIS</span> MCD45A1 in the Brazilian savanna</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Araújo, Fernando Moreira De; Ferreira, Laerte G.</p> <p>2015-04-01</p> <p>Burnings, which cause major changes to the environment, can be effectively monitored via <span class="hlt">satellite</span> data, regarding both the identification of active fires and the estimation of burned areas. Among the many orbital sensors suitable for mapping burned areas on global and regional scales, the moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>), on board the Terra and <span class="hlt">Aqua</span> platforms, has been the most widely utilized. In this study, the performance of the <span class="hlt">MODIS</span> MCD45A1 burned area product was thoroughly evaluated in the Brazilian savanna, the second largest biome in South America and a global biodiversity hotspot, characterized by a conspicuous climatic seasonality and the systematic occurrence of natural and anthropogenic fires. Overall, September MCD45A1 polygons (2000-2012) compared well to the Landsat-based reference mapping (r2 = 0.92) and were closely accompanied, on a monthly basis, by MOD14 and MYD14 hotspots (r2 = 0.89), although large omissions errors, linked to landscape patterns, structures, and overall conditions depicted in each reference image, were observed. In spite of its spatial and temporal limitations, the MCD45A1 product proved instrumental for mapping and understanding fire behavior and impacts on the Cerrado landscapes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120012563','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120012563"><span id="translatedtitle">Moisture Fluxes Derived from EOS <span class="hlt">Aqua</span> <span class="hlt">Satellite</span> Data for the North Water Polynya Over 2003-2009</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Boisvert, Linette N.; Markus, Thorsten; Parkinson, Claire L.; Vihma, Timo</p> <p>2012-01-01</p> <p><span class="hlt">Satellite</span> data were applied to calculate the moisture flux from the North Water polynya during a series of events spanning 2003-2009. The fluxes were calculated using bulk aerodynamic formulas with the stability effects according to the Monin-Obukhov similarity theory. Input parameters were taken from three sources: air relative humidity, air temperature, and surface temperature from the Atmospheric Infrared Sounder (AIRS) onboard NASA's Earth Observing System (EOS) <span class="hlt">Aqua</span> <span class="hlt">satellite</span>, sea ice concentration from the Advanced Microwave Scanning Radiometer (AMSR-E, also onboard <span class="hlt">Aqua</span>), and wind speed from the ECMWF ERA-Interim reanalysis. Our results show the progression of the moisture fluxes from the polynya during each event, as well as their atmospheric effects after the polynya has closed up. These results were compared to results from studies on other polynyas, and fall within one standard deviation of the moisture flux estimates from these studies. Although the estimated moisture fluxes over the entire study region from AIRS are smaller in magnitude than ERA-Interim, they are more accurate due to improved temperature and relative humidity profiles and ice concentration estimates over the polynya. Error estimates were calculated to be 5.56 x10(exp -3) g/sq. m/ s, only 25% of the total moisture flux, thus suggesting that AIRS and AMSR-E can be used with confidence to study smaller scale features in the Arctic sea ice pack and can capture their atmospheric effects. These findings bode well for larger-scale studies of moisture fluxes over the entire Arctic Ocean and the thinning ice pack.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1616014H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1616014H"><span id="translatedtitle">Aerosol radiative effects over global arid and semi-arid regions based on <span class="hlt">MODIS</span> Deep Blue <span class="hlt">satellite</span> observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hatzianastassiou, Nikolaos; Papadimas, Christos D.; Gkikas, Antonis; Matsoukas, Christos; Sayer, Andrew M.; Hsu, N. Christina; Vardavas, Ilias</p> <p>2014-05-01</p> <p>Aerosols are a key parameter for several atmospheric processes related to weather and climate of our planet. Specifically, the aerosol impact on Earth's climate is exerted and quantified through their radiative effects, which are induced by their direct, indirect and semi-direct interactions with radiation, in particular at short wavelengths (solar). It is acknowledged that the uncertainty of present and future climate assessments is mainly associated with aerosols and that a better understanding of their physico-chemical, optical and radiative effects is needed. The contribution of <span class="hlt">satellites</span> to this aim is important as a complementary tool to climate and radiative transfer models, as well as to surface measurements, since space observations of aerosol properties offer an extended spatial coverage. However, such <span class="hlt">satellite</span> based aerosol properties and associated model radiation computations have suffered from unavailability over highly reflecting surfaces, namely polar and desert areas. This is also the case for <span class="hlt">MODIS</span> which, onboard the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, has been providing high quality aerosol data since 2000 and 2002, respectively. These data, more specifically the aerosol optical depth (AOD) which is the most important optical property used in radiative and climate models, are considered to be of best quality. In order to address this problem, the <span class="hlt">MODIS</span> Deep Blue (DB) algorithm has been developed which enables the retrieval of AOD above arid and semi-arid areas of the globe, including the major deserts. In the present study we make use of the FORTH detailed spectral radiative transfer model (RTM) with <span class="hlt">MODIS</span> DB AOD data, supplemented with single scattering albedo (SSA) and asymmetry parameter (AP) aerosol data from the Global Aerosol DataSet (GADS) to estimate the aerosol DREs over the arid and semi-arid regions of the globe. The RTM is run using surface and atmospheric data from the ISCCP-D2 dataset and the NCEP global reanalysis project and computes the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70042059','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70042059"><span id="translatedtitle">Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Boken, Vijendra K.; Easson, Gregory L.; Rowland, James</p> <p>2010-01-01</p> <p>The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) 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 <span class="hlt">satellite</span> data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with <span class="hlt">MODIS</span>-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and <span class="hlt">MODIS</span>-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 <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACP....1513113K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACP....1513113K"><span id="translatedtitle">The regime of aerosol asymmetry parameter over Europe, the Mediterranean and the Middle East based on <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data: evaluation against surface AERONET measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korras-Carraca, M. B.; Hatzianastassiou, N.; Matsoukas, C.; Gkikas, A.; Papadimas, C. D.</p> <p>2015-11-01</p> <p>Atmospheric particulates are a significant forcing agent for the radiative energy budget of the Earth-atmosphere system. The particulates' interaction with radiation, which defines their climate effect, is strongly dependent on their optical properties. In the present work, we study one of the most important optical properties of aerosols, the asymmetry parameter (gaer), over sea surfaces of the region comprising North Africa, the Arabian Peninsula, Europe, and the Mediterranean Basin. These areas are of great interest, because of the variety of aerosol types they host, both anthropogenic and natural. Using <span class="hlt">satellite</span> data from the collection 051 of <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer, Terra and <span class="hlt">Aqua</span>), we investigate the spatiotemporal characteristics of the asymmetry parameter. We generally find significant spatial variability, with larger values over regions dominated by larger size particles, e.g., outside the Atlantic coasts of northwestern Africa, where desert-dust outflow takes place. The gaer values tend to decrease with increasing wavelength, especially over areas dominated by small particulates. The intra-annual variability is found to be small in desert-dust areas, with maximum values during summer, while in all other areas larger values are reported during the cold season and smaller during the warm. Significant intra-annual and inter-annual variability is observed around the Black Sea. However, the inter-annual trends of gaer are found to be generally small. Although <span class="hlt">satellite</span> data have the advantage of broad geographical coverage, they have to be validated against reliable surface measurements. Therefore, we compare <span class="hlt">satellite</span>-measured values with gaer values measured at 69 stations of the global surface AERONET (Aerosol Robotic Network), located within our region of interest. This way, we provide some insight on the quality and reliability of <span class="hlt">MODIS</span> data. We report generally better agreement at the wavelength of 860 nm (correlation</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ACPD...1422677K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ACPD...1422677K"><span id="translatedtitle">The regime of aerosol asymmetry parameter over Europe, Mediterranean and Middle East based on <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data: evaluation against surface AERONET measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korras-Carraca, M. B.; Hatzianastassiou, N.; Matsoukas, C.; Gkikas, A.; Papadimas, C. D.</p> <p>2014-09-01</p> <p>Atmospheric particulates are a significant forcing agent for the radiative energy budget of the Earth-atmosphere system. The particulates' interaction with radiation, which defines their climate effect, is strongly dependent on their optical properties. In the present work, we study one of the most important optical properties of aerosols, the asymmetry parameter (gaer), in the region comprised of North Africa, the Arabian peninsula, Europe, and the Mediterranean basin. These areas are of great interest, because of the variety of aerosol types they host, both anthropogenic and natural. Using <span class="hlt">satellite</span> data from the collection 051 of <span class="hlt">MODIS</span> (MODerate resolution Imaging Spectroradiometer, Terra and <span class="hlt">Aqua</span>), we investigate the spatio-temporal characteristics of the asymmetry parameter. We generally find significant spatial variability, with larger values over regions dominated by larger size particles, e.g. outside the Atlantic coasts of north-western Africa, where desert-dust outflow is taking place. The gaer values tend to decrease with increasing wavelength, especially over areas dominated by small particulates. The intra-annual variability is found to be small in desert-dust areas, with maximum values during summer, while in all other areas larger values are reported during the cold season and smaller during the warm. Significant intra-annual and inter-annual variability is observed around the Black Sea. However, the inter-annual trends of gaer are found to be generally small. Although <span class="hlt">satellite</span> data have the advantage of broad geographical coverage, they have to be validated against reliable surface measurements. Therefore, we compare <span class="hlt">satellite</span>-based values with gaer values measured at 69 stations of the global surface network AERONET (Aerosol Robotic Network), located within our region of interest. This way, we provide some insight on the quality and reliability of <span class="hlt">MODIS</span> data. We report generally better agreement at the wavelength of 870 nm (correlation coefficient</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70032007','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70032007"><span id="translatedtitle">Detection rates of the <span class="hlt">MODIS</span> active fire product in the United States</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hawbaker, T.J.; Radeloff, V.C.; Syphard, A.D.; Zhu, Z.; Stewart, S.I.</p> <p>2008-01-01</p> <p><span class="hlt">MODIS</span> active fire data offer new information about global fire patterns. However, uncertainties in detection rates can render <span class="hlt">satellite</span>-derived fire statistics difficult to interpret. We evaluated the <span class="hlt">MODIS</span> 1??km daily active fire product to quantify detection rates for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> sensors, examined how cloud cover and fire size affected detection rates, and estimated how detection rates varied across the United States. <span class="hlt">MODIS</span> active fire detections were compared to 361 reference fires (??? 18??ha) that had been delineated using pre- and post-fire Landsat imagery. Reference fires were considered detected if at least one <span class="hlt">MODIS</span> active fire pixel occurred within 1??km of the edge of the fire. When active fire data from both <span class="hlt">Aqua</span> and Terra were combined, 82% of all reference fires were found, but detection rates were less for <span class="hlt">Aqua</span> and Terra individually (73% and 66% respectively). Fires not detected generally had more cloudy days, but not when the <span class="hlt">Aqua</span> data were considered exclusively. <span class="hlt">MODIS</span> detection rates decreased with fire size, and the size at which 50% of all fires were detected was 105??ha when combining <span class="hlt">Aqua</span> and Terra (195??ha for <span class="hlt">Aqua</span> and 334??ha for Terra alone). Across the United States, detection rates were greatest in the West, lower in the Great Plains, and lowest in the East. The <span class="hlt">MODIS</span> active fire product captures large fires in the U.S. well, but may under-represent fires in areas with frequent cloud cover or rapidly burning, small, and low-intensity fires. We recommend that users of the <span class="hlt">MODIS</span> active fire data perform individual validations to ensure that all relevant fires are included. ?? 2008 Elsevier Inc. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110016148&hterms=climatology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dclimatology','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110016148&hterms=climatology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dclimatology"><span id="translatedtitle">Response to Toward Unified <span class="hlt">Satellite</span> Climatology of Aerosol Properties. 3; <span class="hlt">MODIS</span> versus MISR versus AERONET</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kahn, Ralph A.; Garay, Michael J.; Nelson, David L.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Hansen, Earl G.; Remer, Lorraine A.; Tanre, Didler</p> <p>2010-01-01</p> <p>A recent paper by Mishchenko et al. compares near-coincident MISR, <span class="hlt">MODIS</span>, and AERONET aerosol optical depth (AOD), and gives a much less favorable impression of the utility of the <span class="hlt">satellite</span> products than that presented by the instrument teams and other groups. We trace the reasons for the differing pictures to whether known and previously documented limitations of the products are taken into account in the assessments. Specifically, the analysis approaches differ primarily in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account. Mishchenko et al. also do not distinguish between observational sampling differences and retrieval algorithm error. We assess the implications of the different analysis approaches, and cite examples demonstrating how the MISR and <span class="hlt">MODIS</span> aerosol products have been applied successfully to a range of scientific investigations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AtmEn..37.2403H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AtmEn..37.2403H"><span id="translatedtitle">Applications of <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data and products for monitoring air quality in the state of Texas</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hutchison, Keith D.</p> <p></p> <p>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 <span class="hlt">satellite</span> 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 <span class="hlt">satellite</span> 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 (<span class="hlt">MODIS</span>), the transport of aerosol-borne pollutants can now be monitored over land and ocean surfaces. Thus, CSR and MOD personnel have applied <span class="hlt">MODIS</span> data to several classes of pollution that routinely impact Texas air quality. Results demonstrate <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> provides the basis for developing advanced data products that will, when used in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010EGUGA..12.5532D&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010EGUGA..12.5532D&link_type=ABSTRACT"><span id="translatedtitle">Snow cover retrieval over Rhone and Po river basins from <span class="hlt">MODIS</span> optical <span class="hlt">satellite</span> data (2000-2009).</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo</p> <p>2010-05-01</p> <p>Estimation of the Snow Covered Area (SCA) is an important issue for meteorological application and hydrological modeling of runoff. With spectral bands in the visible, near and middle infrared, the <span class="hlt">MODIS</span> optical <span class="hlt">satellite</span> sensor can be used to detect snow cover because of large differences between reflectance from snow covered and snow free surfaces. At the same time, it allows separation between snow and clouds. Moreover, the sensor provides a daily coverage of large areas (2,500 km range). However, as the pixel size is 500m x 500m, a <span class="hlt">MODIS</span> pixel may be partially covered by snow, particularly in Alpine areas, where snow may not be present in valleys lying at lower altitudes. Also, variation of reflectance due to differential sunlit effects as a function of slope and aspect, as well as bidirectional effects may be present in images. Nevertheless, it is possible to estimate snow cover at the Sub-Pixel level with a relatively good accuracy and with very good results if the sub-pixel estimations are integrated for a few pixels relative to an entire watershed. Integrated into the EU-FP7 ACQWA Project (www.acqwa.ch), this approach was first applied over Alpine area of Rhone river basin upper Geneva Lake: Canton du Valais, Switzerland (5 375 km²). In a second step over Alps, rolling hills and plain areas in Po catchment for Val d'Aosta and Piemonte regions, Italy (37 190 km²). Watershed boundaries were provided respectively by GRID (Ch) and ARPA (It) partners. The complete <span class="hlt">satellite</span> images database was extracted from the U.S. <span class="hlt">MODIS</span>/NASA website (http://<span class="hlt">modis</span>.gsfc.nasa.gov/) for MOD09_B1 Reflectance images, and from the <span class="hlt">MODIS</span>/NSIDC website (http://nsidc.org/index.html) for MOD10_A2 snow cover images. Only the Terra platform was used because images are acquired in the morning and are therefore better correlated with dry snow surface, avoiding cloud coverage of the afternoon (<span class="hlt">Aqua</span> Platform). The MOD9 Image reflectance and MOD10_A2 products were respectively analyzed to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CSR...112...14C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CSR...112...14C"><span id="translatedtitle">Estimation of water turbidity and analysis of its spatio-temporal variability in the Danube River plume (Black Sea) using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Constantin, Sorin; Doxaran, David; Constantinescu, Ștefan</p> <p>2016-01-01</p> <p>Ocean colour remote sensing information brings important insights for monitoring coastal areas. These regions are home to important natural ecosystems and changes that occur here can have important impacts not only on the local environment, but also on connected wetlands or offshore areas. The present study proposes a new regional methodology for water turbidity retrieval using the <span class="hlt">MODIS</span> red band at 250 m spatial resolution in the Danube Delta coastal area. For this purpose, multiple in-situ turbidity observations were used in order to determine a valid relationship between data collected with turbidity meters and remote sensing reflectance obtained from <span class="hlt">satellite</span> data. A special attention is given to the atmospheric correction of <span class="hlt">satellite</span> data, since complex optical waters require adapted methodologies for accurate remote sensing reflectance computation. Based on products derived using the proposed algorithm, the dynamics of turbidity is evaluated for multiple time periods: from local Terra to <span class="hlt">Aqua</span> overpasses (couple of hours), daily and monthly. Results show a clear strong connection between the Danube discharge and water turbidity in the coastal area. However other environmental parameters (e.g., wind stress) also play an important role and contribute to the magnitude of the river plume extension.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007133','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007133"><span id="translatedtitle"><span class="hlt">Satellite</span> (Timed, Aura, <span class="hlt">Aqua</span>) and In Situ (Meteorological Rockets, Balloons) Measurement Comparability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schmidlin, F. J.; Goldberg, Richard A.; Feofilov, A.; Rose, R.</p> <p>2010-01-01</p> <p>Measurements using the inflatable falling sphere often are requested to provide density data in support of special sounding rocket launchings into the mesosphere and thermosphere. To insure density measurements within narrow time frames and close in space, the inflatable falling sphere is launched within minutes of the major test. Sphere measurements are reliable for the most part, however, availability of these rocket systems has become more difficult and, in fact, these instruments no longer are manufactured resulting in a reduction of the meager stockpile of instruments. Sphere measurements also are used to validate remotely measured temperatures and have the advantage of measuring small-scale atmospheric features. Even so, with the dearth of remaining falling spheres perhaps it is time to consider whether the remote measurements are mature enough to stand alone. Presented are two field studies, one in 2003 from Northern Sweden and one in 2010 from the vicinity of Kwajalein Atoll that compare temperature retrievals between <span class="hlt">satellite</span> and in situ failing spheres. The major <span class="hlt">satellite</span> instruments employed are SABER, MLS, and AIRS. The comparisons indicate that remotely measured temperatures mimic the sphere temperature measurements quite well. The data also confirm that <span class="hlt">satellite</span> retrievals, while not always at the exact location required for individual studies, are adaptable enough and highly useful. Although the falling sphere will provide a measurement at a specific location and time, <span class="hlt">satellites</span> only pass a given location daily or less often. This report reveals that averaged <span class="hlt">satellite</span> measurements can provide temperatures and densities comparable to the falling sphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010AGUFM.A13B0193S&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010AGUFM.A13B0193S&link_type=ABSTRACT"><span id="translatedtitle"><span class="hlt">Satellite</span> (Timed, Aura, <span class="hlt">Aqua</span>) and In Situ (Meteorological Rockets, Balloons) Measurement Comparability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schmidlin, F. J.; Goldberg, R. A.; Feofilov, A.; Rose, R.</p> <p>2010-12-01</p> <p>Measurements using the inflatable falling sphere often are requested to provide density data in support of special sounding rocket launchings into the mesosphere and thermosphere. To insure density measurements within narrow time frames and close in space, the inflatable falling sphere is launched within minutes of the major test. Sphere measurements are reliable for the most part, however, availability of these rocket systems has become more difficult and, in fact, these instruments no longer are manufactured resulting in a reduction of the meager stockpile of instruments. Sphere measurements also are used to validate remotely measured temperatures and have the advantage of measuring small-scale atmospheric features. Even so, with the dearth of remaining falling spheres perhaps it is time to consider whether the remote measurements are mature enough to stand alone. Presented are two field studies, one in 2003 from Northern Sweden and one in 2010 from the vicinity of Kwajalein Atoll that compare temperature retrievals between <span class="hlt">satellite</span> and in situ falling spheres. The major <span class="hlt">satellite</span> instruments employed are SABER, MLS, and AIRS. The comparisons indicate that remotely measured temperatures mimic the sphere temperature measurements quite well. The data also confirm that <span class="hlt">satellite</span> retrievals, while not always at the exact location required for individual studies, are adaptable enough and highly useful. Although the falling sphere will provide a measurement at a specific location and time, <span class="hlt">satellites</span> only pass a given location daily or less often. This report reveals that averaged <span class="hlt">satellite</span> measurements can provide temperatures and densities comparable to the falling sphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.usgs.gov/of/2010/1055/','USGSPUBS'); return false;" href="http://pubs.usgs.gov/of/2010/1055/"><span id="translatedtitle">e<span class="hlt">MODIS</span>: A User-Friendly Data Source</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jenkerson, Calli; Maiersperger, Thomas; Schmidt, Gail</p> <p>2010-01-01</p> <p>The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'e<span class="hlt">MODIS</span>' based on Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). With a more frequent repeat cycle than Landsat and higher spatial resolutions than the Advanced Very High Resolution Spectroradiometer (AVHRR), <span class="hlt">MODIS</span> is well suited for vegetation studies. For operational monitoring, however, the benefits of <span class="hlt">MODIS</span> are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. e<span class="hlt">MODIS</span> responds to a community-specific need for alternatively packaged <span class="hlt">MODIS</span> data, addressing each of these factors for real-time monitoring and historical trend analysis. e<span class="hlt">MODIS</span> processes calibrated radiance data (level-1B) acquired by the <span class="hlt">MODIS</span> sensors on the EOS Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> by combining <span class="hlt">MODIS</span> Land Science Collection 5 Atmospherically Corrected Surface Reflectance production code and USGS EROS <span class="hlt">MODIS</span> Direct Broadcast System (DBS) software to create surface reflectance and Normalized Difference Vegetation Index (NDVI) products. e<span class="hlt">MODIS</span> is produced over the continental United States and over Alaska extending into Canada to cover the Yukon River Basin. The 250-meter (m), 500-m, and 1,000-m products are delivered in Geostationary Earth Orbit Tagged Image File Format (Geo- TIFF) and composited in 7-day intervals. e<span class="hlt">MODIS</span> composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see e<span class="hlt">MODIS</span> Product Description below). For e<span class="hlt">MODIS</span> products generated over the continental United States (e<span class="hlt">MODIS</span> CONUS), the Terra (from 2000) and <span class="hlt">Aqua</span> (from 2002) records are available and continue through present time. e<span class="hlt">MODIS</span> CONUS also is generated in an expedited process that delivers a 7-day rolling composite</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/1045215','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/1045215"><span id="translatedtitle">A SOAP Web Service for accessing <span class="hlt">MODIS</span> land product subsets</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>SanthanaVannan, Suresh K; Cook, Robert B; Pan, Jerry Yun; Wilson, Bruce E</p> <p>2011-01-01</p> <p>Remote sensing data from <span class="hlt">satellites</span> have provided valuable information on the state of the earth for several decades. Since March 2000, the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor on board NASA s Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> have been providing estimates of several land parameters useful in understanding earth system processes at global, continental, and regional scales. However, the HDF-EOS file format, specialized software needed to process the HDF-EOS files, data volume, and the high spatial and temporal resolution of <span class="hlt">MODIS</span> data make it difficult for users wanting to extract small but valuable amounts of information from the <span class="hlt">MODIS</span> record. To overcome this usability issue, the NASA-funded Distributed Active Archive Center (DAAC) for Biogeochemical Dynamics at Oak Ridge National Laboratory (ORNL) developed a Web service that provides subsets of <span class="hlt">MODIS</span> land products using Simple Object Access Protocol (SOAP). The ORNL DAAC <span class="hlt">MODIS</span> subsetting Web service is a unique way of serving <span class="hlt">satellite</span> data that exploits a fairly established and popular Internet protocol to allow users access to massive amounts of remote sensing data. The Web service provides <span class="hlt">MODIS</span> land product subsets up to 201 x 201 km in a non-proprietary comma delimited text file format. Users can programmatically query the Web service to extract <span class="hlt">MODIS</span> land parameters for real time data integration into models, decision support tools or connect to workflow software. Information regarding the <span class="hlt">MODIS</span> SOAP subsetting Web service is available on the World Wide Web (WWW) at http://daac.ornl.gov/modiswebservice.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B53C0204P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B53C0204P"><span id="translatedtitle">Analysis of Water Use Efficiency derived from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> image in Northeast Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, J.; Jang, K.; Kang, S.</p> <p>2014-12-01</p> <p>Water Use Efficiency (WUE) is defined as ratio of evapotranspriation (ET) to gross primary productivity (GPP). It can detect the changes of ecosystem properties due to the variability of enviromental condition, and provide a chance to understand the linkage between carbon and water processes in terrestrial ecosystem. In a changing climate, the understanding of ecosystem functional responses to climate variability is crucial for evaluating effect. However, continental or sub-continental scale WUE analysis is were rare. In this study, WUE was estimated in the Northeast Asia using <span class="hlt">satellite</span> data from 2003 to 2010. ET and GPP were estimated using various <span class="hlt">MODIS</span> products. The estimated ET and GPP showed favorable agreements with flux tower observations. WUE in the study domain showed considerable variations according to the plant functional types and climatic and elevational gradients. The results produced in this study indicate that <span class="hlt">satellite</span> remote sensing provides a useful tool for monitoring variability of terrestrial ecosystem functions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B53B0182K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B53B0182K"><span id="translatedtitle">Detection of Burn Area and Severity with <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Images and Spatial Autocorrelation Techniques</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kaya, S.; Kavzoglu, T.; Tonbul, H.</p> <p>2014-12-01</p> <p>Effects of forest fires and implications are one of the most important natural disasters all over the world. Statistical data observed that forest fires had a variable structure in the last century in Turkey, but correspondingly the population growth amount of forest fires and burn area increase widely in recent years. Depending on this, erosion, landslides, desertification and mass loss come into existence. In addition; after forest fires, renewal of forests and vegetation are very important for land management. Classic methods used for detection of burn area and severity requires a long and challenging process due to time and cost factors. Thanks to advanced techniques used in the field of Remote Sensing, burn area and severity can be determined with high detail and precision. The purpose of this study based on blending <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectradiometer) <span class="hlt">satellite</span> images and spatial autocorrelation techniques together, thus detect burn area and severity absolutely. In this context, spatial autocorrelation statistics like Moran's I and Get is-Ord Local Gi indexes were used to measure and analyze to burned area characteristics. Prefire and postfire <span class="hlt">satellite</span> images were used to determine fire severity depending on spectral indexes corresponding to biomass loss and carbon emissivity intensities. <span class="hlt">Satellite</span> images have used for identification of fire damages and risks in terms of fire management for a long time. This study was performed using prefire and postfire <span class="hlt">satellite</span> images and spatial autocorrelation techniques to determining and analyzing forest fires in Antalya, Turkey region which serious fires occurred. In this context, this approach enables the characterization of distinctive texture of burned area and helps forecasting more precisely. Finally, it is observed that mapping of burned area and severity could be performed from local scale to national scale. Key Words: Spatial autocorrelation, <span class="hlt">MODIS</span>, Fire, Burn Severity</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040035547&hterms=aerosols+desert&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Daerosols%2Bdesert','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040035547&hterms=aerosols+desert&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Daerosols%2Bdesert"><span id="translatedtitle"><span class="hlt">MODIS</span> Retrieval of Dust Aerosol</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, Lorraine A.; Kaufman, Yoram J.; Tanre, Didier</p> <p>2003-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) currently aboard both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> 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-<span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> algorithm tends to under predict particle size because the reflectances at top of atmosphere measured by <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> Look-Up Tables were constructed from Mie theory, assuming a spherical shape. Using a combination of <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> algorithm, in lieu of the original options for large dust-like particles. The results will be analyzed and examined.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012084&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012084&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner <span class="hlt">Satellite</span> Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012063&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012063&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner <span class="hlt">Satellite</span> Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012102&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012102&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner <span class="hlt">Satellite</span> Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012085&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012085&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner <span class="hlt">Satellite</span> Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012103&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012103&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner <span class="hlt">Satellite</span> Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130014411','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130014411"><span id="translatedtitle">A Full Snow Season in Yellowstone: A Database of Restored <span class="hlt">Aqua</span> Band 6</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gladkova, Irina; Grossberg, Michael; Bonev, George; Romanov, Peter; Riggs, George; Hall, Dorothy</p> <p>2013-01-01</p> <p>The algorithms for estimating snow extent for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) optimally use the 1.6- m channel which is unavailable for <span class="hlt">MODIS</span> on <span class="hlt">Aqua</span> due to detector damage. As a test bed to demonstrate that <span class="hlt">Aqua</span> band 6 can be restored, we chose the area surrounding Yellowstone and Grand Teton national parks. In such rugged and difficult-to-access terrain, <span class="hlt">satellite</span> images are particularly important for providing an estimation of snow-cover extent. For the full 2010-2011 snow season covering the Yellowstone region, we have used quantitative image restoration to create a database of restored <span class="hlt">Aqua</span> band 6. The database includes restored radiances, normalized vegetation index, normalized snow index, thermal data, and band-6-based snow-map products. The restored <span class="hlt">Aqua</span>-band-6 data have also been regridded and combined with Terra data to produce a snow-cover map that utilizes both Terra and <span class="hlt">Aqua</span> snow maps. Using this database, we show that the restored <span class="hlt">Aqua</span>-band-6-based snow-cover extent has a comparable performance with respect to ground stations to the one based on Terra. The result of a restored band 6 from <span class="hlt">Aqua</span> is that we have an additional band-6 image of the Yellowstone region each day. This image can be used to mitigate cloud occlusion, using the same algorithms used for band 6 on Terra. We show an application of this database of restored band-6 images to illustrate the value of creating a cloud gap filling using the National Aeronautics and Space Administration s operational cloud masks and data from both <span class="hlt">Aqua</span> and Terra.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUFM.A12B0145M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUFM.A12B0145M"><span id="translatedtitle">Navy Exploitation of SeaWiFS and <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Imagery for Detection of Desert Dust Storms Over Land and Water</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Miller, S. D.</p> <p>2002-12-01</p> <p>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 <span class="hlt">Satellite</span> 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 <span class="hlt">satellite</span> 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 (<span class="hlt">MODIS</span>; aboard Earth Observing System Terra and <span class="hlt">Aqua</span> 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 <span class="hlt">MODIS</span> algorithm combines this information with that of several near-to-far infrared channels, taking advantage of unique spectral</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3170180','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3170180"><span id="translatedtitle">Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> track tiger mosquito invasion: modelling the potential distribution of Aedes albopictus in north-eastern Italy</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2011-01-01</p> <p>Background The continuing spread of the Asian tiger mosquito Aedes albopictus in Europe is of increasing public health concern due to the potential risk of new outbreaks of exotic vector-borne diseases that this species can transmit as competent vector. We predicted the most favorable areas for a short term invasion of Ae. albopictus in north-eastern Italy using reconstructed daily <span class="hlt">satellite</span> data time series (<span class="hlt">MODIS</span> Land Surface Temperature maps, LST). We reconstructed more than 11,000 daily <span class="hlt">MODIS</span> LST maps for the period 2001-09 (i.e. performed spatial and temporal gap-filling) in an Open Source GIS framework. We aggregated these LST maps over time and identified the potential distribution areas of Ae. albopictus by adapting published temperature threshold values using three variables as predictors (0°C for mean January temperatures, 11°C for annual mean temperatures and 1350 growing degree days filtered for areas with autumnal mean temperatures > 11°C). The resulting maps were integrated into the final potential distribution map and this was compared with the known current distribution of Ae. albopictus in north-eastern Italy. Results LST maps show the microclimatic characteristics peculiar to complex terrains, which would not be visible in maps commonly derived from interpolated meteorological station data. The patterns of the three indicator variables partially differ from each other, while winter temperature is the determining limiting factor for the distribution of Ae. albopictus. All three variables show a similar spatial pattern with some local differences, in particular in the northern part of the study area (upper Adige valley). Conclusions Reconstructed daily land surface temperature data from <span class="hlt">satellites</span> can be used to predict areas of short term invasion of the tiger mosquito with sufficient accuracy (200 m pixel resolution size). Furthermore, they may be applied to other species of arthropod of medical interest for which temperature is a relevant</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011AGUFM.U41B0013G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011AGUFM.U41B0013G&link_type=ABSTRACT"><span id="translatedtitle"><span class="hlt">Aqua</span> Education and Public Outreach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Graham, S. M.; Parkinson, C. L.; Chambers, L. H.; Ray, S. E.</p> <p>2011-12-01</p> <p>NASA's <span class="hlt">Aqua</span> <span class="hlt">satellite</span> was launched on May 4, 2002, with six instruments designed to collect data about the Earth's atmosphere, biosphere, hydrosphere, and cryosphere. Since the late 1990s, the <span class="hlt">Aqua</span> mission has involved considerable education and public outreach (EPO) activities, including printed products, formal education, an engineering competition, webcasts, and high-profile multimedia efforts. The printed products include <span class="hlt">Aqua</span> and instrument brochures, an <span class="hlt">Aqua</span> lithograph, <span class="hlt">Aqua</span> trading cards, NASA Fact Sheets on <span class="hlt">Aqua</span>, the water cycle, and weather forecasting, and an <span class="hlt">Aqua</span> science writers' guide. On-going formal education efforts include the Students' Cloud Observations On-Line (S'COOL) Project, the MY NASA DATA Project, the Earth System Science Education Alliance, and, in partnership with university professors, undergraduate student research modules. Each of these projects incorporates <span class="hlt">Aqua</span> data into its inquiry-based framework. Additionally, high school and undergraduate students have participated in summer internship programs. An earlier formal education activity was the <span class="hlt">Aqua</span> Engineering Competition, which was a high school program sponsored by the NASA Goddard Space Flight Center, Morgan State University, and the Baltimore Museum of Industry. The competition began with the posting of a Round 1 <span class="hlt">Aqua</span>-related engineering problem in December 2002 and concluded in April 2003 with a final round of competition among the five finalist teams. The <span class="hlt">Aqua</span> EPO efforts have also included a wide range of multimedia products. Prior to launch, the <span class="hlt">Aqua</span> team worked closely with the Special Projects Initiative (SPI) Office to produce a series of live webcasts on <span class="hlt">Aqua</span> science and the Cool Science website <span class="hlt">aqua</span>.nasa.gov/coolscience, which displays short video clips of <span class="hlt">Aqua</span> scientists and engineers explaining the many aspects of the <span class="hlt">Aqua</span> mission. These video clips, the <span class="hlt">Aqua</span> website, and numerous presentations have benefited from dynamic visualizations showing the <span class="hlt">Aqua</span> launch</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.B33D1589J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.B33D1589J"><span id="translatedtitle">Estimation of Net Radiation and Evapotranspiration in California Using <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jin, Y.; Randerson, J. T.; Goulden, M. L.</p> <p>2007-12-01</p> <p>Soil moisture links surface energy, water and biogeochemical cycles by several different pathways, including by influencing the partitioning of energy into latent and sensible heat and by regulating NPP and heterotrophic respiration fluxes. Evapotranspiration (ET) is a major pathway for water loss and its seasonal variation affects the seasonality of soil moisture and subsequently net ecosystem exchange. We developed an empirical ET algorithm using Ameriflux data and <span class="hlt">MODIS</span> leaf area index to improve the estimation of soil moisture in CASA biogeochemical model at a regional scale. We estimated net radiation (Rn) using <span class="hlt">MODIS</span> BRDF/albedo and skin temperature/emissivity products. A good agreement was found between <span class="hlt">satellite</span>-based estimates and field- measured Rn from SURFRAD, Ameriflux, and 6 recently installed flux towers in southern California, with an absolute difference below 30 W m-2. The ground heat flux component of available energy was estimated using the fraction of vegetation derived from <span class="hlt">MODIS</span> NDVI. We parameterized the Priestly-Taylor coefficient with leaf area index and soil moisture at an 8-day time scale using multi-year data from the Ameriflux sites. We validated this algorithm using ET measurements from May 2006 to April 2007 in southern California tower sites. The spatial distribution of annual mean Rn over California showed an increasing trend from desert to grassland ecosystems, and from grasslands to forests, reflecting decreasing albedo and surface temperature with increasing vegetation cover fraction. The Priestly-Taylor coefficients followed the phenology and the seasonality of soil moisture reasonably well, which leads to higher ET in spring rather than in summer- when Rn peaks. The seasonal cycle of net ecosystem exchange predicted by CASA with these improvements agreed reasonably well with those derived from California's eddy covariance measurements due to the improved seasonality of soil moisture.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=201467&keyword=CO2+AND+uptake&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=65250150&CFTOKEN=13396594','EPA-EIMS'); return false;" href="http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=201467&keyword=CO2+AND+uptake&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=65250150&CFTOKEN=13396594"><span id="translatedtitle">Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data and Ecosystem Modeling</span></a></p> <p><a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>A simulation model based on <span class="hlt">satellite</span> observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Pr...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26832292','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26832292"><span id="translatedtitle">Ice cloud backscatter study and comparison with CALIPSO and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ding, Jiachen; Yang, Ping; Holz, Robert E; Platnick, Steven; Meyer, Kerry G; Vaughan, Mark A; Hu, Yongxiang; King, Michael D</p> <p>2016-01-11</p> <p>An invariant imbedding T-matrix (II-TM) method is used to calculate the single-scattering properties of 8-column aggregate ice crystals. The II-TM based backscatter values are compared with those calculated by the improved geometric-optics method (IGOM) to refine the backscattering properties of the ice cloud radiative model used in the <span class="hlt">MODIS</span> Collection 6 cloud optical property product. The integrated attenuated backscatter-to-cloud optical depth (IAB-ICOD) relation is derived from simulations using a CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span>) lidar simulator based on a Monte Carlo radiative transfer model. By comparing the simulation results and co-located CALIPSO and <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) observations, the non-uniform zonal distribution of ice clouds over ocean is characterized in terms of a mixture of smooth and rough ice particles. The percentage of the smooth particles is approximately 6% and 9% for tropical and midlatitude ice clouds, respectively. PMID:26832292</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160004967&hterms=clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dclouds','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160004967&hterms=clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dclouds"><span id="translatedtitle">Ice Cloud Backscatter Study and Comparison with CALIPSO and <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ding, Jiachen; Yang, Ping; Holz, Robert E.; Platnick, Steven; Meyer, Kerry G.; Vaughan, Mark A.; Hu, Yongxiang; King, Michael D.</p> <p>2016-01-01</p> <p>An invariant imbedding T-matrix (II-TM) method is used to calculate the single-scattering properties of 8-column aggregate ice crystals. The II-TM based backscatter values are compared with those calculated by the improved geometric-optics method (IGOM) to refine the backscattering properties of the ice cloud radiative model used in the <span class="hlt">MODIS</span> Collection 6 cloud optical property product. The integrated attenuated backscatter-to-cloud optical depth (IAB-ICOD) relation is derived from simulations using a CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span>) lidar simulator based on a Monte Carlo radiative transfer model. By comparing the simulation results and co-located CALIPSO and <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) observations, the non-uniform zonal distribution of ice clouds over ocean is characterized in terms of a mixture of smooth and rough ice particles. The percentage of the smooth particles is approximately 6 percent and 9 percent for tropical and mid-latitude ice clouds, respectively.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT........92E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT........92E"><span id="translatedtitle">Automated dust storm detection using <span class="hlt">satellite</span> images. Development of a computer system for the detection of dust storms from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> images and the creation of a new dust storm database</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>El-Ossta, Esam Elmehde Amar</p> <p></p> <p>Dust storms are one of the natural hazards, which have increased in frequency in the recent years over Sahara desert, Australia, the Arabian Desert, Turkmenistan and northern China, which have worsened during the last decade. Dust storms increase air pollution, impact on urban areas and farms as well as affecting ground and air traffic. They cause damage to human health, reduce the temperature, cause damage to communication facilities, reduce visibility which delays both road and air traffic and impact on both urban and rural areas. Thus, it is important to know the causation, movement and radiation effects of dust storms. The monitoring and forecasting of dust storms is increasing in order to help governments reduce the negative impact of these storms. <span class="hlt">Satellite</span> remote sensing is the most common method but its use over sandy ground is still limited as the two share similar characteristics. However, <span class="hlt">satellite</span> remote sensing using true-colour images or estimates of aerosol optical thickness (AOT) and algorithms such as the deep blue algorithm have limitations for identifying dust storms. Many researchers have studied the detection of dust storms during daytime in a number of different regions of the world including China, Australia, America, and North Africa using a variety of <span class="hlt">satellite</span> data but fewer studies have focused on detecting dust storms at night. The key elements of this present study are to use data from the Moderate Resolution Imaging Spectroradiometers on the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> to develop more effective automated method for detecting dust storms during both day and night and generate a <span class="hlt">MODIS</span> dust storm database..</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015444','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015444"><span id="translatedtitle">Impact of Sensor Degradation on the <span class="hlt">MODIS</span> NDVI Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, Dongdong; Morton, Douglas; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert</p> <p>2011-01-01</p> <p>Time series of <span class="hlt">satellite</span> data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent <span class="hlt">satellite</span>-based measurements. Here, we evaluated the impact of sensor degradation on trend detection using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on the Terra and <span class="hlt">Aqua</span> platforms. For Terra <span class="hlt">MODIS</span>, the impact of blue band (Band 3, 470nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004/yr decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends <span class="hlt">MODIS</span> NDVI over North America were consistent with simulated results, with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and <span class="hlt">Aqua</span> (6.7%) <span class="hlt">MODIS</span> sensors during 2002-2010. Planned adjustments to Terra <span class="hlt">MODIS</span> calibration for Collection 6 data reprocessing will largely eliminate this negative bias in NDVI trends over vegetation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140009143','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140009143"><span id="translatedtitle">Impact of Sensor Degradation on the <span class="hlt">MODIS</span> NDVI Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert</p> <p>2012-01-01</p> <p>Time series of <span class="hlt">satellite</span> data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent <span class="hlt">satellite</span>-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on the Terra and <span class="hlt">Aqua</span> platforms. For Terra <span class="hlt">MODIS</span>, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in <span class="hlt">MODIS</span> NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and <span class="hlt">Aqua</span> (6.7%) <span class="hlt">MODIS</span> sensors during 2002-2010. Planned adjustments to Terra <span class="hlt">MODIS</span> calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030096002','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030096002"><span id="translatedtitle">Sea Ice Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.</p> <p>2003-01-01</p> <p>Global sea ice products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>. Daily sea ice extent and ice-surface temperature (IST) products are available at 1- and 4-km resolution. Validation activities have been undertaken to assess the accuracy of the <span class="hlt">MODIS</span> IST product at the South Pole station in Antarctica and in the Arctic Ocean using near-surface air-temperature data from a meteorological station and drifting buoys. Results from the study areas show that under clear skies, the <span class="hlt">MODIS</span> ISTs are very close to those of the near-surface air temperatures with a bias of -1.1 and -1.2 K, and an uncertainty of 1.6 and 1.7 K, respectively. It is shown that the uncertainties would be reduced if the actual temperature of the ice surface were reported instead of the near-surface air temperature. It is not possible to get an accurate IST from <span class="hlt">MODIS</span> in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and the <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> <span class="hlt">satellite</span>, it may be possible to develop a relationship between <span class="hlt">MODIS</span>-derived IST and ice temperature derived from the AMSR-E. Since the AMSR-E measurements are generally unaffected by cloud cover, they may be used to complement the <span class="hlt">MODIS</span> IST measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.4563D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.4563D"><span id="translatedtitle">A study of the cloud cover and cloud top pressure weekly cycle over the region of Eastern Mediterranean with the use of <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dalampiras, Pashalis; Georgoulias, Aristeidis K.; Kourtidis, Konstantinos; Alexandri, Georgia; Meleti, Charoula</p> <p>2014-05-01</p> <p>In this work, the spatiotemporal variability of cloud cover (CC) and cloud top pressure (CTP) over the region of Eastern Mediterranean is presented. The analysis is based on level-2 data from <span class="hlt">MODIS</span> TERRA and <span class="hlt">AQUA</span> <span class="hlt">satellite</span> sensors for the period 3/2000-12/2012 and 7/2002-12/2012, respectively. The data used here are from the 0.1-degree aerosol-cloud gridded dataset that was compiled within the framework of QUADIEEMS project for the investigation of the aerosol indirect effects. The Weekly Cycle Index (WCI) and the day of weekly maximum/minimum patterns are calculated on a seasonal basis and their possible connections with local aerosol sources and the regional aerosol patterns are investigated. To generalize our results, the day-of-the-week variability of CC and CTP for 9 sub-regions with different aerosol characteristics is examined. Among the most striking features is a summer CC midweek minimum over the Balkan Peninsula. Contrasting this, a weekend CC minimum appears over the Aegean and the Black Sea. In spring, we observe a statistically significant weekend CC maximum over the Balkan Peninsula and the sea regions around it. The synergistic use of various <span class="hlt">satellite</span>, model and reanalysis products indicates that these regions are characterized by a strong presence of anthropogenic aerosols. The opposite behaviour is observed for CTP; however, the statistically significant weekly maxima and minima appear mostly over land. The QUADIEEMS project is co-financed by the European Social Fund (ESF) and national resources under the operational programme Education and Lifelong Learning (EdLL) within the framework of the Action "Supporting Postdoctoral Researchers".</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/18817116','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/18817116"><span id="translatedtitle">Monitoring agricultural burning in the Mississippi River Valley region from the moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>).</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Korontzi, Stefania; McCarty, Jessica; Justice, Christopher</p> <p>2008-09-01</p> <p>The 2003 active fire observations from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), on board NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, were analyzed to assess burning activity in the cropland areas of the Mississippi River Valley region. Agricultural burning was found to be an important contributor to fire activity in this region, accounting for approximately one-third of all burning. Agricultural fire activity showed two seasonal peaks: the first, smaller peak, occurring in June during the spring harvesting of wheat; and the second, bigger peak, in October during the fall harvesting of rice and soy. The seasonal signal in agricultural burning was predominantly evident in the early afternoon <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> fire detections. A strong diurnal agricultural fire signal was prevalent during the fall harvesting months, as suggested by the substantially higher number (approximately 3.5 times) of fires detected by <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> in the early afternoon, compared with those detected by <span class="hlt">MODIS</span> Terra in the morning. No diurnal variations in agricultural fire activity were apparent during the springtime wheat-harvesting season. The seasonal and diurnal patterns in agricultural fire activity detected by <span class="hlt">MODIS</span> are supported by known crop management practices in this region. <span class="hlt">MODIS</span> data provide an important means to characterize and monitor agricultural fire dynamics and management practices. PMID:18817116</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JPRS..101...47P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JPRS..101...47P"><span id="translatedtitle">Intercomparison of clumping index estimates from POLDER, <span class="hlt">MODIS</span>, and MISR <span class="hlt">satellite</span> data over reference sites</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pisek, Jan; Govind, Ajit; Arndt, Stefan K.; Hocking, Darren; Wardlaw, Timothy J.; Fang, Hongliang; Matteucci, Giorgio; Longdoz, Bernard</p> <p>2015-03-01</p> <p>Clumping index is the measure of foliage grouping relative to a random distribution of leaves in space. It is a key structural parameter of plant canopies that influences canopy radiation regimes and controls canopy photosynthesis and other land-atmosphere interactions. The Normalized Difference between Hotspot and Darkspot (NDHD) index has been previously used to retrieve global clumping index maps from POLarization and Directionality of the Earth's Reflectances (POLDER) data at ∼6 km resolution and the Bidirectional Reflectance Distribution Function (BRDF) product from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) at 500 m resolution. Most recently the algorithm was also applied with Multi-angle Imaging SpectroRadiometer (MISR) data at 275 m resolution over selected areas. In this study for the first time we characterized and compared the three products over a set of sites representing diverse biomes and different canopy structures. The products were also directly validated with both in-situ vertical profiles and available seasonal trajectories of clumping index over several sites. We demonstrated that the vertical distribution of foliage and especially the effect of understory need to be taken into account while validating foliage clumping products from remote sensing products with values measured in the field. <span class="hlt">Satellite</span> measurements responded to the structural effects near the top of canopies, while ground measurements may be biased by the lower vegetation layers. Additionally, caution should be taken regarding the misclassification in land cover maps as their errors can propagate into the foliage clumping maps. Our results indicate that <span class="hlt">MODIS</span> data and MISR data, with 275 m in particular, can provide good quality clumping index estimates at spatial scales pertinent for modeling local carbon and energy fluxes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020081319&hterms=usher&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dusher','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020081319&hterms=usher&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dusher"><span id="translatedtitle">Global Aerosol Remote Sensing from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>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)</p> <p>2002-01-01</p> <p>The physical characteristics, composition, abundance, spatial distribution and dynamics of global aerosols are still very poorly known, and new data from <span class="hlt">satellite</span> 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 (<span class="hlt">MODIS</span>) sensors aboard the Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> polar-orbiting <span class="hlt">satellites</span> ushers in a new era in aerosol remote sensing from space. Terra and <span class="hlt">Aqua</span> 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 <span class="hlt">MODIS</span> daytime data. The <span class="hlt">MODIS</span> 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-<span class="hlt">MODIS</span> 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 <span class="hlt">Aqua-MODIS</span> aerosol products. The <span class="hlt">MODIS</span> level 2 aerosol products are operationally aggregated to generate global daily, eight-day (weekly), and monthly products at one-degree spatial resolution (level 3). <span class="hlt">MODIS</span> aerosol data are used for the detailed study of local, regional, and global aerosol concentration</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21F3096B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21F3096B"><span id="translatedtitle">In-Depth Evaluation of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> Collection 6 AOD Parameters Over the Contintinental U.S. Via Comparison to Both Ground-Truth and Modeled Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Belle, J. H.; Liu, Y.</p> <p>2014-12-01</p> <p>We evaluated all four <span class="hlt">MODIS</span> Collection 6 aerosol AOD parameters: 10 km Dark-Target, 3 km Dark-Target, 10 km Deep-Blue, and 10 km merged Dark-Target and Deep-Blue over the continental U.S. for the years 2011-2013 using AERONET observations. General results of this evaluation are illustrated in the attached figure, which includes data from 84 permanent AERONET sites and 64 DRAGON sites. There are indications of positive retrieval error in the AOD over the continental U.S. for Dark-Target and merged AOD parameters, such that slopes are greater than one, and the percentage of observations above the error envelope (EE, ±(0.05 + 0.15*AERONET AOD) is greater than the percentage below. In contrast, Deep-Blue has a large number of values within the error envelope. However, the correlation with ground observations is poor (r=0.73), the bias is relatively high (0.03) and the slope is below 1 (0.77). While coverage for Deep-Blue retrievals has been improved in Collection 6, the 10 km merged parameter, while partially dependent on Deep-Blue retrievals, performs poorly with regards to coverage, particularly for lower confidence values. For this parameter, an average of only 40.2% of pixels in a valid AERONET-<span class="hlt">MODIS</span> collocation has any retrieved values. This is in comparison to 72.9% of Deep-Blue pixels and 59.5% of Dark-Target pixels in the same 10 km product. Correlation coefficients between <span class="hlt">MODIS</span> and AERONET AOD over the Western U.S. are significantly lower (between 0.67 and 0.71) than those in the East, (between 0.84 and 0.93). However, Dark-Target and merged AOD parameters from the West do not show overall positive retrieval errors, and have regression slopes against AERONET observations between 0.98 and 1.02. <span class="hlt">MODIS</span> aerosol products are further combined with information from the <span class="hlt">MODIS</span> 16-day gridded NDVI (Normalized Difference Vegetation Index) product, Global Multi-resolution Terrain Elevation Data (GMTED2010), and the National Land Cover Database (NLCD) to elucidate ground</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120007429','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120007429"><span id="translatedtitle">A Project to Map and Monitor Baldcypress Forests in Coastal Louisiana, Using Landsat, <span class="hlt">MODIS</span>, and ASTER <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spruce, Joseph; Sader, Steven; Smoot, James</p> <p>2012-01-01</p> <p>Cypress swamp forests of Louisiana offer many important ecological and economic benefits: wildlife habitat, forest products, storm buffers, water quality, and recreation. Such forests are also threatened by multiple factors: subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, hurricanes, insect and nutria damage, timber harvesting, and land use conversion. Unfortunately, there are many information gaps regarding the type, location, extent, and condition of these forests. Better more up to date swamp forest mapping products are needed to aid coastal forest conservation and restoration work (e.g., through the Coastal Forest Conservation Initiative or CFCI). In response, a collaborative project was initiated to develop, test and demonstrate cypress swamp forest mapping products, using NASA supported Landsat, ASTER, and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data. Research Objectives are: Develop, test, and demonstrate use of Landsat and ASTER data for computing new cypress forest classification products and Landsat, ASTER, and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data for detecting and monitoring swamp forest change</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.B34B..07K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.B34B..07K"><span id="translatedtitle">Terrestrial Carbon Fluxes from Deforestation in the Brazilian Amazon and Cerrado Regions Predicted from <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data and Ecosystem Modeling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klooster, S.; Potter, C.; Genovese, V.</p> <p>2008-12-01</p> <p>The NASA-CASA (Carnegie Ames Stanford Approach) simulation model based on <span class="hlt">satellite</span> observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was used to estimate tropical forest and savanna (Cerrado) carbon pools for the Brazilian Amazon region over the period 2000-2004. Adjustments for mean age of forest stands were carried out across the region, resulting in a new mapping of aboveground biomass pools based on <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data. Yearly maps of newly deforested lands from the Brazilian PRODES (Programa de calculo do desflorestamento da Amazonia ) project were combined with these NASA-CASA biomass predictions to generate seasonal budgets of potential carbon and nitrogen trace gas losses from biomass burning events. Simulations of plant residue and soil carbon decomposition were conducted in the NASA-CASA model during and following deforestation events to track the fate of aboveground biomass pools that were cut and burned each year across the region.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1714285S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1714285S"><span id="translatedtitle">Performance of <span class="hlt">MODIS</span> <span class="hlt">satellite</span> and mesoscale model based land surface temperature for soil moisture deficit estimation using Neural Network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Srivastava, Prashant K.; Petropoulos, George P.; Gupta, Manika; Islam, Tanvir</p> <p>2015-04-01</p> <p>Soil Moisture Deficit (SMD) is a key variable in the water and energy exchanges that occur at the land-surface/atmosphere interface. Monitoring SMD is an alternate method of irrigation scheduling and represents the use of the suitable quantity of water at the proper time by combining measurements of soil moisture deficit. In past it is found that LST has a strong relation to SMD, which can be estimated by <span class="hlt">MODIS</span> or numerical weather prediction model such as WRF (Weather Research and Forecasting model). By looking into the importance of SMD, this work focused on the application of Artificial Neural Network (ANN) for evaluating its capabilities towards SMD estimation using the LST data estimated from <span class="hlt">MODIS</span> and WRF mesoscale model. The benchmark SMD estimated from Probability Distribution Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the calibration and validation experiments. The performances between observed and simulated SMD are assessed in terms of the Nash-Sutcliffe Efficiency (NSE), the Root Mean Square Error (RMSE) and the percentage of bias (%Bias). The application of the ANN confirmed a high capability WRF and <span class="hlt">MODIS</span> LST for prediction of SMD. Performance during the ANN calibration and validation showed a good agreement between benchmark and estimated SMD with <span class="hlt">MODIS</span> LST information with significantly higher performance than WRF simulated LST. The work presented showed the first comprehensive application of LST from <span class="hlt">MODIS</span> and WRF mesoscale model for hydrological SMD estimation, particularly for the maritime climate. More studies in this direction are recommended to hydro-meteorological community, so that useful information will be accumulated in the technical literature domain for different geographical locations and climatic conditions. Keyword: WRF, Land Surface Temperature, <span class="hlt">MODIS</span> <span class="hlt">satellite</span>, Soil Moisture Deficit, Neural Network</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ISPAr.XL1c.371S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ISPAr.XL1c.371S"><span id="translatedtitle">a Comparison of Empirical and Inteligent Methods for Dust Detection Using <span class="hlt">Modis</span> <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shahrisvand, M.; Akhoondzadeh, M.</p> <p>2013-09-01</p> <p>Nowadays, dust storm in one of the most important natural hazards which is considered as a national concern in scientific communities. This paper considers the capabilities of some classical and intelligent methods for dust detection from <span class="hlt">satellite</span> imagery around the Middle East region. In the study of dust detection, <span class="hlt">MODIS</span> images have been a good candidate due to their suitable spectral and temporal resolution. In this study, physical-based and intelligent methods including decision tree, ANN (Artificial Neural Network) and SVM (Support Vector Machine) have been applied to detect dust storms. Among the mentioned approaches, in this paper, SVM method has been implemented for the first time in domain of dust detection studies. Finally, AOD (Aerosol Optical Depth) images, which are one the referenced standard products of OMI (Ozone Monitoring Instrument) sensor, have been used to assess the accuracy of all the implemented methods. Since the SVM method can distinguish dust storm over lands and oceans simultaneously, therefore the accuracy of SVM method is achieved better than the other applied approaches. As a conclusion, this paper shows that SVM can be a powerful tool for production of dust images with remarkable accuracy in comparison with AOT (Aerosol Optical Thickness) product of NASA.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110023010&hterms=climatology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dclimatology','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110023010&hterms=climatology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dclimatology"><span id="translatedtitle">Toward Unified <span class="hlt">Satellite</span> Climatology of Aerosol Properties. 3. <span class="hlt">MODIS</span> Versus MISR Versus AERONET</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mishchenko, Michael I.; Liu, Li; Geogdzhayev, Igor V.; Travis, Larry D.; Cairns, Brian; Lacis, Andrew A.</p> <p>2010-01-01</p> <p>We use the full duration of collocated pixel-level <span class="hlt">MODIS</span>-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual <span class="hlt">MODIS</span> and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured <span class="hlt">MODIS</span> AOTs as opposed to the use of all <span class="hlt">MODIS</span> AOTs has little effect on the resulting accuracy. The <span class="hlt">MODIS</span> and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of <span class="hlt">MODIS</span> and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level <span class="hlt">MODIS</span> and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and <span class="hlt">MODIS</span> aerosol pixels. We conclude that the likely RSTDs for this subset of <span class="hlt">MODIS</span> and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(<span class="hlt">MODIS</span>)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original <span class="hlt">MODIS</span> and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured <span class="hlt">MODIS</span> pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ACPD...1110449M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ACPD...1110449M"><span id="translatedtitle">Aerosol Climatology over Nile Delta based on <span class="hlt">MODIS</span>, MISR and OMI <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marey, H. S.; Gille, J. C.; El-Askary, H. M.; Shalaby, E. A.; El-Raey, M. E.</p> <p>2011-04-01</p> <p>Since 1999 Cairo and the Nile delta region have suffered from air pollution episodes called the "black cloud" during the fall season. These have been attributed to either burning of agriculture waste or long-range transport of desert dust. Here we present a detailed analysis of the optical and microphysical aerosol properties, based on <span class="hlt">satellite</span> data. Monthly mean values of Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aerosol optical depth (AOD) at 550 nm were examined for the 10 yr 2000-2009. Significant monthly variability is observed with maxima in April or May (~0.5) and October (~0.45), and a minimum in December and January (~0.2). Monthly mean values of UV Aerosol Index (UVAI) retrieved by the Ozone Monitoring Instrument (OMI) for 4 yr (2005-2008) exhibit the same AOD pattern. The carbonaceous aerosols during the black cloud periods are confined to the planetary boundary layer (PBL), while dust aerosols exist over a wider range of altitudes, as shown by Cloud-Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span> Observation (CALIPSO) aerosol profiles. The monthly climatology of Multi-angle Imaging SpectroRadiometer (MISR) data show that the aerosols during the black cloud periods are spherical with a higher percentage of small and medium size particles, whereas the spring aerosols are mostly large non-spherical particles. All of the results show that the air quality in Cairo and the Nile delta region is subject to a complex mixture of air pollution types, especially in the fall season, when biomass burning contributes to a background of urban pollution and desert dust.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ACP....1110637M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ACP....1110637M"><span id="translatedtitle">Aerosol climatology over Nile Delta based on <span class="hlt">MODIS</span>, MISR and OMI <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marey, H. S.; Gille, J. C.; El-Askary, H. M.; Shalaby, E. A.; El-Raey, M. E.</p> <p>2011-10-01</p> <p>Since 1999 Cairo and the Nile delta region have suffered from air pollution episodes called the "black cloud" during the fall season. These have been attributed to either burning of agriculture waste or long-range transport of desert dust. Here we present a detailed analysis of the optical and microphysical aerosol properties, based on <span class="hlt">satellite</span> data. Monthly mean values of Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aerosol optical depth (AOD) at 550 nm were examined for the 10 yr period from 2000-2009. Significant monthly variability is observed in the AOD with maxima in April or May (~0.5) and October (~0.45), and a minimum in December and January (~0.2). Monthly mean values of UV Aerosol Index (UVAI) retrieved by the Ozone Monitoring Instrument (OMI) for 4 yr (2005-2008) exhibit the same AOD pattern. The carbonaceous aerosols during the black cloud periods are confined to the planetary boundary layer (PBL), while dust aerosols exist over a wider range of altitudes, as shown by Cloud-Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span> Observation (CALIPSO) aerosol profiles. The monthly climatology of Multi-angle Imaging SpectroRadiometer (MISR) data show that the aerosols during the black cloud periods are spherical with a higher percentage of small and medium size particles, whereas the spring aerosols are mostly large non-spherical particles. All of the results show that the air quality in Cairo and the Nile delta region is subject to a complex mixture of air pollution types, especially in the fall season, when biomass burning contributes to a background of urban pollution and desert dust.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008SPIE.7104E..14P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008SPIE.7104E..14P"><span id="translatedtitle">Snow mapping for water resource management using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data in northern Xinjiang, China</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pei, Huan; Qin, Zhihao; Fang, Shifeng; Liu, Zhihui</p> <p>2008-10-01</p> <p>Snow is the most important freshwater resource in northern Xinjiang, which is a typical inland arid ecosystem in western China. Snow mapping can provide useful information for water resource management in this arid ecosystem. An applicable approach for snow mapping in Northern Xinjiang Basin using <span class="hlt">MODIS</span> data was proposed in this paper. The approach of linear spectral mixture analysis (LSMA) was used to calculate snow cover fractions within a pixel, which was used to establish a regression function with NDSI at a 250-meter grid resolution. Field campaigns were conducted to examine whether NDSI can be used to extend the utility of the snow mapping approach to obtain sub-pixel estimates of snow cover. In addition, snow depths at 80 sampling sites were collected in the study region. The correlation between image reflectivity and snow depth as well as the comparison between measured snow spectra and image spectra were analyzed. An algorithm was developed on the basis of the correlation for snow depth mapping in the region. Validation for another dataset with 50 sampling sites showed an RMSE of 1.63, indicating that the algorithm was able to provide an estimation of snow depth at an accuracy of 1.63cm. The results indicated that snow cover area can reach 81% and average snow depth was 13.8 cm in north Xinjiang in January 2005. Generally speaking, the snow cover and depth had a trend of gradually decreasing from north to south and from the surroundings to the center. Temporally, the cover reached a maximum in early January, and the depth reached a maximum was ten days later. Snow duration was so different in different regions with the Aletai region having the longest and the Bole having the shortest. In the period of snow melting, snow depth decreased earlier, afterward snow cover dwindled. Our study showed that the spatial and temporal variation of snow cover was very critical for water resource management in the arid inland region and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data provide an</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110020758','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110020758"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> Reflected Solar Calibration Uncertainty</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Sun, Junqiang; Butler, James</p> <p>2011-01-01</p> <p>Determination of the calibration accuracy and traceability of a remote sensing instrument is a driving issue in the use of <span class="hlt">satellite</span> data for calibration inter-comparisons and studying climate change. The Terra and <span class="hlt">Aqua</span> MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments have successfully operated for more than 11 and 9 years, respectively. Twenty of the thirty six <span class="hlt">MODIS</span> spectral bands are in the reflected solar region with center wavelengths ranging from 0.41 to 2.2 microns. <span class="hlt">MODIS</span> reflective solar band (RSB) on-orbit calibration is reflectance based through the use of an on-board solar diffuser (SO). The calibration uncertainty requirements are +/-2.0% for the RSB reflectance factors at sensor specified typical scene reflectances or radiances. The SO bi-directional reflectance factor (BRF) was characterized pre-launch and its on-orbit changes are tracked by an on-board solar diffuser stability monitor (SDSM). This paper provides an assessment of <span class="hlt">MODIS</span> RSB on-orbit calibration traceability and uncertainty for its Level 1B (L1B) reflectance factors. It examines in details each of the uncertainty contributors, including those from pre-launch measurements as well as on-orbit observations. Common challenging issues and differences due to individual sensors' specific characteristics and on-orbit performance are also discussed in this paper. Guidance and recommendations are presented, based on lessons from <span class="hlt">MODIS</span> RSB calibration uncertainty assessment, for the development of future instrument calibration and validation plans.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3705466','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3705466"><span id="translatedtitle">Remote Sensing of Agro-droughts in Guangdong Province of China Using <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Gao, Maofang; Qin, Zhihao; Zhang, Hong'ou; Lu, Liping; Zhou, Xia; Yang, Xiuchun</p> <p>2008-01-01</p> <p>A practical approach was developed in the study for drought monitoring in Guangdong province of China on the basis of vegetation supply water index (VSWI) and precipitation distance index (PDI). A comprehensive index for assessment of agro-drought severity (SADI) was then established from the normalized VSWI and PDI. Using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> images and precipitation data from ground-observed meteorological stations, we applied the approach to Guangdong for drought monitoring in 2006. The monitoring results showed that the drought severity on average was very low in the province during the main growing season from May to September in 2006. However, seasonal variation of the severity was also obvious in difference counties of the province. Higher severity of drought could be seen in the periods of late-June (In China each month is traditionally divided into 3 periods. Each is with 10 days and has different names. This division system is mainly with consideration of farming seasons hence has been widely used as the basis of drought monitoring periods in China. In order to keep this tradition, we define, for example, for June, the early-June as the period from 1st to 10th of June, the mid-June as the period from 11th to 20th, and the late-June as the period from 21st to 30th. So mid-August denotes the period from 11th to 20th of August, and early-July the period from 1st to 10th of July, and so on.), early-July, mid-August and late-September. Regionally, Leizhou Peninsula in the west had the most serious drought before mid-May. Validation indicated that our monitoring results were generally consistent with the drought statistics data and the results from Chinese National <span class="hlt">Satellite</span> Meteorological Center (CNSMC), which used only remote sensing data. This consistence confirmed the applicability of our approach for drought monitoring. Our better identification of drought severity in Leizhou Peninsula of western Guangdong than that of CNSMC might suggest that the approach</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=250313&keyword=hu&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=65316514&CFTOKEN=41907884','EPA-EIMS'); return false;" href="http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=250313&keyword=hu&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=65316514&CFTOKEN=41907884"><span id="translatedtitle">Assessment of <span class="hlt">satellite</span> derived diffuse attenuation coefficients and euphotic depths in south Florida coastal waters</span></a></p> <p><a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>Optical data collected in coastal waters off South Florida and in the Caribbean Sea between January 2009 and December 2010 were used to evaluate products derived with three bio-optical inversion algorithms applied to MOIDS/<span class="hlt">Aqua</span>, <span class="hlt">MODIS</span>/Terra, and SeaWiFS <span class="hlt">satellite</span> observations. Th...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100020136','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100020136"><span id="translatedtitle">Remote Sensing of the Absorption Coefficients and Chlorophyll a Concentration in the U.S. Southern Middle Atlantic Bight from SeaWiFS and <span class="hlt">MODIS-Aqua</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pan, Xiaoju; Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.</p> <p>2008-01-01</p> <p>At present, <span class="hlt">satellite</span> remote sensing of coastal water quality and constituent concentration is subject to large errors as compared to the capability of <span class="hlt">satellite</span> sensors in oceanic waters. In this study, field measurements collected on a series of cruises within U.S. southern Middle Atlantic Bight (SMAB) were applied to improve retrievals of <span class="hlt">satellite</span> ocean color products in order to examine the factors that regulate the bio-optical properties within the continental shelf waters of the SMAB. The first objective was to develop improvements in <span class="hlt">satellite</span> retrievals of absorption coefficients of phytoplankton (a(sub ph)), colored dissolved organic matter (CDOM) (a(sub g)), non-pigmented particles (a(sub d)), and non-pigmented particles plus CDOM (a(sub dg)), and chlorophyll a concentration ([Chl_a]). Several algorithms were compared to derive constituent absorption coefficients from remote sensing reflectance (R(sub rs)) ratios. The validation match-ups showed that the mean absolute percent differences (MAPD) were typically less than 35%, although higher errors were found for a(sub d) retrievals. Seasonal and spatial variability of <span class="hlt">satellite</span>-derived absorption coefficients and [Chl_a] was apparent and consistent with field data. CDOM is a major contributor to the bio-optical properties of the SMAB, accounting for 35-70% of total light absorption by particles plus CDOM at 443 nm, as compared to 30-45% for phytoplankton and 0-20% for non-pigmented particles. The overestimation of [Chl_a] from the operational <span class="hlt">satellite</span> algorithms may be attributed to the strong CDOM absorption in this region. River discharge is important in controlling the bio-optical environment, but cannot explain all of the regional and seasonal variability of biogeochemical constituents in the SMAB.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN11B1287L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN11B1287L"><span id="translatedtitle">Use Of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Images And An Atmospheric Dust Transport Model To Evaluate Juniperus Spp. Pollen Phenology And Transport</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A. R.; Nickovic, S.; Crimmins, T. M.; Van De Water, P. K.; Pejanovic, G.; Vukovic, A. J.; Myers, O.; Budge, A.; Zelicoff, A.; Bunderson, L.; Ponce-Campos, G.</p> <p>2011-12-01</p> <p>Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via <span class="hlt">satellite</span> is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and <span class="hlt">satellite</span> data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using <span class="hlt">MODIS</span> data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of <span class="hlt">satellite</span> data products for studying phenology is well documented (White and Nemani 2006). In the current project <span class="hlt">MODIS</span> data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120002863','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120002863"><span id="translatedtitle">Use of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; Van de Water, P. K.; Myers, O. B.; Budge, A. M.; Zelicoff, A. P.; Bunderson, L.; Ponce-Campos, G.; Crimmins, T. M.</p> <p>2011-01-01</p> <p>Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via <span class="hlt">satellite</span> is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and <span class="hlt">satellite</span> data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using <span class="hlt">MODIS</span> data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of <span class="hlt">satellite</span> data products for studying phenology is well documented (White and Nemani 2006). In the current project <span class="hlt">MODIS</span> data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171588','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171588"><span id="translatedtitle">Application of <span class="hlt">MODIS</span>-Derived Active Fire Radiative Energy to Fire Disaster and Smoke Pollution Monitoring</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Kaufman, Yoram J.; Hao, Wei Min; Habib, Shahid</p> <p>2004-01-01</p> <p>The radiative energy emitted by large fires and the corresponding smoke aerosol loading are simultaneously measured from the <span class="hlt">MODIS</span> sensor from both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>. Quantitative relationships between the rates of emission of fire radiative energy and smoke are being developed for different fire-prone regions of the globe. Preliminary results are presented. When fully developed, the system will enable the use of <span class="hlt">MODIS</span> direct broadcast fire data for near real-time monitoring of fire strength and smoke emission as well as forecasting of fire progression and smoke dispersion, several hours to a few days in advance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110014229','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110014229"><span id="translatedtitle">Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data and Ecosystem Modeling</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Potter, C.; Klooster, S.; Huete, A.; Genovese, V.; Bustamante, M.; Ferreira, L. Guimaraes; deOliveira, R. C., Jr.; Zepp, R.</p> <p>2009-01-01</p> <p>A simulation model based on <span class="hlt">satellite</span> observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondonia and the northern portions of the state of Par a. These areas were not significantly impacted by the 2002-2003 El Nino event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhao and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly <span class="hlt">MODIS</span> Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of <span class="hlt">MODIS</span> Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009BGeo....6..937P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009BGeo....6..937P"><span id="translatedtitle">Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data and ecosystem modeling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Potter, C.; Klooster, S.; Huete, A.; Genovese, V.; Bustamante, M.; Guimaraes Ferreira, L.; de Oliveira, R. C., Jr.; Zepp, R.</p> <p>2009-06-01</p> <p>A simulation model based on <span class="hlt">satellite</span> observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondônia and the northern portions of the state of Pará. These areas were not significantly impacted by the 2002-2003 El Niño event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhão and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly <span class="hlt">MODIS</span> Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of <span class="hlt">MODIS</span> Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009BGD.....6..947P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009BGD.....6..947P"><span id="translatedtitle">Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data and ecosystem modeling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Potter, C.; Klooster, S.; Huete, A.; Genovese, V.; Bustamante, M.; Guimaraes Ferreira, L.; Cosme de Oliveira Junior, R.; Zepp, R.</p> <p>2009-01-01</p> <p>A simulation model based on <span class="hlt">satellite</span> observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondônia and the northern portions of the state of Pará. These areas were not significantly impacted by the 2002-2003 El Niño event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhão and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly <span class="hlt">MODIS</span> Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of <span class="hlt">MODIS</span> Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9245E..1HZ','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9245E..1HZ"><span id="translatedtitle">Analysis of urbanization and climate change impacts on the urban thermal environment based on <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu A.</p> <p>2014-10-01</p> <p>Cities are exposed more and more to climate change from greenhouse gas induced radiative forcing, and localized effects from urbanization such as the urban heat island. Urban land covers as the biophysical state of the earth's surface and immediate subsurface are sources and sinks for most of the material and energy movements and interactions between the geosphere and biosphere. Climate change is considered to be the biggest environmental threat in the future in the South- Eastern part of Europe. The aim of this paper is to investigate the influences of urban growth on urban thermal environment as well as the relationships of thermal characteristics to other biophysical parameters in Bucharest metropolitan area of Romania based on time series <span class="hlt">MODIS</span> Terra/<span class="hlt">Aqua</span> and IKONOS data acquired during 2000-2014 periods. Land Surface Temperature (LST) is a key variable for studying urban land surface processes and surface atmosphere interactions, being a crucial component in the study of the surface energy and water budgets. Urbanization created an evolved inverse relationship between impervious and vegetation coverage, and brought about new LST patterns because of LST's correlations with both impervious and vegetation coverage. City thermal environment risk management strategies for mitigating and adapting to climate change must propose efficient plans to reduce greenhouse gas (GHG) emissions and cool the city through changes in the built environment, land use, and transportation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A43B0274W&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A43B0274W&link_type=ABSTRACT"><span id="translatedtitle">The resolution-dependence of <span class="hlt">satellite</span>-based cloud retrievals: First results from ASTER and <span class="hlt">MODIS</span> observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Werner, F.; Wind, G.; Zhang, Z.; Platnick, S. E.; Di Girolamo, L.</p> <p>2015-12-01</p> <p>The spatial resolution dependence of retrieved optical and microphysical cloud properties of marine shallow convective water clouds is presented using data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), as well as the Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) onboard the scientific research <span class="hlt">satellite</span> Terra. Both instruments are characterized by vastly different spatial resolutions of 15m (ASTER) and 1000m (<span class="hlt">MODIS</span>), respectively. Cloud optical thickness (τ) and effective droplet radius (reff) are derived by means of the Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system which yields <span class="hlt">MODIS</span>-like cloud property retrievals via a shared-core architecture. The retrieval algorithm employs a standard bi-spectral retrieval scheme with two reflectances (ρ) in the visible to near-infrared spectral wavelength range (VNIR, 0.86μm) and shortwave infrared spectral wavelength range (SWIR, 2.1μm), respectively. For an exemplary granule the high-resolution ρ sampled by the ASTER instrument are aggregated from 15m to an increasingly coarse spatial resolution between (30-1000m). Subsequently, retrieved τ and reff from aggregated ρ are compared to the mean of the high-resolution cloud properties within the aggregated pixels. The differences in retrieved τ and reff are related to the sub-pixel covariance of ρ in the VNIR and SWIR band, as well as the inhomogeneity index (i.e., the ratio of standard deviation to mean value of ρ in the VNIR). This analysis highlights the impact of sub-pixel inhomogeneity and plane-parallel assumptions in the cloud property retrieval. CHIMAERA also allows for a comparison of ASTER and <span class="hlt">MODIS</span> retrievals without introducing biases due to individual instrument algorithms. Retrieved τ and reff from the 1000m aggregated ρ sampled by ASTER are compared to the retrieved cloud properties provided by <span class="hlt">MODIS</span>. The presented results highlight the different</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AMTD....4.6861V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AMTD....4.6861V"><span id="translatedtitle">Analysis of co-located <span class="hlt">MODIS</span> and CALIPSO observations near clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Várnai, T.; Marshak, A.</p> <p>2011-11-01</p> <p>This paper aims at helping synergistic studies in combining data from different <span class="hlt">satellites</span> for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the <span class="hlt">MODIS</span> imager can refine our perceptions based on CALIOP lidar measurements about the systematic aerosol changes that occur near clouds. The statistical analysis of a yearlong dataset of co-located global maritime observations from the <span class="hlt">Aqua</span> and CALIPSO <span class="hlt">satellites</span> reveals that <span class="hlt">MODIS</span>'s multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on <span class="hlt">Aqua</span> and CALIPSO yield very similar pictures, and that the discrepancies - due mainly to wind drift and differences in view angle - do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, <span class="hlt">MODIS</span> reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in <span class="hlt">MODIS</span> and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when <span class="hlt">MODIS</span> cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. The global median distance to clouds in maritime clear-sky areas is in the 4-5 km range.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUSM.B41A..06L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUSM.B41A..06L"><span id="translatedtitle">Mapping high-resolution incident photosynthetically active radiation over land surfaces from <span class="hlt">MODIS</span> and GOES <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liang, S.; Wang, K.; Wang, D.; Townshend, J.; Running, S.; Tsay, S.</p> <p>2008-05-01</p> <p>Incident photosynthetically active radiation (PAR) is a key variable required by almost all terrestrial ecosystem models. Many radiation efficiency models are linearly related canopy productivity to the absorbed PAR. Unfortunately, the current incident PAR products estimated from remotely sensed data or calculated by radiation models at spatial and temporal resolutions are not sufficient for carbon cycle modeling and various applications. In this study, we aim to develop incident PAR products at one kilometer scale from multiple <span class="hlt">satellite</span> sensors, such as Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) and Geostationary Operational Environmental <span class="hlt">Satellite</span> (GOES) sensor. We first developed a look-up table approach to estimate instantanerous incident PAR product from <span class="hlt">MODIS</span> (Liang et al., 2006). The temporal observations of each pixel are used to estimate land surface reflectance and look-up tables of both aerosol and cloud are searched, based on the top-of-atmosphere reflectance and surface reflectance for determining incident PAR. The incident PAR product includes both the direct and diffuse components. The calculation of a daily integrated PAR using two different methods has also been developed (Wang, et al., 2008a). The similar algorithm has been further extended to GOES data (Wang, et al., 2008b, Zheng, et al., 2008). Extensive validation activities are conducted to evaluate the algorithms and products using the ground measurements from FLUXNET and other networks. They are also compared with other <span class="hlt">satellite</span> products. The results indicate that our approaches can produce reasonable PAR product at 1km resolution. We have generated 1km incident PAR products over North America for several years, which are freely available to the science community. Liang, S., T. Zheng, R. Liu, H. Fang, S. C. Tsay, S. Running, (2006), Estimation of incident Photosynthetically Active Radiation from <span class="hlt">MODIS</span> Data, Journal of Geophysical Research ¡§CAtmosphere. 111, D15208,doi:10</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9639E..10L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9639E..10L"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> on-orbit spatial performance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Link, Daniel; Xiong, Xiaoxiong J.; Wang, Zhipeng</p> <p>2015-10-01</p> <p>The Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> are part of NASA's Earth Observing System and both <span class="hlt">satellites</span> host a nearly-identical Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Of the 36 <span class="hlt">MODIS</span> spectral bands mounted among four Focal Plane Assemblies (FPAs) two have a 250 meter spatial resolution at nadir. Five bands have a spatial resolution of 500 meters, while the remaining bands make observations at 1 kilometer resolution. <span class="hlt">MODIS</span> is equipped with a suite of onboard calibrators to track on-orbit changes in key sensor performance parameters. The Spectro-Radiometric Calibration Assembly (SRCA) contains a calibration source that allows on-orbit assessment of <span class="hlt">MODIS</span> spatial performance, providing information on current band-to-band registration (BBR), FPA-to-FPA registration (FFR), detector-to-detector registration (DDR), modulation transfer function (MTF), and instantaneous field-of-view (IFOV). In this paper, we present the methodology of the on-orbit spatial calibrations using SRCA and the results of these key spatial parameters. The <span class="hlt">MODIS</span> spatial characteristics, measured on-orbit, are compared against design specifications and pre-launch measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020006092&hterms=Franco&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D70%26Ntt%3DFranco','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020006092&hterms=Franco&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D70%26Ntt%3DFranco"><span id="translatedtitle">The <span class="hlt">Aqua</span>-Aura Train</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schoeberl, Mark; Einaudi, Franco (Technical Monitor)</p> <p>2001-01-01</p> <p>This talk will focus on the afternoon constellation of EOS platforms and the scientific benefits that arise from this formation. The afternoon EOS constellation or the "A-train" will provide unprecedented information on clouds and aerosols. At 1:30 PM crossing time EOS-<span class="hlt">Aqua</span> begins the train with the <span class="hlt">MODIS</span>, CERES and AIRS instruments making aerosol, cloud, radiation budget , temperature and water vapor measurements. AMSR-E will also make total column water measurements. Following <span class="hlt">Aqua</span> by one minute, Cloudsat will make active radar precipitation measurements as and PICASSOCENA will make lidar measurements of clouds and aerosols. Fourteen minutes later, EOS-Aura will pass through the same space making upper troposphere water vapor and ice profiles as well as some key trace gases associated with convective processes (MLS and HIRDLS). Additional measurements of aerosols will be made by Aura's OMI instrument.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030025354&hterms=dance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Ddance','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030025354&hterms=dance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Ddance"><span id="translatedtitle"><span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data and GOCART Model Characterization of the Global Aerosol</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram; Chin, Mian; Remer, Lorraine; Tanre, Didier; Lau, William K.-M. (Technical Monitor)</p> <p>2003-01-01</p> <p>Recently produced daily <span class="hlt">MODIS</span> aerosol data for the whole year of 2001 are used to show the concentration and dynamics of aerosol over ocean and large parts of the continents. The data were validated against the Aerosol Robotic Network (AERONET) measurements over land and ocean. Monthly averages and a movie based on the daily data are produced and used to demonstrate the spatial and temporal evolution of aerosol. The <span class="hlt">MODIS</span> wide spectral range is used to distinguish fine smoke and pollution aerosol from coarse dust and salt. The aerosol is observed above ocean and land. The movie produced from the <span class="hlt">MODIS</span> data provides a new dimension to aerosol observations by showing the dynamics of the system. For example in February smoke and dust emitted from the Sahel and West Africa is shown to travel to the North-East Atlantic. In April heavy dust and pollution from East Asia is shown to travel to North America. In May-June pollution and dust play a dynamical dance in the Arabian Sea and Bay of Bengal. In Aug-September smoke from South Africa and South America is shown to pulsate in tandem and to periodically to be transported to the otherwise pristine Southern part of the Southern Hemisphere. The <span class="hlt">MODIS</span> data are compared with the GOCART model and used to estimate the first observation based direct anthropogenic radiative forcing of climate by aerosol.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110005570','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110005570"><span id="translatedtitle"><span class="hlt">Satellite</span> Monitoring of Asian Dust Storms from SeaWiFS and <span class="hlt">MODIS</span>: Source, Pathway, and Interannual Variability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina; Tsay, S.-C.; Bettenhausen, C.; Salustro, C.; Jeong, M. J.</p> <p>2010-01-01</p> <p>Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochernical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new <span class="hlt">satellite</span> algorithm to retrieve aerosol optical thickness and single scattering albedo over bright reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and <span class="hlt">MODIS</span> to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the <span class="hlt">satellite</span> retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new <span class="hlt">satellite</span> products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and <span class="hlt">MODIS</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080045439&hterms=ecosystems+population&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystems%2Bpopulation','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080045439&hterms=ecosystems+population&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystems%2Bpopulation"><span id="translatedtitle"><span class="hlt">Satellite</span> Monitoring of Asian Dust Storms from SeaWiFS and <span class="hlt">MODIS</span>: Source, pathway and Interannual Variability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina</p> <p>2007-01-01</p> <p>Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new <span class="hlt">satellite</span> algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and <span class="hlt">MODIS</span> to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the <span class="hlt">satellite</span> retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new <span class="hlt">satellite</span> products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and <span class="hlt">MODIS</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.A24C..04H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.A24C..04H"><span id="translatedtitle"><span class="hlt">Satellite</span> Monitoring of Asian Dust Storms from SeaWiFS and <span class="hlt">MODIS</span>: Source, Pathway, and Interannual Variability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hsu, N.; Tsay, S.; Jeong, M.; Holben, B.</p> <p>2006-12-01</p> <p>Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of spring-time cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such popu-lation centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new <span class="hlt">satellite</span> algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been dif-ficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and <span class="hlt">MODIS</span> to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the <span class="hlt">satellite</span> retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The compari-sons show reasonable agreements between these two. These new <span class="hlt">satellite</span> prod-ucts will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011TCD.....5.2991R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011TCD.....5.2991R"><span id="translatedtitle">Melt ponds on Arctic sea ice determined from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data using an artificial neural network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rösel, A.; Kaleschke, L.; Birnbaum, G.</p> <p>2011-10-01</p> <p>Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like <span class="hlt">MODIS</span> using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron (MLP) to reduce computational costs. Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 <span class="hlt">MODIS</span> surface reflectance product. The validation of the <span class="hlt">MODIS</span> melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC) for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors (RMSE) range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with correlations coefficients ranging from R2 = 0.28 to R2 = 0.45. The mean annual cycle of the melt pond fraction for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds from the geographical latitude, and has its maximum in mid-July in latitudes between 80° and 88° N. Furthermore, the <span class="hlt">MODIS</span> results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ASI-, NASA Team 2-, and Bootstrap-algorithms with <span class="hlt">MODIS</span> sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016IJAEO..51...37O&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016IJAEO..51...37O&link_type=ABSTRACT"><span id="translatedtitle">Use of <span class="hlt">MODIS</span> <span class="hlt">satellite</span> images for detailed lake morphometry: Application to basins with large water level fluctuations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ovakoglou, George; Alexandridis, Thomas K.; Crisman, Thomas L.; Skoulikaris, Charalampos; Vergos, George S.</p> <p>2016-09-01</p> <p>Lake morphometry is essential for managing water resources and limnetic ecosystems. For reservoirs that receive high sediment loads, frequent morphometric mapping is necessary to define both the effective life of the reservoir and its water storage capacity for irrigation, power generation, flood control and domestic water supply. The current study presents a methodology for updating the digital depth model (DDM) of lakes and reservoirs with wide intra and interannual fluctuations of water levels using <span class="hlt">satellite</span> remote sensing. A time series of Terra <span class="hlt">MODIS</span> <span class="hlt">satellite</span> images was used to map shorelines formed during the annual water level change cycle, and were validated with concurrent Landsat ETM+ <span class="hlt">satellite</span> images. The shorelines were connected with in-situ observation of water levels and were treated as elevation contours to produce the DDM using spatial interpolation. The accuracy of the digitized shorelines is within the mapping accuracy of the <span class="hlt">satellite</span> images, while the resulting DDM is validated using in-situ elevation measurements. Two versions of the DDM were produced to assess the influence of seasonal water fluctuation. Finally, the methodology was applied to Lake Kerkini (Greece) to produce an updated DDM, which was compared with the last available bathymetric survey (1991) and revealed changes in sediment distribution within the lake.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUSM.B33D..01H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUSM.B33D..01H"><span id="translatedtitle">Regional Scaling of Cropland Net Primary Production for Nebraska using <span class="hlt">Satellite</span> Remote Sensing from <span class="hlt">MODIS</span> and the Ecosystem Process Model BIOME-BGC</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heinsch, F. A.; Jolly, W. M.; Mu, Q.; Kimball, J. S.</p> <p>2005-05-01</p> <p>Crops dominate the Midwestern U.S., and this has major implications for the domestic carbon balance. This research is designed to test and improve the ability of <span class="hlt">satellite</span> remote sensing (<span class="hlt">MODIS</span>) to estimate cropland productivity through the use of field measurements and ecosystem modeling. The Biome-BGC ecosystem process model (V4.1.2) has been modified for use in agricultural systems, and tested at the field level for both C3 (soybean) and C4 (maize) crops under different irrigation regimes. Biome-BGC results are verified using local AmeriFlux network site measurements of the net CO2 flux and cropland biomass. These results are spatially aggregated within a 7x7km window centered over an intensive study area and compared with <span class="hlt">satellite</span>-derived GPP and NPP estimates from <span class="hlt">MODIS</span>. Model results are further extrapolated statewide using available estimates of crop coverage and irrigation to assess regional patterns and seasonal variability in productivity captured from both `bottom-up' ecosystem model simulations and `top-down' <span class="hlt">satellite</span> remote sensing approaches. Finally, we evaluate regional productivity differences based on model assumptions of both natural (grasslands) and agricultural land cover types, and assess the potential for improving <span class="hlt">MODIS</span> GPP and NPP algorithms for agricultural regions. Initial results indicate that the model works well in estimating productivity of both maize and soybean using different management techniques. The <span class="hlt">MODIS</span> algorithm does well when site-specific data are used, but the standard outputs from the <span class="hlt">MODIS</span> sensor differ from tower estimates of productivity, most likely a result of the scale mismatch between the two methods. We verify spatial <span class="hlt">MODIS</span> products over a heterogeneous landscape by using Biome-BGC to scale tower-specific measurements to <span class="hlt">MODIS</span> cutout sizes. These results will be used to provide estimates of the regional carbon balance for the larger 20,000 km2 area within the National Institute for Global Environmental Change</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817822L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817822L"><span id="translatedtitle">New methods for reducing cloud obscuration based on combination products of <span class="hlt">MODIS</span> and AMSR2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Muyi; Pan, Yaozhong; Zhu, Xiufang; Yin, Heyang</p> <p>2016-04-01</p> <p>As one of the main sources for water availability in semi-arid mountain regions, snow melt provides runoff and water supply for the downstream population and is of great importance for both human and environmental systems. For this reason, snow data such as snow cover (SCA) and snow depth (SD) is especially important. Snow cover has been mapped using many remote sensors in the visible, near-infrared, thermal, and microwave wavelengths. Since 1966, optical remote sensors such as AVHRR, Landsat and <span class="hlt">MODIS</span> have obtained critically important data for observing the earth's snow cover. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) employed by Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> provides spatially snow covered data with 500 m and daily temporal resolution. However the utility of the <span class="hlt">MODIS</span> snow-cover products is limited by cloud cover which causes gaps in the daily snow-cover map products. In this paper, we developed a new method in order to reduce cloud obscuration. This method includes four parts: A) Combining various <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> products; B) Temporal and spatial filtering; C) Zonal snowline approach and D) Combining the product deriving from the above three parts and the AMSR2 passive microwave snow depth product (with a spatial resolution of 10 km). In part D, the consistency of two different data (optical remote sensing data with spatial resolution of 500 m and passive microwave remote sensing data with a spatial resolution of 10 km) was evaluated. This study was carried out for Qinghai Province located in northwestern part of China during 1st, October, 2013 to 31st, March, 2015. In order to evaluate the performance of the proposed methodology, 14 <span class="hlt">MODIS</span> snow cover product tiles (with cloud coverage less than 10%) were selected as possible "ground truth" data and cloud mask was generated for each tile randomly. The results show successful performances arising from the methods applied, which resulted in all cloud coverage being removed. The overall accuracy of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016ACP....16.1255X&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016ACP....16.1255X&link_type=ABSTRACT"><span id="translatedtitle">Evaluation of VIIRS, GOCI, and <span class="hlt">MODIS</span> Collection 6 AOD retrievals against ground sunphotometer observations over East Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.</p> <p>2016-02-01</p> <p>Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, <span class="hlt">satellite</span>-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology <span class="hlt">Satellite</span> (COMS), and Terra and <span class="hlt">Aqua</span> Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra <span class="hlt">MODIS</span> C6 3 km AOD, and 16 % of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan-South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra <span class="hlt">MODIS</span>, and 56 % of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> C6 3 km AOD fell within the EE. In general, <span class="hlt">satellite</span> aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and <span class="hlt">MODIS</span> C6 3 km products had positive biases.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007001','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007001"><span id="translatedtitle">Detailed Evaluation of <span class="hlt">MODIS</span> Fire Radiative Power Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles</p> <p>2010-01-01</p> <p><span class="hlt">Satellite</span> remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the <span class="hlt">MODIS</span> sensors aboard the polar orbiting Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary <span class="hlt">satellite</span>. During the last few years, FRP has been gaining recognition as an important parameter for facilitating the development of various scientific studies relating to the quantitative characterization of biomass burning and their emissions. Therefore, we are conducting a detailed analysis of the FRP products from <span class="hlt">MODIS</span> to characterize the uncertainties associated with them, such as those due to the <span class="hlt">MODIS</span> bow-tie effects and other factors, in order to establish their error budget for use in scientific research and applications. In this presentation, we will show preliminary results of the <span class="hlt">MODIS</span> FRP data analysis, including comparisons with airborne measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A41C0078M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A41C0078M"><span id="translatedtitle">Assessing <span class="hlt">MODIS</span> Macrophysical Cloud Property Uncertainties</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maddux, B. C.; Ackerman, S. A.; Frey, R.; Holz, R.</p> <p>2013-12-01</p> <p>Cloud, being multifarious and ephemeral, is difficult to observe and quantify in a systematic way. Even basic terminology used to describe cloud observations is fraught with ambiguity in the scientific literature. Any observational technique, method, or platform will contain inherent and unavoidable measurement uncertainties. Quantifying these uncertainties in cloud observations is a complex task that requires an understanding of all aspects of the measurement. We will use cloud observations obtained from the Moderate Resolution Imaging Spectroradiameter(<span class="hlt">MODIS</span>) to obtain metrics of the uncertainty of its cloud observations. Our uncertainty analyses will contain two main components, 1) an attempt to create a bias or uncertainty with respect to active measurements from CALIPSO and 2) a relative uncertainty within the <span class="hlt">MODIS</span> cloud climatologies themselves. Our method will link uncertainty to the physical observation and its environmental/scene characteristics. Our aim is to create statistical uncertainties that are based on the cloud observational values, <span class="hlt">satellite</span> view geometry, surface type, etc, for cloud amount and cloud top pressure. The <span class="hlt">MODIS</span> instruments on the NASA Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> provide observations over a broad spectral range (36 bands between 0.415 and 14.235 micron) and high spatial resolution (250 m for two bands, 500 m for five bands, 1000 m for 29 bands), which the <span class="hlt">MODIS</span> cloud mask algorithm (MOD35) utilizes to provide clear/cloud determinations over a wide array of surface types, solar illuminations and view geometries. For this study we use the standard <span class="hlt">MODIS</span> products, MOD03, MOD06 and MOD35, all of which were obtained from the NASA Level 1 and Atmosphere Archive and Distribution System.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070031724&hterms=Pressure+products&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DPressure%2Bproducts','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070031724&hterms=Pressure+products&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DPressure%2Bproducts"><span id="translatedtitle">Introduction to <span class="hlt">MODIS</span> Cloud Products. Chapter 5</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baum, Bryan A.; Platnick, Steven</p> <p>2006-01-01</p> <p>The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) imagers on the Terra and <span class="hlt">Aqua</span> Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar reflectance and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental <span class="hlt">Satellite</span> (GOES), <span class="hlt">MODIS</span> provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core <span class="hlt">MODIS</span> operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the <span class="hlt">MODIS</span> atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing <span class="hlt">satellite</span>-based cloud climatologies</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030102194','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030102194"><span id="translatedtitle">The <span class="hlt">MODIS</span> Aerosol Algorithm, Products and Validation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Mattoo, S.; Chu, D. A.; Martins, J. V.; Li, R.-R.; Ichoku, C.; Levy, R. C.; Kleidman, R. G.</p> <p>2003-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard both NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> is making near global daily observations of the earth in a wide spectral range. These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode and several derived parameters including reflected spectral solar flux at top of atmosphere. Over ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 microns to 2.13 microns. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral aerosol flux, mass concentration and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of AERONET data gleaned from 133 AERONET stations. 8000 <span class="hlt">MODIS</span> aerosol retrievals colocated with AERONET measurements confirm that one-standard deviation of <span class="hlt">MODIS</span> optical thickness retrievals fall within the predicted uncertainty of delta tauapproximately equal to plus or minus 0.03 plus or minus 0.05 tau over ocean and delta tay equal to plus or minus 0.05 plus or minus 0.15 tau over land. 271 <span class="hlt">MODIS</span> aerosol retrievals co-located with AERONET inversions at island and coastal sites suggest that one-standard deviation of <span class="hlt">MODIS</span> effective radius retrievals falls within delta r_eff approximately equal to 0.11 microns. The accuracy of the <span class="hlt">MODIS</span> retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171375','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171375"><span id="translatedtitle">Cloud Inhomogeneity from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cahalan, Robert F.</p> <p>2004-01-01</p> <p>Two full months (July 2003 and January 2004) of <span class="hlt">MODIS</span> Atmosphere Level-3 data from the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> are analyzed in order to characterize the horizontal variability of cloud optical thickness and water path at global scales. Various options to derive cloud variability parameters are discussed. The climatology of cloud inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two cloud phases, and separately over land and ocean. We find that cloud inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid clouds, weaker for local morning than local afternoon, about the same for liquid and ice clouds on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that <span class="hlt">MODIS</span> is capable of revealing significant fluctuations in cloud horizontal inhomogenity and stress the need to model their global radiative effect in future studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H41F1392S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H41F1392S"><span id="translatedtitle">Estimating sub-monthly TWS using <span class="hlt">MODIS</span> and GRACE <span class="hlt">satellite</span> observations, a case study over Tonlé Sap floodplain</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Steele-Dunne, S. C.; Tangdamrongsub, N.; Ditmar, P.; Gunter, B. C.; Sutanudjaja, E.</p> <p>2015-12-01</p> <p>Knowledge of Terrestrial Water Storage (TWS) can provide valuable information that can be used to improve our understanding of the hydrological cycle and the impact of extreme climate events. Global TWS observations are currently only available from the Gravity Recovery And Climate Experiment <span class="hlt">satellite</span> mission (GRACE) at monthly time scales. In this study, we present a new approach to derive the sub-monthly TWS variation over a regularly inundated area by using <span class="hlt">MODIS</span> reflectance data in addition to GRACE solutions. In the "training" phase, monthly TWS are computed from filtered GRACE solutions. A signal restoration method is applied to correct for signal leakage caused by filtering. In parallel, a time-series of mean monthly inundated area estimates is computed based on the Normalized Difference Water Index (NDWI), derived from <span class="hlt">MODIS</span> data. The training phase completes by finding an empirical relationship between the inundated area and the GRACE-based TWS variations, using a regression analysis. Then, the estimated parameters can be used to convert inundated area estimates into TWS variations without a further need in GRACE data. This approach has 3 major advantages over the usage of GRACE data alone. First, it can be used to cross-validate GRACE and <span class="hlt">MODIS</span> reflectance data in order to identify and eliminate unreliable estimates. Second, it can provide sub-monthly (e.g., 8-day) TWS variations without loss of spatial resolution. Lastly, it can be used to fill gaps in TWS estimates based on GRACE data and to extend the time-series of TWS estimates beyond the time interval when GRACE data are available. The methodology is demonstrated using the Tonlé Sap floodplain located in Central Cambodia as a test case. The analysis shows an excellent agreement between the 8-day NDWI-based TWS estimates averaged over monthly intervals and the GRACE-based monthly TWS variations. The approach developed would have similar application in other areas that experience regular large</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.H43G1314L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.H43G1314L"><span id="translatedtitle">Investigating changes in suspended sediment concentrations in the Peace-Athabasca Delta, Canada using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Long, C.; Pavelsky, T. M.</p> <p>2011-12-01</p> <p>Changes in the magnitude, distribution, and timing of sedimentary recharge to a freshwater delta have the potential to significantly affect the delta's hydrology, geomorphology, and ecology. The Peace-Athabasca Delta (PAD) in northeastern Alberta, Canada is one system potentially facing significant changes due to substantial decreases in discharge from the Athabasca River into the delta over at least the past four decades. We use bands 1 and 2 of daily 250-m Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) imagery, published river discharge data, and field measurements of suspended sediment concentrations to determine the effects of the decrease in Athabasca River flow on the delivery of sediment throughout the PAD. Daily <span class="hlt">MODIS</span> images for every summer (May-September) from 2000 to 2011 are used to track the timing, magnitude, and spatial characteristics of the delivery and distribution of high sediment water from the Athabasca River into the delta. Comparison of this time-series of <span class="hlt">satellite</span> images allows us to examine changes in sedimentary recharge throughout the last decade. Preliminary analysis for 2002 (the lowest water year of the decade) and 2005 (the highest water year) show that in 2005 the amount of sediment delivered to the delta was significantly higher than it was in 2002. This suggests that changes in river discharge do affect the delivery of sediment into the delta. Analysis of <span class="hlt">MODIS</span> images also reveals that not all areas of the PAD are equally recharged with sediment with any given discharge from the Athabasca River. By comparing the spatial distribution of sediment with same-day discharge on the Athabasca River, we can determine flow thresholds required to deliver sediment to individual lakes. A map of these thresholds allows us to then identify which portions of the PAD are no longer being recharged with sediment under current flow conditions and which additional areas could be particularly vulnerable to further decreases in Athabasca River</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007301','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007301"><span id="translatedtitle">Response to "Toward Unified <span class="hlt">Satellite</span> Climatology of Aerosol Properties. 3. <span class="hlt">MODIS</span> Versus MISR Versus AERONET"</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kahn, Ralph A.; Garay, Michael J.; Nelson, David L.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Hansen, Earl G.; Remer, Lorraine A.; Tanre, Didier</p> <p>2010-01-01</p> <p>A recent paper by Mishchenko et al. compares near-coincident MISR, <span class="hlt">MODIS</span>, and AERONET aerosol optical depth (AOD) products, and reports much poorer agreement than that obtained by the instrument teams and others. We trace the reasons for the discrepancies primarily to differences in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AdSpR..57..127G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AdSpR..57..127G"><span id="translatedtitle">Investigation and validation of <span class="hlt">MODIS</span> SST in the northern Persian Gulf</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ghanea, Mohsen; Moradi, Masoud; Kabiri, Keivan; Mehdinia, Ali</p> <p>2016-01-01</p> <p>Validation of <span class="hlt">satellite</span> derived sea surface temperature (SST) is necessary since <span class="hlt">satellite</span> minus buoy SST (= bias) relies on atmospheric and oceanographic conditions and time periods. This research validates <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span>) <span class="hlt">satellite</span> daytime SST with buoy SST at the northern Persian Gulf. Sixteen dates during June 2011 to June 2015 were selected for validation. The buoy-<span class="hlt">satellite</span> matchups were gained within one image pixel (1 km at nadir) and ±6 h in time. For most matchups, time interval was ±3 h. Effects of total column water vapor, aerosol optical depth, wind speed, glint, and <span class="hlt">satellite</span> zenith angle on bias are then investigated. These parameters are classified based on root mean square (RMS) difference between <span class="hlt">satellite</span> and buoy SST. Final results represent a near-perfect R2 (>0.989) for both <span class="hlt">satellites</span>. The bias was 0.07 ± 0.53 °C and -0.06 ± 0.44 °C for <span class="hlt">MODIS-Aqua</span> and -Terra, respectively.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A33A3149S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A33A3149S"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span> Total Precipitable Water Using Surface GPS Technology</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Serra, Y. L.; Fears, A. J.; Moker, J.</p> <p>2014-12-01</p> <p>In this research we validate estimates of atmospheric total precipitable water (TPW) from the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) instruments onboard the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> using surface Global Positioning System (GPS) derived TPW collected at ten stations across northwest Mexico during the 2013 North American monsoon (NAM) season. The <span class="hlt">MODIS</span> Level 2 products provide TPW estimated from both the infrared (IR) and near-infrared (NIR) spectral bands and are available over the NAM region approximately twice per day. Our comparisons indicate that the correlations of Terra and <span class="hlt">Aqua</span> IR TPW with the GPS observations are all significant at the 95% confidence level, while the NIR correlations show little or no significance. The analysis also finds that Terra and <span class="hlt">Aqua</span> have significant seasonal biases with respect to the GPS for both the IR and NIR estimates at several locations, with the IR estimates showing better agreement than the NIR estimates. The dependence of the errors on elevation and time of overpass will be discussed to help identify contributing factors to the observed errors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012TCry....6..431R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012TCry....6..431R"><span id="translatedtitle">Melt ponds on Arctic sea ice determined from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data using an artificial neural network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rösel, A.; Kaleschke, L.; Birnbaum, G.</p> <p>2012-04-01</p> <p>Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like the Moderate Resolution Image Spectroradiometer (<span class="hlt">MODIS</span>) using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron to reduce computational costs. Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 <span class="hlt">MODIS</span> surface reflectance product. The validation of the <span class="hlt">MODIS</span> melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC) for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with coefficient of determination ranging from R2=0.28 to R2=0.45. The mean annual cycle of the melt pond fraction per grid cell for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds on the geographical latitude, and has its maximum in mid-July at latitudes between 80° and 88° N. Furthermore, the <span class="hlt">MODIS</span> results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ARTIST Sea Ice-, NASA Team 2-, and Bootstrap-algorithms with <span class="hlt">MODIS</span> sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMT.....8.4025K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMT.....8.4025K"><span id="translatedtitle">Uncertainties of <span class="hlt">satellite</span>-derived surface skin temperatures in the polar oceans: <span class="hlt">MODIS</span>, AIRS/AMSU, and AIRS only</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kang, H.-J.; Yoo, J.-M.; Jeong, M.-J.; Won, Y.-I.</p> <p>2015-10-01</p> <p>Uncertainties in the <span class="hlt">satellite</span>-derived surface skin temperature (SST) data in the polar oceans during two periods (16-24 April and 15-23 September) 2003-2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (<span class="hlt">MODIS</span> IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. <span class="hlt">MODIS</span> IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to -2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992-0.999) method was greater than that of the <span class="hlt">MODIS</span> IST to the AIRS/AMSU (0.968-0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of -0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (<span class="hlt">MODIS</span>, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ~ 2.8 ± 1.9 K decade-1) in the northern high regions (70-80° N) as expected from the ice-albedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMTD....8.4451K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMTD....8.4451K"><span id="translatedtitle">Uncertainties of <span class="hlt">satellite</span>-derived surface skin temperatures in the polar oceans: <span class="hlt">MODIS</span>, AIRS/AMSU, and AIRS only</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kang, H.-J.; Yoo, J.-M.; Jeong, M.-J.; Won, Y.-I.</p> <p>2015-05-01</p> <p>Uncertainties in the <span class="hlt">satellite</span>-derived Surface Skin Temperature (SST) data in the polar oceans during two periods (16-24 April and 15-23 September) of 2003-2014 were investigated and the three datasets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (<span class="hlt">MODIS</span> IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. <span class="hlt">MODIS</span> IST was systematically up to 1.65 K warmer at the sea ice boundary and up to 2.04 K colder in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992-0.999) method was greater than that of the <span class="hlt">MODIS</span> IST to the AIRS/AMSU (0.968-0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of -0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a~less accurate GCM forecast over the seasonally-varying frozen oceans than the microwave data. The three datasets (<span class="hlt">MODIS</span>, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ~2.8 ± 1.9 K decade-1) in the northern high latitude regions (70-80° N) as expected from the ice-albedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012AGUFM.A33M0338G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012AGUFM.A33M0338G&link_type=ABSTRACT"><span id="translatedtitle">Operationalizing a Research Sensor: <span class="hlt">MODIS</span> to VIIRS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grant, K. D.; Miller, S. W.; Puschell, J.</p> <p>2012-12-01</p> <p>The National Oceanic and Atmospheric Administration (NOAA) and NASA are jointly acquiring the next-generation civilian environmental <span class="hlt">satellite</span> system: the Joint Polar <span class="hlt">Satellite</span> System (JPSS). JPSS will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental <span class="hlt">Satellites</span> (POES) managed by NOAA. The JPSS <span class="hlt">satellite</span> will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The primary sensor for the JPSS mission is the Visible/Infrared Imager Radiometer Suite (VIIRS) developed by Raytheon Space and Airborne Systems (SAS). The ground processing system for the JPSS mission is known as the Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS) which are both developed by Raytheon Intelligence and Information Systems (IIS). The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by Raytheon SAS for the NASA Earth Observing System (EOS) as a research instrument to capture data in 36 spectral bands, ranging in wavelength from 0.4 μm to 14.4 μm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). <span class="hlt">MODIS</span> data provides unprecedented insight into large-scale Earth system science questions related to cloud and aerosol characteristics, surface emissivity and processes occurring in the oceans, on land, and in the lower atmosphere. <span class="hlt">MODIS</span> has flown on the EOS Terra <span class="hlt">satellite</span> since 1999 and on the EOS <span class="hlt">Aqua</span> <span class="hlt">satellite</span> since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of <span class="hlt">MODIS</span>-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to <span class="hlt">MODIS</span> for the next-generation polar-orbiting environmental <span class="hlt">satellites</span>, the Visible/Infrared Imager</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120004209','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120004209"><span id="translatedtitle">An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, <span class="hlt">MODIS</span>, and ASTER <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spruce, Joseph P.; Sader, Steve; Smoot, James</p> <p>2012-01-01</p> <p>This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, <span class="hlt">satellite</span>, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. <span class="hlt">MODIS</span>-based change products were applied to view and assess insect-induced swamp forest defoliation. <span class="hlt">MODIS</span>, Landsat, and ASTER <span class="hlt">satellite</span> data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713537G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713537G"><span id="translatedtitle">Intercomparison of <span class="hlt">MODIS-Aqua</span> C051 and C006 Level 3 Deep Blue AOD and Ångström exponent retrievals over the Sahara desert and the Arabian Peninsula during the period 2002-2014</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gkikas, Antonis; Basart, Sara; Korras-Carraca, Marios; Papadimas, Christos; Hatzianastassiou, Nikos; Sayer, Andrew; Hsu, Christina; Baldasano, Jose Maria</p> <p>2015-04-01</p> <p>Dust loads emitted from the arid regions of Northern Africa and the Arabian Peninsula account for the major portion of the global dust aerosol burden. Depending on prevailing atmospheric circulation they can be transported far away from their source areas. Considering the key role of dust aerosols to weather and climate a better description of their spatial and temporal variability it is an issue of great importance. The main target of the present study is to describe aerosols' regime over Northern Africa and Arabian Peninsula using Deep Blue aerosol optical depth (AOD550nm) and Ångström exponent (α412-470nm) measurements. Given the applied changes to the retrieval algorithm, emphasis is also given to the inter-comparison between the data from Collections 051 and 006. The analysis is performed using <span class="hlt">MODIS-Aqua</span> daily Level 3 data at 1°x1° spatial resolution over the period 2002-2014. The study region extends from 20°W to 60°E and from 0° to 40°N. The obtained long-term geographical distributions reveal many similarities between C051 and C006 AOD retrievals. They both indicate a zone of high AODs along the parallel of 15°N, extending from the western coasts of Africa to Chad where the maximum values (~1.3) are recorded. In the Arabian Peninsula, the maximum AODs (up to 0.6) are found in Iraq. On the contrary, more apparent differences between the two collections are found for α412-470nm. It is evident a reduction of C006 retrievals, which is more pronounced across the Sahara desert. In C006, the α412-470nm values over the deserts of Northern Africa and Middle East mostly vary from 0 to 0.6 while higher values (up to 1.5) are observed in sub-sahel regions, west coasts of Saudi Arabia and Iran. During the study period, in both collections, AOD has decreased by up to 93% in N. Africa (northern parts of Algeria) while it has increased by up to 70% in the Middle East (northern parts of Iraq). Reversed tendencies are found for the α412-470nm retrievals. For</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AMT.....9.3193S&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AMT.....9.3193S&link_type=ABSTRACT"><span id="translatedtitle">Comparison of <span class="hlt">MODIS</span> and VIIRS cloud properties with ARM ground-based observations over Finland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sporre, Moa K.; O'Connor, Ewan J.; Håkansson, Nina; Thoss, Anke; Swietlicki, Erik; Petäjä, Tuukka</p> <p>2016-07-01</p> <p>Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments aboard the <span class="hlt">satellites</span> Terra and <span class="hlt">Aqua</span> and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP <span class="hlt">satellite</span> are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols - Effects on Clouds and Climate (BAECC) campaign. The <span class="hlt">satellite</span> cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, <span class="hlt">satellites</span> overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, <span class="hlt">satellites</span> underestimated CTH by on average 169 m (5.8 %). <span class="hlt">MODIS</span> collection 6 overestimated LWP by on average 13 g m-2 (11 %). Interestingly, LWP for <span class="hlt">MODIS</span> collection 5.1 is slightly overestimated by <span class="hlt">Aqua</span> (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the <span class="hlt">MODIS</span> instrument on Terra. This evaluation indicates that the <span class="hlt">satellite</span> cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the <span class="hlt">satellites</span> in this high-latitude location.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1111496C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1111496C"><span id="translatedtitle">Actual evapotranspiration estimation in a Mediterranean mountain region by means of Landsat-5 TM and TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> imagery and Sap Flow measurements in Pinus sylvestris forest stands.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Pons, X.; Llorens, P.</p> <p>2009-04-01</p> <p>Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and in the assessment of environmental stress that affects forest and agricultural ecosystems. An increase of evapotranspiration while precipitation remains constant, or is reduced, could decrease water availability for natural and agricultural systems and human needs. Consequently, water balance methods, as the evapotranspiration modelling, have been widely used to estimate crop and forest water needs, as well as the global change effects. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute evapotranspiration at regional scales in a feasible way. Currently, the 38% of Catalonia (NE of the Iberian Peninsula) is covered by forests, and one of the most important forest species is Scots Pine (Pinus sylvestris) which represents the 18.4% of the area occupied by forests. The aim of this work is to model actual evapotranspiration in Pinus sylvestris forest stands, in a Mediterranean mountain region, using remote sensing data, and compare it with stand-scale sap flow measurements measured in the Vallcebre research area (42° 12' N, 1° 49' E), in the Eastern Pyrenees. To perform this study a set of 30 cloud-free TERRA-<span class="hlt">MODIS</span> images and 10 Landsat-5 TM images of path 198 and rows 31 and 32 from June 2003 to January 2005 have been selected to perform evapotranspiration modelling in Pinus sylvestris forest stands. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected two different types of products which contain the remote sensing data we have used to model daily evapotranspiration, daily LST product and daily calibrated reflectances product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013278','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013278"><span id="translatedtitle"><span class="hlt">Satellite</span> Monitoring of Asian Dust Storms from SeaWiFS and <span class="hlt">MODIS</span>: Source, Pathway, and Interannual Variability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina; Tsay, S.-C.; Bettenhausen, C.; Sayer, A.</p> <p>2011-01-01</p> <p>Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces peop Ie indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be tran sported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new <span class="hlt">satellite</span> algorithm to retrieve aerosol optical thickness and single scattering albedo over brightreflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as Sea WiFS and <span class="hlt">MODIS</span> to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the <span class="hlt">satellite</span> retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new <span class="hlt">satellite</span> products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from Sea WiFS and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040000136&hterms=satellite+movement+earth&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsatellite%2Bmovement%2Bearth','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040000136&hterms=satellite+movement+earth&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsatellite%2Bmovement%2Bearth"><span id="translatedtitle">Near-Real-Time Detection and Monitoring of Dust Events by <span class="hlt">Satellite</span> (SeaWIFS, <span class="hlt">MODIS</span>, and TOMS)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina; Tsay, Si-Chee; Herman, Jay R.; Kaufman, Yoram</p> <p>2002-01-01</p> <p>Over the last few years <span class="hlt">satellites</span> have given us increasingly detailed information on the size, location, and duration of dust events around the world. These data not only provide valuable feedback to the modelling community as to the fidelity of their aerosol models but are also finding increasing use in near real-time applications. In particular, the ability to locate and track the development of aerosol dust clouds on a near real-time basis is being used by scientists and government to provide warning of air pollution episodes over major urban area. This ability has also become a crucial component of recent coordinated campaigns to study the characteristics of tropospheric aerosols such as dust and their effect on climate. One such recent campaign was ACE-Asia, which was designed to obtain the comprehensive set of ground, aircraft, and <span class="hlt">satellite</span> data necessary to provide a detailed understanding of atmospheric aerosol particles over the Asian-Pacific region. As part of ACE-Asia, we developed a near real-time data processing and access system to provide <span class="hlt">satellite</span> data from the polar-orbiting instruments Earth Probe TOMS (in the form of absorbing aerosol index) and SeaWiFS (in the form of aerosol optical thickness, AOT, and Angstrom exponent). The results were available via web access. The location and movement information provided by these data were used both in support of the day-to-day flight planning of ACE-Asia and as input into aerosol transport models. While near real-time SeaWiFS data processing can be performed using either the normal global data product or data obtained via direct broadcast to receiving stations close to the area of interest, near real-time <span class="hlt">MODIS</span> processing of data to provide aerosol retrievals is currently only available using its direct broadcast capability. In this paper, we will briefly discuss the algorithms used to generate these data. The retrieved aerosol optical thickness and Angstrom exponent from SeaWiFS will be compared with</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150006839','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150006839"><span id="translatedtitle">High Resolution Aerosol Data from <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> for Urban Air Quality Studies</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.</p> <p>2013-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for <span class="hlt">MODIS</span> which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional <span class="hlt">MODIS</span> 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from <span class="hlt">MODIS</span> to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ISPAr41B6..185Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ISPAr41B6..185Y"><span id="translatedtitle">Application of the Terra <span class="hlt">Modis</span> <span class="hlt">Satellite</span> Data for Environmental Monitoring in Western Siberia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yashchenkoa, I. G.; Peremitina, T. O.</p> <p>2016-06-01</p> <p>Using the <span class="hlt">MODIS</span> thematic products, the status of vegetation of oil producing areas in Western Siberia for the period 2010-2015 is monitored. An approach for estimating the impact of various factors on the ecology of oil producing areas using the NDVI coefficient and remote sensing data on the status of vegetation is proposed. The approach is tested within four technologically-disturbed lands - four oil fields, Krapivinskoye, Myldzhenskoye, Luginetskoye, and Urmanskoye in Tomsk region. The territory of the Oglatsky Status Nature Reserve of regional importance is investigated as a reference area.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1815907B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1815907B"><span id="translatedtitle">Assessment of the <span class="hlt">MODIS</span>-Terra Collection 006 aerosol optical depth data over the greater Mediterranean basin and inter-comparison against <span class="hlt">MODIS</span> C005 and AERONET</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Betsikas, Marios; Hatzianastassiou, Nikos; Papadimas, Christos D.; Gkikas, Antonis; Matsoukas, Christos; Sayer, Andrew; Hsu, Christina; Vardavas, Ilias</p> <p>2016-04-01</p> <p>Aerosols are one of the key factors determining the Earth's solar radiation budget. The aerosol radiative effects are strongly dependent on aerosol optical depth (AOD) which is a good measure of atmospheric aerosol loading. Therefore, understanding better the spatial and temporal patterns of AOD at both global and regional scales is important for more accurate estimations of aerosol radiative effects. Nowadays, improved globally distributed AOD products are available largely based on <span class="hlt">satellite</span> observations. Currently, one of the most acknowledged accurate AOD dataset is the one derived from measurements of the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument onboard the twin Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> <span class="hlt">satellite</span> platforms. The <span class="hlt">MODIS</span> aerosol retrieval algorithm, which is used to produce AOD data, is continuously improved and updated, leading to releases of successive series, named as Collections. Recently, <span class="hlt">MODIS</span> Collection 6 (C006) dataset has been made available. Despite their advantages, <span class="hlt">satellite</span> AOD products have to be assessed through comparisons against ground based AOD products, such as those from AERosol Robotic Network (AERONET). The aim of the present study is to assess the newest <span class="hlt">MODIS</span> C006 AOD product over the greater Mediterranean basin. The assessment is performed through comparisons of the <span class="hlt">MODIS</span>-Terra C006 Level-3 AOD data against corresponding data from the previous C005 <span class="hlt">MODIS</span> dataset, as well as versus AOD data from AERONET stations within the study region. The study period extends from 2001 to 2012 and our comparisons are performed on a monthly basis. Emphasis is given on differences between the <span class="hlt">MODIS</span> C006 AOD data and corresponding previous C005 data, as to their spatial and temporal, seasonal and inter-annual, patterns. The results show a better agreement of <span class="hlt">MODIS</span> C006 than C005 AOD data with AERONET, while the C006 data offer a complete spatial coverage of the study region, specifically over the northern African</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040016318','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040016318"><span id="translatedtitle">Earth Observing System (EOS) <span class="hlt">Aqua</span> Launch and Early Mission Attitude Support Experiences</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tracewell, D.; Glickman, J.; Hashmall, J.; Natanson, G.; Sedlak, J.</p> <p>2003-01-01</p> <p>The Earth Observing System (EOS) <span class="hlt">Aqua</span> <span class="hlt">satellite</span> was successfully launched on May 4,2002. <span class="hlt">Aqua</span> is the second in the series of EOS <span class="hlt">satellites</span>. EOS is part of NASA s Earth Science Enterprise Program, whose goals are to advance the scientific understanding of the Earth system. <span class="hlt">Aqua</span> is a three-axis stabilized, Earth-pointing spacecraft in a nearly circular, sun-synchronous orbit at an altitude of 705 km. The Goddard Space Flight Center (GSFC) Flight Dynamics attitude team supported all phases of the launch and early mission. This paper presents the main results and lessons learned during this period, including: real-time attitude mode transition support, sensor calibration, onboard computer attitude validation, response to spacecraft emergencies, postlaunch attitude analyses, and anomaly resolution. In particular, Flight Dynamics support proved to be invaluable for successful Earth acquisition, fine-point mode transition, and recognition and correction of several anomalies, including support for the resolution of problems observed with the <span class="hlt">MODIS</span> instrument.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A53C0371A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A53C0371A"><span id="translatedtitle"><span class="hlt">MODIS</span> Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Albayrak, A.; Wei, J. C.; Petrenko, M.; Lary, D. J.; Leptoukh, G. G.</p> <p>2011-12-01</p> <p>Over the past decade, global aerosol observations have been conducted by space-borne sensors, airborne instruments, and ground-base network measurements. Unfortunately, quite often we encounter the differences of aerosol measurements by different well-calibrated instruments, even with a careful collocation in time and space. The differences might be rather substantial, and need to be better understood and accounted for when merging data from many sensors. The possible causes for these differences come from instrumental bias, different <span class="hlt">satellite</span> viewing geometries, calibration issues, dynamically changing atmospheric and the surface conditions, and other "regressors", resulting in random and systematic errors in the final aerosol products. In this study, we will concentrate on the subject of removing biases and the systematic errors from <span class="hlt">MODIS</span> (both Terra and <span class="hlt">Aqua</span>) aerosol product, using Machine Learning algorithms. While we are assessing our regressors in our system when comparing global aerosol products, the Aerosol Robotic Network of sun-photometers (AERONET) will be used as a baseline for evaluating the <span class="hlt">MODIS</span> aerosol products (Dark Target for land and ocean, and Deep Blue retrieval algorithms). The results of bias adjustment for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> are planned to be incorporated into the AeroStat Giovanni as part of the NASA ACCESS funded AeroStat project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160009171','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160009171"><span id="translatedtitle">Validation of Cloud Parameters Derived from Geostationary <span class="hlt">Satellites</span>, AVHRR, <span class="hlt">MODIS</span>, and VIIRS Using SatCORPS Algorithms</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; Xi, B.</p> <p>2016-01-01</p> <p>Validation is a key component of remote sensing that can take many different forms. The NASA LaRC <span class="hlt">Satellite</span> ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary <span class="hlt">satellites</span>, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting <span class="hlt">satellite</span> imagers, <span class="hlt">MODIS</span>, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; <span class="hlt">satellite</span> and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110023848&hterms=spectroradiometer+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectroradiometer%2BMODIS','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110023848&hterms=spectroradiometer+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectroradiometer%2BMODIS"><span id="translatedtitle">Discrepancies Between <span class="hlt">MODIS</span> and ISCCP Land Surface Temperature Products Analyzed with Microwave Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moncet, Jean-Luc; Liang, Pan; Lipton, Alan E.; Galantowicz, John F.; Prigent, Catherine</p> <p>2011-01-01</p> <p>This paper compares land surface temperature (LST) products from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the International <span class="hlt">Satellite</span> Cloud Climatology Project (ISCCP). With both sources, the LST data are derived from infrared measurements. For ISCCP, LST is a secondary product in support of the primary cloud analyses, but the LST data have been used for several other purposes. The <span class="hlt">MODIS</span> measurements from the <span class="hlt">Aqua</span> spacecraft are taken at about 01:30 and 13:30 local time, and the ISCCP three-hourly data, based on several geostationary and polar orbiting <span class="hlt">satellites</span>. were interpolated to the <span class="hlt">MODIS</span> measurement times. For July 2003 monthly averages over all clear-sky locations, the ISCCP-<span class="hlt">MODIS</span> differences were +5.0 K and +2.5 K for day and night, respectively, and there were areas with differences as large as 25 K. The day-night differences were as much as approximately 10 K higher for ISCCP than for <span class="hlt">MODIS</span>. The <span class="hlt">MODIS</span> measurements were more consistent with independent microwave measurements from AMSR-E, by several measures, with respect to day-night differences and day-to-day variations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110012488','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110012488"><span id="translatedtitle">The Characterization of Deep Convective Cloud Albedo as a Calibration Target Using <span class="hlt">MODIS</span> Reflectances</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Doelling, David R.; Hong, Gang; Morstad, Daniel; Bhatt, Rajendra; Gopalan, Arun; Xiong, Jack</p> <p>2010-01-01</p> <p>There are over 25 years of historical <span class="hlt">satellite</span> data available to climate analysis. The historical <span class="hlt">satellite</span> data needs to be well calibrated, especially in the visible, where there is no onboard calibration on operational <span class="hlt">satellites</span>. The key to the vicarious calibration of historical <span class="hlt">satellites</span> relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all <span class="hlt">satellites</span>, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated <span class="hlt">MODIS</span> is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard black-bodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean. Functionality between particle size and ozone absorption with DCC albedo will be examined. Although DCC clouds are nearly Lambertion, the angular distribution of reflectances will be sampled and compared with theoretical models. Both <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> DCC angular models will be compared for consistency. Normalizing angular geostationary DCC reflectances, which were calibrated against <span class="hlt">MODIS</span>, with SCIAMACHY spectral reflectances and comparing them to <span class="hlt">MODIS</span> DCC reflectances will inspect the usage of DCC albedos as an absolute calibration target.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4634488','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4634488"><span id="translatedtitle">True Colour Classification of Natural Waters with Medium-Spectral Resolution <span class="hlt">Satellites</span>: SeaWiFS, <span class="hlt">MODIS</span>, MERIS and OLCI</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>van der Woerd, Hendrik J.; Wernand, Marcel R.</p> <p>2015-01-01</p> <p>The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne “ocean colour” instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10) of narrow (≈10 nm) bands. Surprisingly, the analysis of the <span class="hlt">satellite</span> data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral <span class="hlt">satellite</span> data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α). Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, <span class="hlt">MODIS</span>, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments. PMID:26473859</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26473859','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26473859"><span id="translatedtitle">True colour classification of natural waters with medium-spectral resolution <span class="hlt">satellites</span>: SeaWiFS, <span class="hlt">MODIS</span>, MERIS and OLCI.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Woerd, Hendrik J van der; Wernand, Marcel R</p> <p>2015-01-01</p> <p>The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne "ocean colour" instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10) of narrow (≈10 nm) bands. Surprisingly, the analysis of the <span class="hlt">satellite</span> data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral <span class="hlt">satellite</span> data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α). Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, <span class="hlt">MODIS</span>, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments. PMID:26473859</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030112964&hterms=clam&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclam','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030112964&hterms=clam&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclam"><span id="translatedtitle">Towards Improved <span class="hlt">MODIS</span> Aerosol Retrieval over the US East Coast Region: Re-examining the Aerosol Model and Surface Assumptions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Levy, R. C.; Remer, L. A.; Kaufman, Y. J.; Holben, B. N.</p> <p>2002-01-01</p> <p>The MODerate resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) aboard the Terra and recently the <span class="hlt">Aqua</span> platform, produces a set of aerosol products over both ocean and land regions. Previous validation efforts have shown that from a global perspective, aerosol optical depth (AOD) is successfully retrieved from <span class="hlt">MODIS</span>. Even over coastal regions, the over- land and over-ocean retrievals are consistent with each other, and well matched with ground-based sunphotometer measurements (such as AERONET). However, the East Coast of the United States is one region where there is consistently a discrepancy between land and ocean retrievals. Over the ocean, <span class="hlt">MODIS</span> AODs are consistent with coastal sunphotometer measurements, but over land, AODs are consistently over- estimated. In this study we use field data from the Chesapeake Lighthouse and Aircraft Measurements for <span class="hlt">Satellites</span> experiment (CLAMS), (held during summer 2001) to determine the aerosol properties at a number of sites. Using the 6-S radiative transfer package, we compute simulated <span class="hlt">satellite</span> radiances and compare them with observed <span class="hlt">MODIS</span> radiances. We believe that the AOD over-estimation is not likely due to an incorrect choice of the urban/industrial aerosol models. Using 6-S to do an atmospheric correction for a very low AOD case, we show rather, that the discrepancies are likely a result of incorrect assumptions about the surface reflectance properties. Understanding and improving <span class="hlt">MODIS</span> retrievals over the East Coast will not only improve the global quality of <span class="hlt">MODIS</span>, but also would enable the use of <span class="hlt">MODIS</span> as a tool for monitoring regional aerosol events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1111496C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1111496C&link_type=ABSTRACT"><span id="translatedtitle">Actual evapotranspiration estimation in a Mediterranean mountain region by means of Landsat-5 TM and TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> imagery and Sap Flow measurements in Pinus sylvestris forest stands.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Pons, X.; Llorens, P.</p> <p>2009-04-01</p> <p>Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and in the assessment of environmental stress that affects forest and agricultural ecosystems. An increase of evapotranspiration while precipitation remains constant, or is reduced, could decrease water availability for natural and agricultural systems and human needs. Consequently, water balance methods, as the evapotranspiration modelling, have been widely used to estimate crop and forest water needs, as well as the global change effects. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute evapotranspiration at regional scales in a feasible way. Currently, the 38% of Catalonia (NE of the Iberian Peninsula) is covered by forests, and one of the most important forest species is Scots Pine (Pinus sylvestris) which represents the 18.4% of the area occupied by forests. The aim of this work is to model actual evapotranspiration in Pinus sylvestris forest stands, in a Mediterranean mountain region, using remote sensing data, and compare it with stand-scale sap flow measurements measured in the Vallcebre research area (42° 12' N, 1° 49' E), in the Eastern Pyrenees. To perform this study a set of 30 cloud-free TERRA-<span class="hlt">MODIS</span> images and 10 Landsat-5 TM images of path 198 and rows 31 and 32 from June 2003 to January 2005 have been selected to perform evapotranspiration modelling in Pinus sylvestris forest stands. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected two different types of products which contain the remote sensing data we have used to model daily evapotranspiration, daily LST product and daily calibrated reflectances product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120007859','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120007859"><span id="translatedtitle">An Overview of <span class="hlt">MODIS</span> On-orbit Operation, Calibration, and Lessons</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Jack; Barnes, William; Salomonson, Vincent</p> <p>2012-01-01</p> <p>Two nearly identical copies of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) have successfully operated onboard the Terra and <span class="hlt">Aqua</span> spacecraft for more than II years and 9 years since their launch in December 1999 and May 2002, respectively. <span class="hlt">MODIS</span> is a key instrument for the NASA's Earth Observing System (EOS) missions. <span class="hlt">MODIS</span> observations have produced an unprecedented amount and a broad range of data products and significantly benefited the science and user community. Its follow-on instrument, the Visible/Infrared Imager Radiometer Suite (VIIRS) on-board the NPOESS Preparatory Project (NPP) spacecraft, is currently scheduled for launch in late October, 2011. The NPP serves as a bridge mission between EOS and the Joint Polar <span class="hlt">Satellite</span> System (JPSS). <span class="hlt">MODIS</span> collects data in 36 spectral bands, covering spectral regions from visible (VIS) to long-wave infrared (L WIR), and at three different spatial resolutions. Because of its stringent design requirements, <span class="hlt">MODIS</span> was built with a complete set of onboard calibrators, including a solar diffuser (SO), a solar diffuser stability monitor (SDSM), a blackbody (BB), a spectroradiometric calibration assembly (SRCA), and a space view (SV) port. Except for tbe SRCA, VIlRS carries the same set of onboard calibrators as <span class="hlt">MODIS</span>. The SD/SDSM system is used together to calibrate tbe reflective solar bands (RSB). The BB is designed for the thermal emissive bands (TEB) calibration. Similar to Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, VIlRS will also make regular lunar observations to monitor RSB radiometric calibration stability. In this paper, we provide an overview of <span class="hlt">MODIS</span> on-orbit operation and calibration activities and present issues identified and lessons learned from mission-long instrument operations and implementation of various calibration and characterization strategies. Examples of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument on-orbit performance, including their similarities and unique characteristics, are discussed in tbe context of what</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AtmEn..47..435B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AtmEn..47..435B"><span id="translatedtitle">Spatio-temporal variations in aerosol optical and cloud parameters over Southern India retrieved from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Balakrishnaiah, G.; Raghavendra kumar, K.; Suresh Kumar Reddy, B.; Rama Gopal, K.; Reddy, R. R.; Reddy, L. S. S.; Swamulu, C.; Nazeer Ahammed, Y.; Narasimhulu, K.; KrishnaMoorthy, K.; Suresh Babu, S.</p> <p>2012-02-01</p> <p>Remote sensing of global aerosols has generated a great scientific interest in a variety of applications related to global warming and climate change. The spatial and temporal variations in aerosol particles over Southern India were described in the present study and the impact of these variations on various optical properties of clouds, using Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data retrieved from the Terra <span class="hlt">satellite</span>. High mean Aerosol Optical Depth (AOD) values were observed in almost all regions during the summer season, whereas in Pune, Visakhapatnam and Hyderabad, high AOD values were noticed during the monsoon season. The Ångström exponent that increases with AOD is opposite to what would be the case if swelling of particles due to hygroscopic growth near cloudy areas played a major role in the <span class="hlt">MODIS</span> data. We then analyzed the relationships between AOD and four other cloud parameters, namely water vapor (WV), cloud fraction (CF), cloud top temperature (CTT) and cloud top pressure (CTP). Regional correlation maps and time series plots for aerosol (AOD) and cloud parameters were produced to provide a better understanding of aerosol-cloud interaction. The correlation between AOD and CF was greater than 0.51 in Visakhapatnam, 0.45 in Thiruvanantapuram, 0.42 in Pune and whereas in Bangalore, Hyderabad and Anantapur, it is 0.17, 0.39 and 0.12, respectively. The analyses showed strong positive correlations between AOD and WV for all cities investigated. The correlation between AOD and CF was positive for all selected cities. AOD showed a negative correlation with CTP and CTT in Southern Indian regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B43C0572P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B43C0572P"><span id="translatedtitle">Characterization, Validation and Intercomparison of Clumping Index Maps from POLDER, <span class="hlt">MODIS</span>, and MISR <span class="hlt">Satellite</span> Data Over Reference Sites</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pisek, J.; He, L.; Chen, J. M.; Govind, A.; Sprintsin, M.; Ryu, Y.; Arndt, S. K.; Hocking, D.; Wardlaw, T.; Kuusk, J.; Oliphant, A. J.; Korhonen, L.; Fang, H.; Matteucci, G.; Longdoz, B.; Raabe, K.</p> <p>2015-12-01</p> <p>Vegetation foliage clumping significantly alters its radiation environment and therefore affects vegetation growth as well as water and carbon cycles. The clumping index is useful in ecological and meteorological models because it provides new structural information in addition to the effective leaf area index (LAI) retrieved from mono-angle remote sensing and allows accurate separation of sunlit and shaded leaves in the canopy. Not accounting for the foliage clumping in LAI retrieval algorithms leads to substantial underestimation of actual LAI, especially for needleleaf forests. Normalized Difference between Hotspot and Darkspot (NDHD) index has been previously used to retrieve global clumping index maps from POLarization and Directionality of the Earth's Reflectances (POLDER) data at ~6 km resolution, from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Bidirectional Reflectance Distribution Function (BRDF) product at 500 m resolution. Most recently the algorithm was applied with Multi-angle Imaging SpectroRadiometer (MISR) data at 275 m resolution over selected areas. In this presentation we characterize and intercompare the three products over a set of sites representing diverse biomes and different canopy structures. The products are also directly validated with both in-situ vertical profiles and seasonal trajectories of clumping index. We illustrate that the vertical distribution of foliage and especially the effect of understory needs to be taken into account while validating foliage clumping products from remote sensing products with values measured in the field. <span class="hlt">Satellite</span> measurements respond to the structural effects near the top of canopies, while ground measurements may be biased by the lower vegetation layers. Additionally, caution should be taken regarding the misclassification in land cover maps as their errors can be propagated into the foliage clumping maps. Our results indicate that <span class="hlt">MODIS</span> data and MISR data with 275 m resolution in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.3186P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.3186P"><span id="translatedtitle">Characterization, validation and intercomparison of clumping index maps from POLDER, <span class="hlt">MODIS</span>, and MISR <span class="hlt">satellite</span> data over reference sites</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pisek, Jan; He, Liming; Chen, Jing; Govind, Ajit; Sprintsin, Michael; Ryu, Youngryel; Arndt, Stefan; Hocking, Darren; Wardlaw, Timothy; Kuusk, Joel; Oliphant, Andrew; Korhonen, Lauri; Fang, Hongliang; Matteucci, Giorgio; Longdoz, Bernard; Raabe, Kairi</p> <p>2015-04-01</p> <p>Vegetation foliage clumping significantly alters its radiation environment and therefore affects vegetation growth as well as water and carbon cycles. The clumping index is useful in ecological and meteorological models because it provides new structural information in addition to the effective leaf area index (LAI) retrieved from mono-angle remote sensing and allows accurate separation of sunlit and shaded leaves in the canopy. Not accounting for the foliage clumping in LAI retrieval algorithms leads to substantial underestimation of actual LAI, especially for needleleaf forests. Normalized Difference between Hotspot and Darkspot (NDHD) index has been previously used to retrieve global clumping index maps from POLarization and Directionality of the Earth's Reflectances (POLDER) data at ~6 km resolution, from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Bidirectional Reflectance Distribution Function (BRDF) product at 500 m resolution. Most recently the algorithm was applied with Multi-angle Imaging SpectroRadiometer (MISR) data at 275 m resolution over selected areas. In this presentation we characterize and intercompare the three products over a set of sites representing diverse biomes and different canopy structures. The products are also directly validated with both in-situ vertical profiles and seasonal trajectories of clumping index. We illustrate that the vertical distribution of foliage and especially the effect of understory needs to be taken into account while validating foliage clumping products from remote sensing products with values measured in the field. <span class="hlt">Satellite</span> measurements respond to the structural effects near the top of canopies, while ground measurements may be biased by the lower vegetation layers. Additionally, caution should be taken regarding the misclassification in land cover maps as their errors can be propagated into the foliage clumping maps. Our results indicate that <span class="hlt">MODIS</span> data and MISR data with 275 m in particular can</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006671','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006671"><span id="translatedtitle">Long Term Cloud Property Datasets From <span class="hlt">MODIS</span> and AVHRR Using the CERES Cloud Algorithm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; Hong, Gang; Bhatt, Rajendra</p> <p>2015-01-01</p> <p>Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to <span class="hlt">MODIS</span> data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp <span class="hlt">satellites</span> to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the <span class="hlt">MODIS</span> and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/24287529','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/24287529"><span id="translatedtitle">Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between <span class="hlt">MODIS</span> and 30 other <span class="hlt">satellite</span> sensors using rice canopy spectra.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing</p> <p>2013-01-01</p> <p>Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different <span class="hlt">satellite</span> sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation <span class="hlt">satellite</span> sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various <span class="hlt">satellite</span> instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra <span class="hlt">MODIS</span>, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra <span class="hlt">MODIS</span> ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between <span class="hlt">MODIS</span> and the other 30 <span class="hlt">satellite</span> sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between <span class="hlt">MODIS</span> and the other 30 <span class="hlt">satellite</span> sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3892887','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3892887"><span id="translatedtitle">Comparability of Red/Near-Infrared Reflectance and NDVI Based on the Spectral Response Function between <span class="hlt">MODIS</span> and 30 Other <span class="hlt">Satellite</span> Sensors Using Rice Canopy Spectra</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing</p> <p>2013-01-01</p> <p>Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different <span class="hlt">satellite</span> sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation <span class="hlt">satellite</span> sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various <span class="hlt">satellite</span> instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra <span class="hlt">MODIS</span>, the mean relative percentage difference (RPD) ranged from −12.67% to 36.30% for the red reflectance, −8.52% to −0.23% for the NIR reflectance, and −9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra <span class="hlt">MODIS</span> ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between <span class="hlt">MODIS</span> and the other 30 <span class="hlt">satellite</span> sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between <span class="hlt">MODIS</span> and the other 30 <span class="hlt">satellite</span> sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26158600','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26158600"><span id="translatedtitle">Intercomparison of Aerosol Optical Thickness Derived from <span class="hlt">MODIS</span> and in Situ Ground Datasets over Jaipur, a Semi-arid Zone in India.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Payra, Swagata; Soni, Manish; Kumar, Anikender; Prakash, Divya; Verma, Sunita</p> <p>2015-08-01</p> <p>The first detailed seasonal validation has been carried out for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> Level 2.0 Collection Version 5.1 AOT (τ<span class="hlt">MODIS</span>) with Aerosol Robotic Network (AERONET) Level 2.0 AOT (τAERONET) for the years 2009-2012 over semi-arid region Jaipur, northwestern India. The correlation between τ<span class="hlt">MODIS</span> versus τAERONET at 550 nm is determined with different spatial and temporal size windows. The τ<span class="hlt">MODIS</span> overestimates τAERONET within a range of +0.06 ± 0.24 during the pre-monsoon (April-June) season, while it underestimates the τAERONET with -0.04 ± 0.12 and -0.05 ± 0.18 during dry (December-March) and post-monsoon (October-November) seasons, respectively. Correlation without (with) error envelope has been found for pre-monsoon at 0.71 (0.89), post-monsoon at 0.76 (0.94), and dry season at 0.78 (0.95). τ<span class="hlt">MODIS</span> is compared to τAERONET at three more ground AERONET stations in India, i.e., Kanpur, Gual Pahari, and Pune. Furthermore, the performance of <span class="hlt">MODIS</span> Deep Blue and <span class="hlt">Aqua</span> AOT550 nm (τDB550 nm and τ<span class="hlt">Aqua</span>550 nm) with τAERONET is also evaluated for all considered sites over India along with a U.S. desert site at White Sand, Tularosa Basin, NM. The statistical results reveal that τ<span class="hlt">Aqua</span>550 nm performs better over Kanpur and Pune, whereas τDB550 nm performs better over Jaipur, Gual Pahari, and White Sand High Energy Laser Systems Test Facility (HELSTF) (U.S. site). PMID:26158600</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3337546','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3337546"><span id="translatedtitle">Terra and <span class="hlt">Aqua</span>: new data for epidemiology and public health</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Tatem, Andrew J.; Goetz, Scott J.; Hay, Simon I.</p> <p>2012-01-01</p> <p>Earth-observing <span class="hlt">satellites</span> have only recently been exploited for the measurement of environmental variables of relevance to epidemiology and public health. Such work has relied on sensors with spatial, spectral and geometric constraints that have allowed large-area questions associated with the epidemiology of vector-borne diseases to be addressed. Moving from pretty maps to pragmatic control tools requires a suite of <span class="hlt">satellite</span>-derived environmental data of higher fidelity, spatial resolution, spectral depth and at similar temporal resolutions to existing meteorological <span class="hlt">satellites</span>. Information derived from sensors onboard the next generation of moderate-resolution Earth-observing sensors may provide the key. The <span class="hlt">MODIS</span> and ASTER sensors onboard the Terra and <span class="hlt">Aqua</span> platforms provide substantial improvements in spatial resolution, number of spectral channels, choices of bandwidths, radiometric calibration and a much-enhanced set of pre-processed and freely available products. These sensors provide an important advance in moderate-resolution remote sensing and the data available to those concerned with improving public health. PMID:22545030</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3842799','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3842799"><span id="translatedtitle">Alaska ecosystem carbon fluxes estimated from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data inputs from 2000 to 2010</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2013-01-01</p> <p>Background Trends in Alaska ecosystem carbon fluxes were predicted from inputs of monthly MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) vegetation index time-series combined with the NASA-CASA (Carnegie Ames Stanford Approach) carbon cycle simulation model over the past decade. CASA simulates monthly net ecosystem production (NEP) as the difference in carbon fluxes between net primary production (NPP) and soil microbial respiration (Rh). Results Model results showed that NEP on a unit area basis was estimated to be highest (> +10 g C m-2 yr-1) on average over the period 2000 to 2010 within the Major Land Resource Areas (MRLAs) of the Interior Brooks Range Mountains, the Arctic Foothills, and the Western Brooks Range Mountains. The lowest (as negative land C source fluxes) mean NEP fluxes were predicted for the MLRAs of the Cook Inlet Lowlands, the Ahklun Mountains, and Bristol Bay-Northern Alaska Peninsula Lowlands. High levels of interannual variation in NEP were predicted for most MLRAs of Alaska. Conclusions The relatively warm and wet years of 2004 and 2007 resulted in the highest positive NEP flux totals across MLRAs in the northern and western coastal locations in the state (i.e., the Brooks Range Mountains and Arctic Foothills). The relatively cold and dry years of 2001 and 2006 were predicted with the lowest (negative) NEP flux totals for these MLRAs, and likewise across the Ahklun Mountains and the Yukon-Kuskokwim Highlands. PMID:24261829</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AMT.....5..389V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AMT.....5..389V"><span id="translatedtitle">Analysis of co-located <span class="hlt">MODIS</span> and CALIPSO observations near clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Várnai, T.; Marshak, A.</p> <p>2012-02-01</p> <p>This paper aims at helping synergistic studies in combining data from different <span class="hlt">satellites</span> for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the <span class="hlt">MODIS</span> (MODerate resolution Imaging Spectroradiometer) imager can refine our perceptions based on CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar measurements about the systematic aerosol changes that occur near clouds. The statistical analysis of a yearlong dataset of co-located global maritime observations from the <span class="hlt">Aqua</span> and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span> Observation) <span class="hlt">satellites</span> reveals that <span class="hlt">MODIS</span>'s multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on <span class="hlt">Aqua</span> and CALIPSO yield very similar pictures, and that the discrepancies - due mainly to wind drift and differences in view angle - do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, <span class="hlt">MODIS</span> reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in <span class="hlt">MODIS</span> and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when <span class="hlt">MODIS</span> cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. In maritime areas perceived cloud free, the global median distance to clouds below 3 km altitude is in the 4-5 km range.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080037745&hterms=new+product+development&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dnew%2Bproduct%2Bdevelopment','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080037745&hterms=new+product+development&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dnew%2Bproduct%2Bdevelopment"><span id="translatedtitle">Production and Distribution of NASA <span class="hlt">MODIS</span> Remote Sensing Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wolfe, Robert</p> <p>2007-01-01</p> <p>The two Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on-board NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from <span class="hlt">MODIS</span>/Terra for over 7 years and for <span class="hlt">MODIS/Aqua</span> for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the <span class="hlt">MODIS</span> Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original <span class="hlt">MODIS</span> science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to <span class="hlt">MODIS</span>, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006SPIE.6411E..23L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006SPIE.6411E..23L"><span id="translatedtitle">Assessment and monitoring of desertification using <span class="hlt">satellite</span> imagery of <span class="hlt">MODIS</span> in East Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lin, Meng-Lung; Chu, Chieh-Ming; Shih, Jyh-Yi; Wang, Qiu-Bing; Chen, Cheng-Wu; Wang, Shin; Tao, Yi-Huang; Lee, Yung-Tan</p> <p>2006-12-01</p> <p>The desertification in Northwestern China and Mongolia shows the result of conflicts between economic development and natural conservation. Many researches have proven the desert areas are growing in these regions. The variations of bi-weekly NDVI <span class="hlt">satellite</span> images are used as one of the parameters to evaluate the vegetation dynamics over large scale studies. In this study, remotely sensed <span class="hlt">satellite</span> images are conducted to provide multi-temporal vegetated and non-vegetated areas in order to assess the status of desertification in East Asia. Spatial data derived from these <span class="hlt">satellite</span> images are applied to evaluate vegetation dynamics at regional scale to find out the hot spot areas vulnerable to desertification. The results show that the desert areas are mainly distributed over southern Mongolia, central and western Inner-Mongolia, western China (the Taklimakan desert). The desert areas were expanded from 2000 to 2002, were shrunk in 2003, and were expanded from 2003 to 2005 again. The hot spot areas of desertification are mainly distributed over southeastern Mongolia and eastern Inner-Mongolia. The results will help administrators to refine the planning processes in defining the boundaries of protected areas and will facilitate to take decision of the priority areas for conservation of desertification.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130003322','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130003322"><span id="translatedtitle">Use of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Luvall, J. C.; Sprigg, W.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P.; Budge, A.; Hudspeth, W.; Krapfl, H.; Toth, B.; Zelicoff, A.; Myers, O.; Bunderson, L.; Ponce-Campos, G.; Crimmins, T.; Menache, M.</p> <p>2012-01-01</p> <p>Juniperus spp. pollen is a significant aeroallergen that can be transported 200-600 km from the source. Local observations of Juniperus spp. phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Methods: The Dust REgional Atmospheric Model (DREAM)is a verified model for atmospheric dust transport modeling using <span class="hlt">MODIS</span> data products to identify source regions and quantities of dust. We successfully modified the DREAM model to incorporate pollen transport (PREAM) and used <span class="hlt">MODIS</span> <span class="hlt">satellite</span> images to develop Juniperus ashei pollen input source masks. The Pollen Release Potential Source Map, also referred to as a source mask in model applications, may use different <span class="hlt">satellite</span> platforms and sensors and a variety of data sets other than the USGS GAP data we used to map J. ashei cover type. <span class="hlt">MODIS</span> derived percent tree cover is obtained from <span class="hlt">MODIS</span> Vegetation Continuous Fields (VCF) product (collection 3 and 4, MOD44B, 500 and 250 m grid resolution). We use updated 2010 values to calculate pollen concentration at source (J. ashei ). The original <span class="hlt">MODIS</span> derived values are converted from native approx. 250 m to 990m (approx. 1 km) for the calculation of a mask to fit the model (PREAM) resolution. Results: The simulation period is chosen following the information that in the last 2 weeks of December 2010. The PREAM modeled near-surface concentrations (Nm-3) shows the transport patterns of J. ashei pollen over a 5 day period (Fig. 2). Typical scales of the simulated transport process are regional.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ERL.....8c5035A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ERL.....8c5035A"><span id="translatedtitle">Mapping the extent of abandoned farmland in Central and Eastern Europe using <span class="hlt">MODIS</span> time series <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alcantara, Camilo; Kuemmerle, Tobias; Baumann, Matthias; Bragina, Eugenia V.; Griffiths, Patrick; Hostert, Patrick; Knorn, Jan; Müller, Daniel; Prishchepov, Alexander V.; Schierhorn, Florian; Sieber, Anika; Radeloff, Volker C.</p> <p>2013-09-01</p> <p>The demand for agricultural products continues to grow rapidly, but further agricultural expansion entails substantial environmental costs, making recultivating currently unused farmland an interesting alternative. The collapse of the Soviet Union in 1991 led to widespread abandonment of agricultural lands, but the extent and spatial patterns of abandonment are unclear. We quantified the extent of abandoned farmland, both croplands and pastures, across the region using <span class="hlt">MODIS</span> NDVI <span class="hlt">satellite</span> image time series from 2004 to 2006 and support vector machine classifications. Abandoned farmland was widespread, totaling 52.5 Mha, particularly in temperate European Russia (32 Mha), northern and western Ukraine, and Belarus. Differences in abandonment rates among countries were striking, suggesting that institutional and socio-economic factors were more important in determining the amount of abandonment than biophysical conditions. Indeed, much abandoned farmland occurred in areas without major constraints for agriculture. Our map provides a basis for assessing the potential of Central and Eastern Europe’s abandoned agricultural lands to contribute to food or bioenergy production, or carbon storage, as well as the environmental trade-offs and social constraints of recultivation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AnGla..46...35F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AnGla..46...35F"><span id="translatedtitle"><span class="hlt">Satellite</span>-derived surface type and melt area of the Greenland ice sheet using <span class="hlt">MODIS</span> data from 2000 to 2005</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fausto, Robert S.; Mayer, Christoph; Ahlstrøm, Andreas P.</p> <p>2007-10-01</p> <p>A new surface classification algorithm for monitoring snow and ice masses based on data from the moderate-resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) is presented. The algorithm is applied to the Greenland ice sheet for the period 2000-05 and exploits the spectral variability of ice and snow reflectance to determine the surface classes dry snow, wet snow and glacier ice. The result is a monthly glacier surface type (GST) product on a 1 km resolution grid. The GST product is based on a grouped criteria technique with spectral thresholds and normalized indices for the classification on a pixel-by-pixel basis. The GST shows the changing surface classes, revealing the impact of climate variations on the Greenland ice sheet over time. The area of wet snow and glacier ice is combined into the glacier melt area (GMA) product. The GMA is analyzed in relation to the different surface classes in the GST product. The results are validated with data from weather stations and similar types of <span class="hlt">satellite</span>-derived products. The validation shows that the automated algorithm successfully distinguishes between the different surface types, implying that the product is a promising indicator of climate change impact on the Greenland ice sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC21A1076P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC21A1076P"><span id="translatedtitle">Comparison of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Land Surface Temperature with Air Temperature along a 5000-metre Elevation Transect on Kilimanjaro, Tanzania.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pepin, N. C.; Williams, R.; Maeda, E. E.</p> <p>2015-12-01</p> <p>There is concern that high elevations may be warming more rapidly than lower elevations, but there is a lack of observational data from weather stations in the high mountains. One alternative data source is <span class="hlt">satellite</span> LST (Land Surface Temperature) which has extensive spatial coverage. This study compares instantaneous values of LST (1030 and 2230 local solar time) as measured by the <span class="hlt">MODIS</span> MOD11A2 product at 1 km resolution with equivalent screen level air temperatures (in the same pixel) measured from a transect of 22 in situ weather stations across Kilimanjaro ranging in elevation from 990 to 5803 m. Data consists of 11 years on the SW slope and 3 years on the NE slope, equating to >500 and ~140 octtads (8-day periods) respectively. Results show substantial differences between LST and local air temperature, sometimes up to 20C. During the day the LST tends to be higher than air temperature and the reverse is true at night. The differences show large variance, particularly during the daytime, and tend to increase with elevation, particularly on the NE slope of the mountain which faces the sun when the daytime observations are taken (1030 LST). Differences between LST and air temperature are larger in the dry seasons (JF and JJAS), and reduce when conditions are more cloudy. Systematic relationships with cloud cover and vegetation characteristics (as measured by NDVI and MAIAC for the same pixel) are displayed. More vegetation reduces daytime surface heating above the air temperature, but this relationship weakens with elevation. Nighttime differences are more stable and show no relationship with vegetation indices. Therefore the predictability of the LST/air temperature differences reduces at high elevations and it is therefore much more challenging to use <span class="hlt">satellite</span> data at high elevations to complement in situ air temperature measurements for climate change assessments, especially for daytime maximum temperatures.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113289D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113289D"><span id="translatedtitle">On the evaluation of vegetation resilience in Southern Italy by using VEGETATION, <span class="hlt">MODIS</span>, TM <span class="hlt">satellite</span> time series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Didonna, I.; Coluzzi, R.</p> <p>2009-04-01</p> <p><span class="hlt">Satellite</span> technologies can be profitably used for investigating the dynamics of vegetation re-growth after disturbance at different temporal and spatial scales. Nevertheless, disturbance -induced dynamical processes are very difficult to study since they affect the complex soil-surface-atmosphere system, due to the existence of feedback mechanisms involving human activity, ecological patterns and different subsystems of climate. The remote sensing of vegetation has been traditionally carried out by using vegetation indices, which are quantitative measures, based on vegetation spectral properties, that attempt to measure biomass or vegetative vigor. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. The simplest form of vegetation index is simply a ratio between two digital values from these two spectral bands. The most widely used index is the well-known normalized difference vegetation index NDVI = [NIR-R]/ [NIR+R]. The normalization of the NDVI reduces the effects of variations caused by atmospheric contaminations. High values of the vegetation index identify pixels covered by substantial proportions of healthy vegetation. NDVI is indicative of plant photosynthetic activity and has been found to be related to the green leaf area index and the fraction of photosynthetically active radiation absorbed by vegetation. Variations in NDVI values become indicative of variations in vegetation composition and dynamics. In this study, we analyze the mutiscale <span class="hlt">satellite</span> temporal series ( 2000 to 2008) of NDVI and other vegetation indices from SPOT VEGETATION, <span class="hlt">MODIS</span> and Landsat TM data acquired for some significant test areas affetced and unaffected (Southern Italy) by different types of environmental diturbances (drought, salinity, pollution, etc). Our objective was to characterize quantitatively the resilient effect of vegetation cover at differen temporal and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/22200944','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/22200944"><span id="translatedtitle">Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/<span class="hlt">MODIS</span> <span class="hlt">satellite</span> data.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Patel, N R; Parida, B R; Venus, V; Saha, S K; Dadhwal, V K</p> <p>2012-12-01</p> <p>The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T (s)) from <span class="hlt">MODIS</span> 8-day composite data during cloud-free period (September-October) were adopted to construct an NDVI-T (s) space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut. PMID:22200944</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001AGUFMOS52A0517K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001AGUFMOS52A0517K"><span id="translatedtitle"><span class="hlt">MODIS</span> Ocean Color, SST and Primary Productivity Products at the NASA Goddard Earth Sciences DAAC</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Koziana, J.; Leptoukh, G.; Savtchenko, A.; Serafino, G.; Sharma, A. K.</p> <p>2001-12-01</p> <p>The Goddard Earth Science (GES) Distributed Active Archive Center (DAAC) plays a major role in enabling basic scientific research and providing access to scientific data for the user community through the ingest, processing, archive and distribution of <span class="hlt">MODIS</span> data. <span class="hlt">MODIS</span> is part of the instrument package on the Terra (formally AM-1) <span class="hlt">satellite</span> that was launched on December 18. 1999. Global scale ocean products are derived from many of the 36 different wavelengths measured by the <span class="hlt">MODIS</span>/Terra instrument and are archived at a rate of about 230 GB/day. This paper will provide a description of the <span class="hlt">MODIS</span> Ocean data products and associated geophysical parameters, data access, data availability and tools. The full suite of ocean products is grouped into three categories: ocean color, SST and primary productivity. The amount of <span class="hlt">MODIS</span> ocean data being archived at the DAAC will increase dramatically in the near future when the data from the <span class="hlt">MODIS</span> instrument onboard the <span class="hlt">Aqua</span> (formally PM-1) spacecraft begins transmission. This will result in a significant increase in the volume of ocean data being ingested, archived and distributed at the GES DAAC. The current suite of products will be generated for both Terra and <span class="hlt">Aqua</span>. In addition, joint Terra/<span class="hlt">Aqua</span> ocean products will be derived. The challenge, to distribute such large volumes of data to the ocean community, is achieved through a combination of GES DAAC Hierarchical Search and Order Tool known as, WHOM, and EOS Data Gateway (EDG) World Wide Web (WWW) interfaces and an FTP site that contains samples of <span class="hlt">MODIS</span> data. The <span class="hlt">MODIS</span> Data Support Team (MDST) continues the tradition of quality support at the GES DAAC for the ocean color data from CZCS and SeaWiFS by providing expert assistance to users in accessing data products, information on visualization tools, documentation for data products and formats (HDF-EOS), information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/<span class="hlt">MODIS</span>/index.html</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040015040','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040015040"><span id="translatedtitle"><span class="hlt">MODIS</span> Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fargion, Giulietta S.; McClain, Charles R.</p> <p>2003-01-01</p> <p>The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, <span class="hlt">satellite</span> 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 <span class="hlt">satellite</span> systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Earth Observing System (EOS) Terra platform (similar evaluations of <span class="hlt">MODIS/Aqua</span> are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040034204','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040034204"><span id="translatedtitle">Passive and Active Detection of Clouds: Comparisons between <span class="hlt">MODIS</span> and GLAS Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mahesh, Ashwin; Gray, Mark A.; Palm, Stephen P.; Hart, William D.; Spinhirne, James D.</p> <p>2003-01-01</p> <p>The Geoscience Laser Altimeter System (GLAS), launched on board the Ice, Cloud and Land Elevation <span class="hlt">Satellite</span> in January 2003 provides space-borne laser observations of atmospheric layers. GLAS provides opportunities to validate passive observations of the atmosphere for the first time from space with an active optical instrument. Data from the Moderate Resolution Imaging Spectrometer aboard the <span class="hlt">Aqua</span> <span class="hlt">satellite</span> is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, <span class="hlt">MODIS</span> scene identification from spectral radiances agrees with GLAS. Disagreement between the two platforms is most significant over snow-covered surfaces in the northern hemisphere. Daytime clouds detected by GLAS are also more easily seen in the <span class="hlt">MODIS</span> data as well, compared to observations made at night. These comparisons illustrate the capabilities of active remote sensing to validate and assess passive measurements, and also to complement them in studies of atmospheric layers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT........33Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT........33Z"><span id="translatedtitle">Determination of the single scattering albedo and direct radiative forcing of biomass burning aerosol with data from the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) <span class="hlt">satellite</span> instrument</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhu, Li</p> <p></p> <p>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 <span class="hlt">satellite</span> 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 (<span class="hlt">MODIS</span>) observed reflectance at the top of the atmosphere (TOA). We evaluated <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> Enhanced Vegetation Albedo (MEVA), to improve the representations of spectral variations of vegetation surface albedo based on <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> retrieved biomass burning aerosol SSA and the surface albedo spectrum determined from the MEVA technique to calculate TOA flux and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010JPRS...65..380P&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010JPRS...65..380P&link_type=ABSTRACT"><span id="translatedtitle">Early-season crop area estimates for winter crops in NE Australia using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Potgieter, A. B.; Apan, A.; Hammer, G.; Dunn, P.</p> <p></p> <p>To date, industry and crop forecasters have had a good idea of the potential crop yield for a specific season, but early-season information on crop area for a shire or region has been mostly unavailable. The question of "how early and with what accuracy?" area estimates can be determined using multi-temporal Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) enhanced vegetation index (EVI) imagery was investigated in this paper. The study was conducted for two shires in Queensland, Australia for the 2003 and 2004 seasons, and focused on deriving total winter crop area estimates (including wheat, barley and chickpea). A simple metric ( ΔE), which measures the green-up rate of the crop canopy, was derived. Using the unsupervised k-means classification algorithm, the accumulated difference of two consecutive images (one month apart) for three EVI threshold cut-offs ( ΔEi, where i=250, 500 and 750) at monthly intervals from April to October was calculated. July showed the highest pixel accuracy with percent correctly classified for all thresholds of 94% and 98% for 2003 and 2004, respectively. The differences in accuracy between the three cut-offs were minimal and the T500 threshold was selected as the preferred cut-off to avoid measuring too small or too large fluctuations in the differential EVI values. When compared to the aggregated shire data (surveyed) on crop area across shires and seasons, average percent differences for the ΔE for July and August ranged from -19% to 9%. To capture most of the variability in green-up within a region, the average ΔE of July and August was used for the early-season prediction of total winter crop area estimates. This resulted in high accuracy (R 2=0.96; RMSE = 3157 ha) for predicting the total winter crop from 2000 to 2004 across both shires. This result indicated that this simple multi-temporal remote sensing approach could be used with confidence in early-season crop area prediction at least one to two months ahead of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030020719&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030020719&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems"><span id="translatedtitle">Remote Sensing of Cloud, Aerosol, and Land Properties from <span class="hlt">MODIS</span>: Applications to the East Asia Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Moody, Eric G.</p> <p>2002-01-01</p> <p><span class="hlt">MODIS</span> is an earth-viewing cross-track scanning spectroradiometer launched on the Terra <span class="hlt">satellite</span> in December 1999 and the <span class="hlt">Aqua</span> <span class="hlt">satellite</span> in May 2002. <span class="hlt">MODIS</span> scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using <span class="hlt">MODIS</span> data, focusing primarily on (i) the <span class="hlt">MODIS</span> cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral reflectance. The physical principles behind the determination of each of these products will be described, together with an example of their application using <span class="hlt">MODIS</span> observations to the east Asian region. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 min (Level-3 products).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.B32D..02D&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.B32D..02D&link_type=ABSTRACT"><span id="translatedtitle">Urban Area Monitoring using <span class="hlt">MODIS</span> Time Series Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Devadiga, S.; Sarkar, S.; Mauoka, E.</p> <p>2015-12-01</p> <p>Growing urban sprawl and its impact on global climate due to urban heat island effects has been an active area of research over the recent years. This is especially significant in light of rapid urbanization that is happening in some of the first developing nations across the globe. But so far study of urban area growth has been largely restricted to local and regional scales, using high to medium resolution <span class="hlt">satellite</span> observations, taken at distinct time periods. In this presentation we propose a new approach to detect and monitor urban area expansion using long time series of <span class="hlt">MODIS</span> data. This work characterizes data points using a vector of several annual metrics computed from the <span class="hlt">MODIS</span> 8-day and 16-day composite L3 data products, at 250M resolution and over several years and then uses a vector angle mapping classifier to detect and segment the urban area. The classifier is trained using a set of training points obtained from a reference vector point and polygon pre-filtered using the <span class="hlt">MODIS</span> VI product. This work gains additional significance, given that, despite unprecedented urban growth since 2000, the area covered by the urban class in the <span class="hlt">MODIS</span> Global Land Cover (MCD12Q1, MCDLCHKM and MCDLC1KM) product hasn't changed since the launch of Terra and <span class="hlt">Aqua</span>. The proposed approach was applied to delineate the urban area around several cities in Asia known to have maximum growth in the last 15 years. Results were verified using high resolution Landsat data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A51B3032C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A51B3032C"><span id="translatedtitle">Using the Mixed Effect Model as an Alternative Approach to Improve Correlation between <span class="hlt">Satellite</span> Derived Aerosol Optical Depth (MISR & <span class="hlt">MODIS</span>) and Ground Measured PM2.5 Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cabanes, H. V. O.; Lagrosas, N.</p> <p>2014-12-01</p> <p>The study seeks to determine the efficacy of using aerosol optical depth (AOD) data from MISR and <span class="hlt">MODIS</span> as a surrogate for ground-based particulate matter (PM2.5) data by using AOD as an input for various computational methods. The data set used in the study ranged from January 2011 to December 2012. The advantage of the mixed effects model is in its ability to consider temporally changing attributes through the inclusion of random effects in the regression model. The study first established that MISR and <span class="hlt">MODIS</span> AOD has a correlation with ground measured PM2.5 through regression analysis thereby providing rationale for further analysis. The regression analyses resulted in an R2 of 0.7513 and 0.7536 for <span class="hlt">MODIS</span> and MISR, respectively. With the rationale established, data quality improvement measures were carried out through data screening and empirical correction. The data screening process involved the removal of data entries in which the absolute difference of <span class="hlt">MODIS</span> and MISR AOD values deviated far more than the average of the data set. On the other hand, empirical correction was done by developing correction equations through multivariate regression with ground parameters such as AERONET AOD, relative humidity, and wind speed. Both methods were found to yield marked improvement in the correlation of <span class="hlt">satellite</span>-derived AOD with PM2.5. After data quality had been improved, several computational methods are assessed by solving for the R2 and absolute error percentage. The methods are simple linear regression with <span class="hlt">MODIS</span> (R2 = 0.7764, 18.43%) and MISR (R2 = 0.7614, 17.99%), multivariate linear regression with <span class="hlt">MODIS</span> and MISR together (R2 = 0.8721, 13.63%), artificial neural network with <span class="hlt">MODIS</span> and MISR as inputs (R2 = 0.8764, 13.45%), and the mixed effects model with <span class="hlt">MODIS</span> and MISR as predictors (R2 = 0.9793, 5.20%). Among these, the mixed effects model performed the best and further error analysis showing an error that was independent on seasonality and dependent on the PM</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012EGUGA..14.9747O&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012EGUGA..14.9747O&link_type=ABSTRACT"><span id="translatedtitle">Monitoring the spatial and temporal dynamics of annual floods in the Niger Inner Delta using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ogilvie, A.; Belaud, G.; Delenne, C.; Bader, J.-C.; Oleksiak, A.; Bailly, J.-S.</p> <p>2012-04-01</p> <p>The Niger Inner Delta is a vast three million hectare wetland in Mali, whose annual flood supports the livelihoods of over one million herders, fishermen and farmers. Large projects on the Niger River upstream may however alter the extent and dynamics of the flood in the future. Due to the scale (about 50 000 km2) and the very flat topography of this hydrological system, there is very scarce ground data to characterise the flood and its spatial and temporal dynamics remain poorly understood. Since the flood is mainly caused by precipitation in the upper catchment, the flood peak in the delta occurs a few weeks after the rainy season, when cloud cover does not limit the use of optical remote sensing data. An original automated method was developed to study the progress of the flooding using normalised band ratio indices on 8-day <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) 500m-<span class="hlt">satellite</span> images. The Modified Normalised Difference Water Index (MNDWI) was shown to be the most suitable for detecting flooded areas out of six commonly used band ratio indices. Its combination with the Normalised Difference Moisture Index (NDMI) aids the distinction between flooded and humid vegetation, especially in the drier months when the flood recedes. Three 30m Landsat images covering different phases of the flood, on which K-means clustering and analysis of spectral profiles enabled the identification of flooded pixels, were used to calibrate the threshold values of both indices. A programme using a specific composite MNDWI-NDMI index, with constant thresholds and a topographically relevant grid of the river and its floodplain was developed in ENVI IDL© to automatically provide the percentage of flooded pixels per grid cell for each image. The method was validated by computing correlations between water depth measurements from gauging stations in the delta and the flooded surface area for the corresponding grid cell calculated from the <span class="hlt">MODIS</span> images. Estimates of the total</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A44B..04A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A44B..04A"><span id="translatedtitle"><span class="hlt">Modis</span> Bits: when a Byte Isn't Enough</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ackerman, S. A.; Frey, R.; Holz, R.</p> <p>2013-12-01</p> <p>Assessments of the final results of the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) cloud mask have been studied and published. In this presentation, we present an assessment of the individual and group tests using the bit output structure of the <span class="hlt">MODIS</span> cloud mask algorithm. The <span class="hlt">MODIS</span>) on the NASA Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> provides an unprecedented opportunity for earth remote sensing. Its broad spectral range (36 bands between 0.415-14.235 microns), high spatial resolution (250 m for two bands, 500 m for 5 bands, 1000 m for 29 bands), frequent observations of polar regions (28 times a day), and low thermal band instrument noise (roughly 0.1 K for a 300 K scene) provide a number of possibilities for improving cloud detection. <span class="hlt">MODIS</span> scans a swath width sufficient for providing global coverage every two days from a polar-orbiting, sun-synchronous platform at an altitude of 705 km. The <span class="hlt">MODIS</span> products, including MOD021KM, MOD03 and the cloud mask (MOD35), were obtained from the NASA Goddard Space Flight Center Distributed Active Archive Center (GDAAC). The <span class="hlt">MODIS</span> cloud mask algorithm includes several domains defined according to latitude, surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. A series of spectral tests is applied to identify the presence of clouds. There are several groups of tests, with differing numbers of tests in each group depending on the domain. A clear-sky confidence level ranging from 1 (high) to 0 (low) is returned for each test. The minimum confidence from all tests within a group is taken to be representative of that group. The Nth root of the product of all the group confidences (Q) determines the final confidence, where N is the number of groups. A fused data set of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard NASA's Cloud Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span> Observation (CALIPSO; data retrieved from the NASA CALIOPSO DAAC) and observations</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.3132T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.3132T"><span id="translatedtitle">Using <span class="hlt">MODIS</span> data to estimate river discharge in ungauged sites</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tarpanelli, A.; Brocca, L.; Lacava, T.; Faruolo, M.; Melone, F.; Moramarco, T.; Pergola, N.; Tramutoli, V.</p> <p>2012-04-01</p> <p>The discharge prediction at a river site is fundamental for water resources management and flood risk prevention. An accurate discharge estimation depends on local hydraulic conditions which are usually detected by recording water level and carrying out flow measurements, which are costly and sometimes impractical for high flows. Over the last decade, the possibility to obtain river discharge estimates from <span class="hlt">satellite</span> sensors data has become of considerable interest. For large river basins, the use of <span class="hlt">satellite</span> data derived by altimeter and microwave sensors, characterized by a daily temporal resolution, has proven to be a useful tool to integrate or even increase the discharge monitoring. For smaller basins, Synthetic Aperture Radars (SARs) have been usually employed for the indirect estimation of water elevation but their low temporal resolution (from a few days up to 30 days) might be considered not suitable for discharge prediction. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard of Terra and <span class="hlt">Aqua</span> Earth Observing System (EOS) <span class="hlt">satellites</span>, can provide a proper tradeoff between temporal and spatial resolution useful for discharge estimation. It assures, in fact, at least a daily temporal resolution and a spatial resolution up to 250 m in the first two channels. In this study, the capability of <span class="hlt">MODIS</span> data for discharge prediction is investigated. Specifically, the different spectral behavior of water and land in the Near Infrared (NIR) portion of the electromagnetic spectrum (<span class="hlt">MODIS</span> channel 2) is exploited by computing the ratio of the <span class="hlt">MODIS</span> channel 2 reflectance values between two pixels located within and outside the river. Values of such a ratio should increase when more water and, hence, discharge, is present. Time series of daily water level, velocity and discharge between 2002 and 2010 measured at different gauging stations located along the Upper Tiber River (central Italy) and the Po River (North Italy), as well as <span class="hlt">MODIS</span> channel 2 data for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..534..466D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..534..466D"><span id="translatedtitle">Improving the accuracy of <span class="hlt">MODIS</span> 8-day snow products with in situ temperature and precipitation data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dong, Chunyu; Menzel, Lucas</p> <p>2016-03-01</p> <p><span class="hlt">MODIS</span> snow data are appropriate for a wide range of eco-hydrological studies and applications in the fields of snow-related hazards, early warning systems and water resources management. However, the high spatio-temporal resolution of the remotely sensed data is often biased by snow misclassifications, and cloud cover frequently limits the availability of the <span class="hlt">MODIS</span>-based snow cover information. In this study, we applied a four-step methodology that aims to optimize the accuracy of <span class="hlt">MODIS</span> snow data. To reduce the cloud fraction, 8-day <span class="hlt">MODIS</span> data from both the <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span> were combined. Neighborhood analysis was applied as well for this purpose, and it also contributed to the retrieval of some omitted snow. Two meteorological filters were then applied to combine information from station-based measurements of minimum ground temperature, precipitation and air temperature. This procedure helped to reduce the overestimation of snow cover. To test this technique, the methodology was applied to the Rhineland-Palatinate region in southwestern Germany (approximately 20,000 km2), where cloud cover is especially high during winter and surface heterogeneity is complex. The results show that mean annual cloud coverage (reference period 2002-2013) of the 8-day <span class="hlt">MODIS</span> snow maps could be reduced using this methodology from approximately 14% to 4.5%. During the snow season, obstruction by clouds could be reduced by even a higher degree, but still remains at about 11%. Further, the overall snow overestimation declined from 11.0-11.9% (using the original <span class="hlt">Aqua</span>-Terra data) to 1.0-1.5%. The method is able to improve the overall accuracy of the 8-day <span class="hlt">MODIS</span> snow product from originally 78% to 89% and even to 93% during cloud free periods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040016045&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040016045&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille"><span id="translatedtitle">The <span class="hlt">MODIS</span> Aerosol Algorithm, Products, Validation and Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, L. A.; Kaufman, Y. J.; Tanre, D.</p> <p>2003-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) currently aboard both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> 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, complementing field and modeling efforts to produce a comprehensive picture of aerosol characteristics. The three years of Terra-<span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> aerosol optical thickness retrievals are accurate to within the pre-launch expectations. <span class="hlt">MODIS</span>-derived size parameters are also compared with AERONET retrievals and found to agree well for fine-mode dominated aerosol regimes. Aerosol regimes dominated by dust aerosol are less accurate, attributed to what is thought to be nonsphericity. Errors due to nonsphericity will be reduced by introducing a new set of empirical phase functions, derived without any assumptions of particle shape. The major innovation that <span class="hlt">MODIS</span> bring to the field of remote sensing of aerosol is the measure of particle size and the separation of finemode and coarsemode dominated aerosol regimes. Particle size can separate finemode man-made aerosols created during combustion, from larger natural aerosols originating from salt spray or wind erosion. This separation allows for the calculation of aerosol radiative effect and the estimation of the man-made aerosol radiative forcing. <span class="hlt">MODIS</span> can also be used in regional studies of aerosol-cloud interaction that affect the global radiative and hydrological cycles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A13J0315L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A13J0315L"><span id="translatedtitle">From <span class="hlt">MODIS</span> to VIIRS: Steps toward continuing the dark-target aerosol climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Mattoo, S.; Liu, H.; Munchak, L. A.; Laszlo, I.; Cronk, H.</p> <p>2012-12-01</p> <p>By this fall-2012 AGU meeting, the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) has been flying on NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> for 13 years and 10.5 years, respectively. During this time, the <span class="hlt">MODIS</span> Aerosol Science Team has fine-tuned the aerosol retrieval algorithms and data processing protocols, resulting in a highly robust, stable and usable aerosol product. The aerosol optical depth (AOD) product has been validated extensively, and the <span class="hlt">MODIS</span>-retrieved environmental data record (EDR) is becoming a strong foundation for creating an aerosol climate data record (CDR). With last year's launch of the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, the VIIRS-derived aerosol product has been designed to continue that provided by <span class="hlt">MODIS</span>. VIIRS and <span class="hlt">MODIS</span> have similar orbital mechanics and provide similar spectral resolution with similar spatial resolution. At the same time, the VIIRS and <span class="hlt">MODIS</span> aerosol algorithms have similar physical assumptions. In fact, the initial validation exercises suggest that, in general, the VIIRS aerosol product is performing well, and that the expected error for the VIIRS-derived AOD is similar to that reported by <span class="hlt">MODIS</span>. Although VIIRS should be able to derive an aerosol product similar in quality to <span class="hlt">MODIS</span>, can the VIIRS aerosol record be "stitched" together with the <span class="hlt">MODIS</span> record? To answer this question, instead of qualifying how similar they are, we need to quantify how their differences can and do impact the resulting aerosol products. There are instrumental differences, such as orbit altitude (805km versus 705km), spatial resolution (375m/750m versus 250m/500m/1000m), spectral differences, and sampling differences). There are pre-processing differences (cloud masking, gas correction assumptions, pixel selection protocols). There are retrieval algorithm differences, and of course final processing and quality control differences. Although we expect that most of differences have little or no impact, some may be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060046366','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060046366"><span id="translatedtitle">Multilayered Clouds Identification and Retrieval for CERES Using <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung</p> <p>2006-01-01</p> <p>Traditionally, analyses of <span class="hlt">satellite</span> data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using <span class="hlt">satellite</span> data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from <span class="hlt">satellite</span> microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on <span class="hlt">Aqua</span>, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to <span class="hlt">MODIS</span> and AMSR-E data taken from the <span class="hlt">Aqua</span> <span class="hlt">satellite</span> over non-polar ocean surfaces.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010cosp...38..365C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010cosp...38..365C"><span id="translatedtitle">Near real-time model to monitor SST anomalies related to undersea earthquakes and SW monsoon phenomena from TRMM-<span class="hlt">AQUA</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chakravarty, Subhas</p> <p></p> <p>Near real-time interactive computer model has been developed to extract daily mean global Sea Surface Temperature (SST) values of 1440x720 pixels, each one covering 0.25° x0.25° lat-long area and SST anomalies from longer period means pertaining to any required oceanic grid size of interest. The core MATLAB code uses the daily binary files (3-day aggregate values) of global SST data (derived from TRMM/TMI-<span class="hlt">AQUA</span>/AMSRE <span class="hlt">satellite</span> sensors) available on near real-time basis through the REMSS/NASA website and converts these SSTs into global/regional maps and displays as well as digitised text data tables for further analysis. As demonstrated applications of the model, the SST data for the period between 2003-2009 has been utilised to study (a) SST anomalies before, during and after the occurrence of two great under-sea earthquakes of 26 December 2004 and 28 March 2005 near the western coast of Sumatra and (b) variation of pixel numbers with SSTs between 27-31° C within (i) Nino 4 region and (ii) a broader western Pacific region (say Nino-BP) affected by ENSO events before (January-May) and during (June-October) Monsoon onset/progress. Preliminary results of these studies have been published (Chakravarty, The Open Oceanography Journal, 2009 and Chakravarty, IEEE Xplore, 2009). The results of the SST-earthquake analysis indicate a small but consistent warming of 0.2-0.3° C in the 2° x2° grid area near the earthquake epicentre starting a week earlier to a week later for the event of 26 December 2004. The changes observed in SST for the second earthquake is also indicated but with less clarity owing to the mixing of land and ocean surfaces and hence less number of SST pixels available within the 2° x 2° grid area near the corresponding epicen-tre. Similar analysis for the same period of non-earthquake years did not show any such SST anomalies. These results have far reaching implications to use SST as a possible parameter to be monitored for signalling occurrence of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012139&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012139&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dhdf"><span id="translatedtitle">CERES Monthly Gridded Single <span class="hlt">Satellite</span> TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Edition2A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012117&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012117&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dhdf"><span id="translatedtitle">CERES Monthly Gridded Single <span class="hlt">Satellite</span> TOA and Surfaces/Clouds(SFC) data in HDF (CER_SFC_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Edition1B)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012138&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012138&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dhdf"><span id="translatedtitle">CERES Monthly Gridded Single <span class="hlt">Satellite</span> TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Edition2A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012EGUGA..1414064L&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012EGUGA..1414064L&link_type=ABSTRACT"><span id="translatedtitle">Daily estimates of fire danger using multitemporal <span class="hlt">satellite</span> <span class="hlt">MODIS</span> data: the experience of FIRE-SAT in the Basilicata Region (Italy)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lanorte, R.; Lasaponara, R.; De Santis, F.; Aromando, A.; Nole, G.</p> <p>2012-04-01</p> <p>Daily estimates of fire danger using multitemporal <span class="hlt">satellite</span> <span class="hlt">MODIS</span> data: the experience of FIRE-SAT in the Basilicata Region (Italy) A. Lanorte, F. De Santis , A. Aromando, G. Nolè, R. Lasaponara, CNR-IMAA, Potenza, Italy In the recent years the Basilicata Region (Southern Italy) has been characterized by an increasing incidence of fire disturbance which also tends to affect protected (Regional and national parks) and natural vegetated areas. FIRE_SAT project has been funded by the Civil Protection of the Basilicata Region in order to set up a low cost methodology for fire danger/risk monitoring based on <span class="hlt">satellite</span> Earth Observation techniques. To this aim, NASA Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data were used. The spectral capability and daily availability makes <span class="hlt">MODIS</span> products especially suitable for estimating the variations of fuel characteristics. This work presents new significant results obtained in the context of FIRE-SAT project. In order to obtain a dynamical indicator of fire susceptibility based on multitemporal <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data, up-datable in short-time periods (daily), we used the spatial/temporal variations of following parameters: (1) Relative Greenness Index (2) Live and dead fuel moisture content (3) Temperature In particular, the dead fuel moisture content is a key factor in fire ignition. Dead fuel moisture dynamics are significantly faster than those observed for live fuel. Dead fine vegetation exhibits moisture and density values dependent on rapid atmospheric changes and strictly linked to local meteorological conditions. For this reason, commonly, the estimation of dead fuel moisture content is based on meteorological variables. In this study we propose to use <span class="hlt">MODIS</span> data to estimate meteorological data (specifically Relative Humidity) at an adequate spatial and temporal resolution. The assessment of dead fuel moisture content plays a decisive role in determining a fire dynamic danger index in combination with other</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016EGUGA..1814368J&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016EGUGA..1814368J&link_type=ABSTRACT"><span id="translatedtitle">Estimation of snowpack matching ground-truth data and <span class="hlt">MODIS</span> <span class="hlt">satellite</span>-based observations by using regression kriging</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Juan Collados-Lara, Antonio; Pardo-Iguzquiza, Eulogio; Pulido-Velazquez, David</p> <p>2016-04-01</p> <p>The estimation of Snow Water Equivalent (SWE) is essential for an appropriate assessment of the available water resources in Alpine catchment. The hydrologic regime in these areas is dominated by the storage of water in the snowpack, which is discharged to rivers throughout the melt season. An accurate estimation of the resources will be necessary for an appropriate analysis of the system operation alternatives using basin scale management models. In order to obtain an appropriate estimation of the SWE we need to know the spatial distribution snowpack and snow density within the Snow Cover Area (SCA). Data for these snow variables can be extracted from in-situ point measurements and air-borne/space-borne remote sensing observations. Different interpolation and simulation techniques have been employed for the estimation of the cited variables. In this paper we propose to estimate snowpack from a reduced number of ground-truth data (1 or 2 campaigns per year with 23 observation point from 2000-2014) and <span class="hlt">MODIS</span> <span class="hlt">satellite</span>-based observations in the Sierra Nevada Mountain (Southern Spain). Regression based methodologies has been used to study snowpack distribution using different kind of explicative variables: geographic, topographic, climatic. 40 explicative variables were considered: the longitude, latitude, altitude, slope, eastness, northness, radiation, maximum upwind slope and some mathematical transformation of each of them [Ln(v), (v)^-1; (v)^2; (v)^0.5). Eight different structure of regression models have been tested (combining 1, 2, 3 or 4 explicative variables). Y=B0+B1Xi (1); Y=B0+B1XiXj (2); Y=B0+B1Xi+B2Xj (3); Y=B0+B1Xi+B2XjXl (4); Y=B0+B1XiXk+B2XjXl (5); Y=B0+B1Xi+B2Xj+B3Xl (6); Y=B0+B1Xi+B2Xj+B3XlXk (7); Y=B0+B1Xi+B2Xj+B3Xl+B4Xk (8). Where: Y is the snow depth; (Xi, Xj, Xl, Xk) are the prediction variables (any of the 40 variables); (B0, B1, B2, B3) are the coefficients to be estimated. The ground data are employed to calibrate the multiple regressions. In</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2171368','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2171368"><span id="translatedtitle">Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Scharlemann, Jörn P. W.; Benz, David; Hay, Simon I.; Purse, Bethan V.; Tatem, Andrew J.; Wint, G. R. William; Rogers, David J.</p> <p>2008-01-01</p> <p>Background Remotely-sensed environmental data from earth-orbiting <span class="hlt">satellites</span> 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 (<span class="hlt">MODIS</span>) sensors on-board NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> 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. <span class="hlt">MODIS</span> data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> data for the period from 2001 to 2005. Conclusions/Significance Global temporal Fourier processed images of 1 km <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling. PMID:18183289</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C43D0433M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C43D0433M"><span id="translatedtitle"><span class="hlt">MODIS</span> Data and Services at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McAllister, M.; Booker, L.; Fowler, D. K.; Haran, T. M.</p> <p>2014-12-01</p> <p>For close to 15 years, the National Snow and Ice Data Center (NSIDC) NASA Distributed Active Archive Center (NDAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span>. The archive contains a wide selection of snow and sea ice data products relevant to cryospheric science. NSIDC offers a variety of methods for obtaining these data. Users can ftp data directly from an online archive which allows for a very quick download. The Reverb Search & Order Tool contains a complete set of metadata for all products which can be searched for and ordered. Reverb allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new <span class="hlt">MODIS</span> data automatically ftp'd or staged on a local server as it is archived at NSIDC. Since <span class="hlt">MODIS</span> products are in HDF-EOS format, a number of tools have been developed to assist with browsing, editing, reprojection, resampling, and format conversion. One such service, Data Access, can be accessed through Reverb and performs subsetting, reformatting, and reprojection. This service can also be accessed via an Application Programming Interface (API) from a user-written client. Other tools include the <span class="hlt">MODIS</span> Swath-to-Grid Toolbox (MS2GT) and the <span class="hlt">MODIS</span> Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute <span class="hlt">MODIS</span> scenes. NSIDC also created the MIST to provide subsets of certain Version 5 <span class="hlt">MODIS</span> products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations. Tools from other sources include HDFView from the National Center for Supercomputing Applications (NCSA), and the <span class="hlt">MODIS</span> Reprojection Tool (MRT) and MRT Swath developed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011189','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011189"><span id="translatedtitle"><span class="hlt">MODIS</span> 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Munchak, L. A.; Levy, R. C.; Mattoo, S.; Remer, L. A.; Holben, B. N.; Schafer, J. S.; Hostetler, C. A.; Ferrare, R. A.</p> <p>2013-01-01</p> <p>MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments aboard the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the <span class="hlt">MODIS</span> aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, <span class="hlt">MODIS</span> Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km <span class="hlt">MODIS</span> pixel, meaning that higher resolution <span class="hlt">satellite</span> retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of <span class="hlt">MODIS</span>/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the <span class="hlt">MODIS</span> 3 km product adds new information to the existing set of <span class="hlt">satellite</span> derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007890','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007890"><span id="translatedtitle">Estimation of Surface Air Temperature from <span class="hlt">MODIS</span> 1km Resolution Land Surface Temperature Over Northern China</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina</p> <p>2010-01-01</p> <p>Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and <span class="hlt">satellite</span> remotely sensed land surface temperature from <span class="hlt">MODIS</span> over the dry and semiarid regions of northern China. Studies were conducted for both <span class="hlt">MODIS</span>-Terra and <span class="hlt">MODIS-Aqua</span> by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and <span class="hlt">MODIS</span> land surface temperature, surface maximum and minimum air temperatures are estimated from 1km <span class="hlt">MODIS</span> land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004SPIE.5542...14B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004SPIE.5542...14B"><span id="translatedtitle"><span class="hlt">MODIS</span> instrument status and operational activities</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barnes, William L.; Xiong, Xiaoxiong; Salomonson, Vincent V.</p> <p>2004-10-01</p> <p>The Terra <span class="hlt">MODIS</span> and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have been successfully operated on-orbit for a total of more than six and a half years, collecting data for the science and applications communities to develop and enhance their understanding of the Earth/atmosphere system and to support studies of the climate and climate changes. Since its launch in December 1999, the Terra <span class="hlt">MODIS</span> has experienced several changes of its operational configuration either caused by the failure of individual electronics subsystems or purposely switched for better signal response or data quality. Excluding minor anomalies related to instrument reset events during initial on-orbit operation, the <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> has been operating in a single configuration since its launch in May 2002. There are approximately 40 science products that are being produced using the calibrated data sets from each instrument. In addition, several products are generated using the combined observations from both instruments. This paper provides an overview of Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument status and summarizes those on-orbit operational activities designed and implemented to provide and support instrument calibration and characterization. The assessments of instrument performance are based on the use of on-board calibrators (OBC) and other activities specially developed and implemented by the <span class="hlt">MODIS</span> Characterization Support Team (MCST) at NASA/GSFC. Both instruments are performing well. During four and a half years of Terra <span class="hlt">MODIS</span> on-orbit operation, 11 detectors became noisy and one inoperable out of a total of 490 detectors. Except for band 6 at 1.6m that had many inoperable detectors (identified pre-launch and immediately after launch), there have been no new noisy or inoperable detectors in <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> during its two years of on-orbit operation. The sensors' spectral and spatial performance have also been very stable.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080030347&hterms=scan&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dscan','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080030347&hterms=scan&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dscan"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> Scan Mirror Reflectance Changes On-Orbit</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Wu, A.; Angal, A.</p> <p>2008-01-01</p> <p>Since launch, the NASA EOS Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have operated successfully for more than 8 and 6 years, respectively. <span class="hlt">MODIS</span> collects data using a two-sided scan mirror over a large scan angular range. The scan mirror is made of a polished, nickel-plated beryllium base coated with high purity silver, which is then over-coated with the Denton proprietary silicon monoxide and silicon dioxide mixture. The scan mirror's reflectance was characterized pre-launch using its witness samples, and the response versus scan angle was measured at the sensor system level. In this study, we present an assessment of <span class="hlt">MODIS</span> scan mirror on-orbit degradation by examining changes of spectral band response over each sensor's mission lifetime. Results show that the scan mirror's optical properties for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have experienced significant degradation since launch in the VIS spectral region, which is mirror side dependent as well as scan angle dependent. In general, the mirror degradation is more severe for Terra <span class="hlt">MODIS</span> than <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, especially during recent years. For Terra <span class="hlt">MODIS</span>, the degradation rate is noticeably different between the mirror sides. On the other hand, there has been little mirror side dependent difference for <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017659','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017659"><span id="translatedtitle">Corrections to <span class="hlt">MODIS</span> Terra Calibration and Polarization Trending Derived from Ocean Color Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Eplee, Robert E.; Franz, Bryan A.</p> <p>2014-01-01</p> <p>Remotely sensed ocean color products require highly accurate top-of-atmosphere (TOA) radiances, on the order of 0.5% or better. Due to incidents both prelaunch and on-orbit, meeting this requirement has been a consistent problem for the <span class="hlt">MODIS</span> instrument on the Terra <span class="hlt">satellite</span>, especially in the later part of the mission. The NASA Ocean Biology Processing Group (OBPG) has developed an approach to correct the TOA radiances of <span class="hlt">MODIS</span> Terra using spatially and temporally averaged ocean color products from other ocean color sensors (such as the SeaWiFS instrument on Orbview-2 or the <span class="hlt">MODIS</span> instrument on the <span class="hlt">Aqua</span> <span class="hlt">satellite</span>). The latest results suggest that for <span class="hlt">MODIS</span> Terra, both linear polarization parameters of the Mueller matrix are temporally evolving. A change to the functional form of the scan angle dependence improved the quality of the derived coefficients. Additionally, this paper demonstrates that simultaneously retrieving polarization and gain parameters improves the gain retrieval (versus retrieving the gain parameter only).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020001350&hterms=information+asymmetry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dinformation%2Basymmetry','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020001350&hterms=information+asymmetry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dinformation%2Basymmetry"><span id="translatedtitle">Remote Sensing of Aerosol and their Radiative Properties from the <span class="hlt">MODIS</span> Instrument on EOS-Terra <span class="hlt">Satellite</span>: First Results and Evaluation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Holben, Brent; Lau, William K.-M. (Technical Monitor)</p> <p>2001-01-01</p> <p>The <span class="hlt">MODIS</span> instrument was launched on the NASA Terra <span class="hlt">satellite</span> in Dec. 1999. Since last Oct., the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. <span class="hlt">MODIS</span> has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse aerosol particles. The information is more precise over the ocean where we derive also the effective radius and scattering asymmetry parameter of the aerosol. New methods to derive the aerosol single scattering albedo are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. The AErosol RObotic NETwork of ground based radiometers is used for global validation of the <span class="hlt">satellite</span> derived optical thickness, size parameters and single scattering albedo and measure additional aerosol parameters that cannot be derived from space.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023376','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023376"><span id="translatedtitle"><span class="hlt">MODIS</span> Radiometric Calibration and Uncertainty Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Chiang, Vincent; Sun, Junqiang; Wu, Aisheng</p> <p>2011-01-01</p> <p>Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have collected more than II and 9 years of datasets for comprehensive studies of the Earth's land, ocean, and atmospheric properties. <span class="hlt">MODIS</span> observations are made in 36 spectral bands: 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, <span class="hlt">MODIS</span> was developed with very stringent calibration and uncertainty requirements. As a result, <span class="hlt">MODIS</span> was designed and built with a set of state of the art on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated if necessary. In terms of its calibration traceability, <span class="hlt">MODIS</span> RSB calibration is reflectance based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of <span class="hlt">MODIS</span> calibration methodologies and discusses details of its on-orbit calibration uncertainties. It assesses uncertainty contributions from individual components and differences between Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> due to their design characteristics and on-orbit periormance. Also discussed in this paper is the use of <span class="hlt">MODIS</span> LIB uncertainty index CUI) product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70173626','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70173626"><span id="translatedtitle">High-frequency remote monitoring of large lakes with <span class="hlt">MODIS</span> 500 m imagery</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.</p> <p>2012-01-01</p> <p><span class="hlt">Satellite</span>-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 <span class="hlt">satellites</span>. Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on <span class="hlt">Aqua</span>/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using <span class="hlt">MODIS</span> 500 m data and compared <span class="hlt">MODIS</span> utility to Landsat-based methods. <span class="hlt">MODIS</span> images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and <span class="hlt">satellite</span>-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 <span class="hlt">MODIS</span> data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to 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 <span class="hlt">satellite</span>-based remote monitoring programs relying on spectral data alone.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040075015&hterms=Biomass+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3D%2528Biomass%2Benergy%2529','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040075015&hterms=Biomass+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3D%2528Biomass%2Benergy%2529"><span id="translatedtitle">Use of <span class="hlt">MODIS</span>-Derived Fire Radiative Energy to Estimate Smoke Aerosol Emissions over Different Ecosystems</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Kaufman, Yoram J.</p> <p>2003-01-01</p> <p>Biomass burning is the main source of smoke aerosols and certain trace gases in the atmosphere. However, estimates of the rates of biomass consumption and emission of aerosols and trace gases from fires have not attained adequate reliability thus far. Traditional methods for deriving emission rates employ the use of emission factors e(sub x), (in g of species x per kg of biomass burned), which are difficult to measure from <span class="hlt">satellites</span>. In this era of environmental monitoring from space, fire characterization was not a major consideration in the design of the early <span class="hlt">satellite</span>-borne remote sensing instruments, such as AVHRR. Therefore, although they are able to provide fire location information, they were not adequately sensitive to variations in fire strength or size, because their thermal bands used for fire detection saturated at the lower end of fire radiative temperature range. As such, hitherto, <span class="hlt">satellite</span>-based emission estimates employ proxy techniques using <span class="hlt">satellite</span> derived fire pixel counts (which do not express the fire strength or rate of biomass consumption) or burned areas (which can only be obtained after the fire is over). The <span class="hlt">MODIS</span> sensor, recently launched into orbit aboard EOS Terra (1999) and <span class="hlt">Aqua</span> (2002) <span class="hlt">satellites</span>, have a much higher saturation level and can, not only detect the fire locations 4 times daily, but also measures the at-<span class="hlt">satellite</span> fire radiative energy (which is a measure of the fire strength) based on its 4 micron channel temperature. Also, <span class="hlt">MODIS</span> measures the optical thickness of smoke and other aerosols. Preliminary analysis shows appreciable correlation between the <span class="hlt">MODIS</span>-derived rates of emission of fire radiative energy and smoke over different regions across the globe. These relationships hold great promise for deriving emission coefficients, which can be used for estimating smoke aerosol emissions from <span class="hlt">MODIS</span> active fire products. This procedure has the potential to provide more accurate emission estimates in near real</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060028491','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060028491"><span id="translatedtitle">Overview of CERES Cloud Properties Derived From VIRS AND <span class="hlt">MODIS</span> DATA</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minis, Patrick; Geier, Erika; Wielicki, Bruce A.; Sun-Mack, Sunny; Chen, Yan; Trepte, Qing Z.; Dong, Xiquan; Doelling, David R.; Ayers, J. Kirk; Khaiyer, Mandana M.</p> <p>2006-01-01</p> <p>Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and <span class="hlt">Aqua</span> during late 1999 and early 2002, respectively. When combined, these <span class="hlt">satellites</span> should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and <span class="hlt">Aqua</span> scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span> are analyzed to define the cloud properties for each CERES footprint. To minimize inter-<span class="hlt">satellite</span> differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each <span class="hlt">satellite</span> imager is calibrated in a fashion consistent with its counterpart on the other CERES <span class="hlt">satellites</span> (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/18542490','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/18542490"><span id="translatedtitle">Depolarization ratio and attenuated backscatter for nine cloud types: analyses based on collocated CALIPSO lidar and <span class="hlt">MODIS</span> measurements.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cho, Hyoun-Myoung; Yang, Ping; Kattawar, George W; Nasiri, Shaima L; Hu, Yongxiang; Minnis, Patrick; Trepte, Charles; Winker, David</p> <p>2008-03-17</p> <p>This paper reports on the relationship between lidar backscatter and the corresponding depolarization ratio for nine types of cloud systems. The data used in this study are the lidar returns measured by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud- Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span> Observations (CALIPSO) <span class="hlt">satellite</span> and the collocated cloud products derived from the observations made by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard <span class="hlt">Aqua</span> <span class="hlt">satellite</span>. Specifically, the operational <span class="hlt">MODIS</span> cloud optical thickness and cloud-top pressure products are used to classify cloud types on the basis of the International <span class="hlt">Satellite</span> Cloud Climatology Project (ISCCP) cloud classification scheme. While the CALIPSO observations provide information for up to 10 cloud layers, in the present study only the uppermost clouds are considered. The layer-averaged attenuated backscatter (gamma') and layer-averaged depolarization ratio (delta) from the CALIPSO measurements show both water- and ice-phase features for global cirrus, cirrostratus, and deep convective cloud classes. Furthermore, we screen both the <span class="hlt">MODIS</span> and CALIPSO data to eliminate cases in which CALIPSO detected two- or multi-layered clouds. It is shown that low gamma' values corresponding to uppermost thin clouds are largely eliminated in the CALIPSO delta-gamma' relationship for single-layered clouds. For mid-latitude and polar regions corresponding, respectively, to latitude belts 30 degrees -60 degrees and 60 degrees -90 degrees in both the hemispheres, a mixture of water and ice is also observed in the case of the altostratus class. <span class="hlt">MODIS</span> cloud phase flags are also used to screen ice clouds. The resultant water clouds flagged by the <span class="hlt">MODIS</span> algorithm show only water phase feature in the delta-gamma' relation observed by CALIOP; however, in the case of the ice clouds flagged by the <span class="hlt">MODIS</span> algorithm, the co-existence of ice- and water-phase clouds is still observed in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.B54C..03M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.B54C..03M"><span id="translatedtitle">High-Latitude Vegetation Trends in North America from Integration of <span class="hlt">MODIS</span>, Landsat, and Dynamic Vegetation Models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Masek, J.; Morton, D. C.; Mcmanus, K. M.; Wang, D.; Nagol, J. R.; Poulter, B.; Boudreau, S.; Ropars, P.</p> <p>2011-12-01</p> <p>Dynamic Global Vegetation Models (DGVMs) generally predict poleward migration of temperate and boreal vegetation biomes in response to climate warming. Some models anticipate rapid migration of these biomes during the 21st century, suggesting that local vegetation shifts should already be observable in the <span class="hlt">satellite</span> record. We have examined trends in high-latitude North American vegetation using long-term data records from Landsat and <span class="hlt">MODIS</span> and model results from the Lund-Potsdam-Jena (LPJ) DGVM under a range of climate scenarios. Specifically, we have focused on NDVI trends observed from both Landsat and <span class="hlt">MODIS</span>, as well as spectral changes in the Landsat record that could be related to compositional change. Unlike past studies that relied on integrated measures of growing season NDVI, we focused on "peak summer" trends, which are more closely related to the amount (e.g., leaf area index) and composition of vegetation, rather than variability in vegetation phenology. Analysis of a 25-year Landsat TM/ETM+ record for northern Quebec revealed widespread increases in mid-summer LAI in shrub tundra cover types since the 1980's. These increases are consistent with trends in <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> NDVI for the most recent decade, field observations of increasing shrub cover in the region, and previous studies using AVHRR data (e.g. Pouliot et al., 2009, Int. J. Remote Sens). Continental analysis of <span class="hlt">MODIS</span> data can place these trends in a wider context more suitable for comparisons with DGVM simulations. Across North America, we compared greening and browning trends in mid-summer <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> NDVI to climate data records and LPJ model results. The <span class="hlt">satellite</span> data record indicated a more complex vegetation response to climate warming across North America than model results, with both the magnitude and seasonal timing of warming playing a role. The remote sensing results will be discussed in the context of improving projections of future climate-driven biome shifts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050180543','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050180543"><span id="translatedtitle">Validation of AIRS/AMSU Cloud Retrievals Using <span class="hlt">MODIS</span> Cloud Analyses</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Molnar, Gyula I.; Susskind, Joel</p> <p>2005-01-01</p> <p>The AIRS/AMSU (flying on the EOS-<span class="hlt">AQUA</span> <span class="hlt">satellite</span>) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by <span class="hlt">MODIS/AQUA</span> (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from <span class="hlt">MODIS</span>. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same <span class="hlt">satellite</span> positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B41D0430W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B41D0430W"><span id="translatedtitle">Improvements to the <span class="hlt">MODIS</span> Land Products in Collection Version 6</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wolfe, R. E.; Devadiga, S.; Masuoka, E. J.; Running, S. W.; Vermote, E.; Giglio, L.; Wan, Z.; Riggs, G. A.; Schaaf, C.; Myneni, R. B.; Friedl, M. A.; Wang, Z.; Sulla-menashe, D. J.; Zhao, M.</p> <p>2013-12-01</p> <p>The <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) Adaptive Processing System (MODAPS), housed at the NASA Goddard Space Flight Center (GSFC), has been processing the earth view data acquired by the <span class="hlt">MODIS</span> instrument aboard the Terra (EOS AM) and <span class="hlt">Aqua</span> (EOS PM) <span class="hlt">satellites</span> to generate suite of land and atmosphere data products using the science algorithms developed by the <span class="hlt">MODIS</span> Science Team. These data products are used by diverse set of users in research and other applications from both government and non-government agencies around the world. These validated global products are also being used in interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. Hence an increased emphasis is being placed on generation of high quality consistent data records from the <span class="hlt">MODIS</span> data through reprocessing of the records using improved science algorithms. Since the launch of Terra in December 1999, <span class="hlt">MODIS</span> land data records have been reprocessed four times. The Collection Version 6 (C6) reprocessing of <span class="hlt">MODIS</span> Land and Atmosphere products is scheduled to start in Fall 2013 and is expected to complete in Spring 2014. This presentation will describe changes made to the C6 science algorithms to correct issues in the C5 products, additional improvements made to the products as deemed necessary by the data users and science teams, and new products introduced in this reprocessing. In addition to the improvements from product specific changes to algorithms, the C6 products will also see significant improvement in the calibration by the <span class="hlt">MODIS</span> Calibration Science Team (MCST) of the C6 L1B Top of the Atmosphere (TOA) reflectance and radiance product, more accurate geolocation, and an improved Land Water mask. For the a priori land cover input, this reprocessing will use the multi-year land cover product generated with three years of <span class="hlt">MODIS</span> data as input as opposed to one</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010PhDT.........6S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010PhDT.........6S"><span id="translatedtitle">Tracking daily land surface albedo and reflectance anisotropy with moderate-resolution imaging spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shuai, Yanmin</p> <p></p> <p>A new algorithm provides daily values of land surface albedo and angular reflectance at a 500-m spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments currently in orbit on NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellite</span> platforms. To overcome the day-to-day variance in observed surface reflectance induced by differences in view and solar illumination angles, the algorithm uses the RossThickLiSparse-Reciprocal bidirectional reflectance model, which is fitted to all <span class="hlt">MODIS</span> observations of a 500-m resolution cell acquired during a 16-day moving window. Individual observations are weighted by their quality, observation coverage, and proximity to the production date of interest. Product quality is measured by (1) the root mean square error (RMSE) of observations against the best model fit; and (2) the ability of the angular sampling pattern of the observations at hand to determine reflectance model parameters accurately. A regional analysis of model fits to data from selected <span class="hlt">MODIS</span> data tiles establishes the bounds of these quality measures for application in the daily algorithm. The algorithm, which is now available to users of direct broadcast <span class="hlt">satellite</span> data from <span class="hlt">MODIS</span>, allows daily monitoring of rapid surface radiation and land surface change phenomena such as crop development and forest foliage cycles. In two demonstrations, the daily algorithm captured rapid change in plant phenology. The growth phases of a winter wheat crop, as monitored at the Yucheng agricultural research station in Yucheng, China, matched <span class="hlt">MODIS</span> daily multispectral reflectance data very well, especially during the flowering and heading stages. The daily algorithm also captured the daily change in autumn leaf color in New England, documenting the ability of the algorithm to work well over large regions with varying degrees of cloud cover and atmospheric conditions. Daily surface albedos measured using ground-based instruments on towers at the agricultural and</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B33C0418S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B33C0418S"><span id="translatedtitle">Detection of irrigation timing using <span class="hlt">MODIS</span> and SAR: Effect of land cover heterogeneity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Seungtaek, J.; Keunchang, J.; Lee, H.; Seokyeong, H.; Kang, S.</p> <p>2010-12-01</p> <p>Rice is one of the world’s major staple foods. Paddy rice fields had unique biophysical characteristics that the rice is grown on flooded soils unlike other crops. Distribution and timing of irrigation of paddy rice fields are of importance to determine hydrological balance and efficiency of water resource. In this paper, we detected the distribution and timing of irrigation of paddy rice fields using the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor onboard the NASA EOS <span class="hlt">Aqua</span> <span class="hlt">satellite</span>. Previous researches demonstrated that <span class="hlt">MODIS</span> data can be utilized to detect timing of irrigation by combining vegetation index and Land Surface Water Index (LSWI). Land cover heterogeneity, however, causes considerable uncertainty of the <span class="hlt">satellite</span>-based detections. To evaluate and quantify the effect of land cover heterogeneity, Radarsat-1 Synthetic Aperture Radar (SAR) images were applied together with the <span class="hlt">MODIS</span> images. Sub-pixel heterogeneity of <span class="hlt">MODIS</span> image on land cover and irrigation was evaluated and quantified by using the Radarsat-1 SAR images. The degree of sub-pixel heterogeneity was related with detection of a threshold value of LSWI to determine the timing of irrigation. The threshold value with the degree of heterogeneity increased (R2=0.95), which was applied to detect the timing of irrigation over complex land cover areas. Reliable detecting of timing of irrigation could enhance reliability of <span class="hlt">MODIS</span>-based estimation on evapotranspiration from paddy rice fields. In this presentation, we will demonstrate the enhancement of <span class="hlt">MODIS</span>-based evapotranspiration by using our new algorithm on detection of timing of irrigation. Acknowledgement: This study was supported by National Academy of Agricultural Science, RDA, Republic of Korea.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRC..119.8646L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRC..119.8646L"><span id="translatedtitle">River runoff effect on the suspended sediment property in the upper Chesapeake Bay using <span class="hlt">MODIS</span> observations and ROMS simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Xiaoming; Wang, Menghua</p> <p>2014-12-01</p> <p>Ocean color data derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the <span class="hlt">satellite</span> <span class="hlt">Aqua</span> from 2002 to 2012 and simulations from the Regional Ocean Modeling System (ROMS) are used to study the impact of the Susquehanna River discharge on the total suspended sediment (TSS) concentration in the upper Chesapeake Bay. Since the water in the upper Chesapeake Bay is highly turbid, the shortwave infrared (SWIR)-based atmospheric correction algorithm is used for deriving the normalized water-leaving radiance nLw(λ) spectra from <span class="hlt">MODIS-Aqua</span> measurements. nLw(λ) spectra are further processed into the diffuse attenuation coefficient at the wavelength of 490 nm Kd(490) and TSS. <span class="hlt">MODIS-Aqua</span>-derived monthly TSS concentration in the upper Chesapeake Bay and in situ Susquehanna River discharge data show similar patterns in seasonal variations. The TSS monthly temporal variation in the upper Chesapeake Bay is also found in phase with the monthly averaged river discharge data. Since the Susquehanna River discharge is mainly dominated by a few high discharge events due to winter-spring freshets or tropical storms in each year, the impact of these high discharge events on the upper Chesapeake Bay TSS is investigated. Both <span class="hlt">MODIS</span>-measured daily TSS images and sediment data derived from ROMS simulations show that the Susquehanna River discharge is the dominant factor for the variations of TSS concentration in the upper Chesapeake Bay. Although the high river discharge event usually lasts for only a few days, its induced high TSS concentration in the upper Chesapeake Bay can sustain for ˜10-20 days. The elongated TSS rebounding stage is attributed to horizontal advection of slowly settling fine sediment from the Susquehanna River.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015362','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015362"><span id="translatedtitle">Estimating Contrail Climate Effects from <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minnis, Patrick; Duda, David P.; Palikonda, Rabindra; Bedka, Sarah T.; Boeke, Robyn; Khlopenkov, Konstantin; Chee, Thad; Bedka, Kristopher T.</p> <p>2011-01-01</p> <p>An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>. The CDA is refined and balanced using visual error analysis. It is applied to <span class="hlt">MODIS</span> data taken by Terra and <span class="hlt">Aqua</span> over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to <span class="hlt">MODIS</span> data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C51A0477M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C51A0477M"><span id="translatedtitle"><span class="hlt">MODIS</span> Data and Services at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McAllister, M.; Fowler, D. K.</p> <p>2010-12-01</p> <p>For nearly a decade, the National Snow and Ice Data Center (NSIDC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span>. The archive contains a wide selection of data products relevant to cryospheric science, including snow and sea ice. NSIDC offers a variety of methods for obtaining these data. Our Data Pool is an online archive which allows a user to very quickly download desired products and also has a spatial and temporal search capability. The Warehouse Inventory Search Tool (WIST) contains a complete set of metadata for all products which can be searched for and ordered. WIST also allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new <span class="hlt">MODIS</span> data automatically ftp’d or staged on a local server as it is archived at NSIDC. Since <span class="hlt">MODIS</span> products are in HDF-EOS format, NSIDC has developed a number of tools to assist with browsing, editing, reprojection, resampling, and format conversion including <span class="hlt">MODIS</span> Swath-to-Grid Toolbox (MS2GT) and the <span class="hlt">MODIS</span> Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute <span class="hlt">MODIS</span> scenes. NSIDC created the MIST to also provide subsets of certain Version 5 <span class="hlt">MODIS</span> products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F"><span id="translatedtitle"><span class="hlt">MODIS</span> Collection 6 Data at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.</p> <p>2015-12-01</p> <p>For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span>. Collection 6 represents the next revision to NSIDC's <span class="hlt">MODIS</span> archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the <span class="hlt">MODIS</span> science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though <span class="hlt">MODIS</span> snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new <span class="hlt">MODIS</span> snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The <span class="hlt">MODIS</span> Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The <span class="hlt">MODIS</span> sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011lrsg.book..635Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011lrsg.book..635Z"><span id="translatedtitle"><span class="hlt">MODIS</span>-Derived Terrestrial Primary Production</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Maosheng; Running, Steven; Heinsch, Faith Ann; Nemani, Ramakrishna</p> <p></p> <p>Temporal and spatial changes in terrestrial biological productivity have a large impact on humankind because terrestrial ecosystems not only create environments suitable for human habitation, but also provide materials essential for survival, such as food, fiber and fuel. A recent study estimated that consumption of terrestrial net primary production (NPP; a list of all the acronyms is available in the appendix at the end of the chapter) by the human population accounts for about 14-26% of global NPP (Imhoff et al. 2004). Rapid global climate change is induced by increased atmospheric greenhouse gas concentration, especially CO2, which results from human activities such as fossil fuel combustion and deforestation. This directly impacts terrestrial NPP, which continues to change in both space and time (Melillo et al. 1993; Prentice et al. 2001; Nemani et al. 2003), and ultimately impacts the well-being of human society (Milesi et al. 2005). Additionally, substantial evidence show that the oceans and the biosphere, especially terrestrial ecosystems, currently play a major role in reducing the rate of the atmospheric CO2 increase (Prentice et al. 2001; Schimel et al. 2001). NPP is the first step needed to quantify the amount of atmospheric carbon fixed by plants and accumulated as biomass. Continuous and accurate measurements of terrestrial NPP at the global scale are possible using <span class="hlt">satellite</span> data. Since early 2000, for the first time, the <span class="hlt">MODIS</span> sensors onboard the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, have operationally provided scientists with near real-time global terrestrial gross primary production (GPP) and net photosynthesis (PsnNet) data. These data are provided at 1 km spatial resolution and an 8-day interval, and annual NPP covers 109,782,756 km2 of vegetated land. These GPP, PsnNet and NPP products are collectively known as MOD17 and are part of a larger suite of <span class="hlt">MODIS</span> land products (Justice et al. 2002), one of the core Earth System or Climate Data Records (ESDR or</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT........27Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT........27Y"><span id="translatedtitle">Analysis, improvement and application of the <span class="hlt">MODIS</span> leaf area index products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Wenze</p> <p></p> <p>Green leaf area governs the exchanges of energy, mass and momentum between the Earth's surface and the atmosphere. Therefore, leaf area index (LAI) and fraction of incident photosynthetically active radiation (0.4-0.7 mum) absorbed by the vegetation canopy (FPAR) are widely used in vegetation monitoring and modeling. The launch of Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> with the moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) instrument onboard provided the first global products of LAI and FPAR, derived mainly from an algorithm based on radiative transfer. The objective of this research is to comprehensively evaluate the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> LAI/FPAR products. Large volumes of these products have been analyzed with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus back-up), snow (snow-free versus snow on the ground) and cloud (cloud-free versus cloudy) conditions. Field validation efforts identified several key factors that influence the accuracy of algorithm retrievals. The strategy of validation efforts guiding algorithm refinements has led to progressively more accurate LAI/FPAR products. The combination of products derived from the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> sensors increases the success rate of the main radiative transfer algorithm by 10-20 percent over woody vegetation. The Terra Collection 4 LAI data reveal seasonal swings in green leaf area of about 25 percent in a majority of the Amazon rainforests caused by variability in cloud cover and light. The timing and the influence of this seasonal cycle are critical to understanding tropical plant adaptation patterns and ecological processes. The results presented in this dissertation suggest how the product quality has gradually improved largely through the efforts of validation activities. The Amazon case study highlights the utility of these data sets for monitoring global vegetation dynamics. Thus, these results can be seen as a benchmark for evaluation of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/24258878','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/24258878"><span id="translatedtitle">Systematic errors in temperature estimates from <span class="hlt">MODIS</span> data covering the western Palearctic and their impact on a parasite development model.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Alonso-Carné, Jorge; García-Martín, Alberto; Estrada-Peña, Agustin</p> <p>2013-11-01</p> <p>The modelling of habitat suitability for parasites is a growing area of research due to its association with climate change and ensuing shifts in the distribution of infectious diseases. Such models depend on remote sensing data and require accurate, high-resolution temperature measurements. The temperature is critical for accurate estimation of development rates and potential habitat ranges for a given parasite. The <span class="hlt">MODIS</span> sensors aboard the <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span> provide high-resolution temperature data for remote sensing applications. This paper describes comparative analysis of <span class="hlt">MODIS</span>-derived temperatures relative to ground records of surface temperature in the western Palaearctic. The results show that <span class="hlt">MODIS</span> overestimated maximum temperature values and underestimated minimum temperatures by up to 5-6 °C. The combined use of both <span class="hlt">Aqua</span> and Terra datasets provided the most accurate temperature estimates around latitude 35-44° N, with an overestimation during spring-summer months and an underestimation in autumn-winter. Errors in temperature estimation were associated with specific ecological regions within the target area as well as technical limitations in the temporal and orbital coverage of the <span class="hlt">satellites</span> (e.g. sensor limitations and <span class="hlt">satellite</span> transit times). We estimated error propagation of temperature uncertainties in parasite habitat suitability models by comparing outcomes of published models. Error estimates reached 36% of annual respective measurements depending on the model used. Our analysis demonstrates the importance of adequate image processing and points out the limitations of <span class="hlt">MODIS</span> temperature data as inputs into predictive models concerning parasite lifecycles. PMID:24258878</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1712414Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1712414Z"><span id="translatedtitle">Analysis of drought events in a Mediterranean semi-arid region, Using SPOT-VGT and TERRA-<span class="hlt">MODIS</span> <span class="hlt">satellite</span> products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zribi, Mehrez; Dridi, Ghofrane; Amri, Rim; Lili-Chabaane, Zohra</p> <p>2015-04-01</p> <p>In semi-arid regions, and northern Africa in particular, the scarcity of rainfall and the occurrence of long periods of drought, represent one of the main environmental factors having a negative effect on agricultural productivity. This is the case in Central Tunisia, where the monitoring of agricultural and water resources is of prime importance. Vegetation cover is a key parameter to analyse this problem. Remote sensing has shown in the last decades a high potential to estimate these surface parameters. This study is based on two <span class="hlt">satellite</span> products: SPOT-VGT (1998-2012) and TERRA-<span class="hlt">MODIS</span> (2001-2012) NDVI products. They are used to study the dynamics of vegetation and land use. Different behaviors linked to drought periods have been observed. A strong agreement is observed between products proposed by the two sensors. Low spatial resolution SPOT-VGT and TERRA-<span class="hlt">MODIS</span> NDVI images were used to map the land into three characteristic classes: olive trees, annual agriculture and pastures. An analysis of vegetation behaviour for dry years is proposed using the Windowed Fourier Transform (WTF). The Fourier Transform is able to analyze the frequency content of a signal in the time domain by decomposing the signal as the superposition of sine and cosine basis functions. Analysis for annual agricultural areas demonstrates a combined effect between climate and farmers behaviours. In these areas, bare soils show a high increasing for drought years. Highest percent of bare soil is retrieved with TERRA-<span class="hlt">MODIS</span> than with SPOT-VGT. This could be explained by the spatial resolution of the two sensors. The temporal series of optical images are finally used to calculate a drought index, namely the VAI (Vegetation Anomaly Index), on the plain of Kairouan (Amri et al., 2011). This index shows a high correlation with precipitation statistics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120001461','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120001461"><span id="translatedtitle">Use of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Images and an Atmospheric Dust Transport Model To Evaluate Juniperus spp. Pollen Phenology and Dispersal</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Luvall, J. C.; Sprigg, W. A.; Levetin, Estelle; Huete, Alfredo; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.; Zelicoff, A. P.; Bunderson, L.; Crimmins, T. M.</p> <p>2011-01-01</p> <p>Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using <span class="hlt">MODIS</span> data products to identify source regions and quantities of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen release will be estimated based on <span class="hlt">MODIS</span> derived phenology of Juniperus spp. communities. Ground based observational records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110010232','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110010232"><span id="translatedtitle">Use of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Luvall, Jeffrey C.</p> <p>2011-01-01</p> <p>Pollen can be transported great distances. Van de Water et. al. reported Juniperus spp. pollen was transported 200-600 km. Hence local obse rvations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using <span class="hlt">MODIS</span> data produ cts to identify source regions and quantities of dust. We are modifyi ng the DREAM model to incorporate pollen transport. Pollen release wi ll be estimated based on <span class="hlt">MODIS</span> derived phenology of Juniperus spp. communities. Ground based observations records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention?s Nat ional Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110014813','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110014813"><span id="translatedtitle">Use of <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.; Zelicoff, A. P.; Bunderson, L.; Crimmins, T. M.</p> <p>2011-01-01</p> <p>Pollen can be transported great distances. Van de Water et. al. reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using <span class="hlt">MODIS</span> data products to identify source regions and quantities of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen release will be estimated based on <span class="hlt">MODIS</span> derived phenology of Juniperus spp. communities. Ground based observational records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013289','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013289"><span id="translatedtitle">An Examination of the Nature of Global <span class="hlt">MODIS</span> Cloud Regimes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.</p> <p>2014-01-01</p> <p>We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument aboard the <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span>. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from <span class="hlt">satellites</span> and other sources, we examine regime structural and thermodynamical characteristics. We establish that the <span class="hlt">MODIS</span> cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007875','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007875"><span id="translatedtitle">Validation of the <span class="hlt">MODIS</span> "Clear-Sky" Surface Temperature of the Greenland Ice Sheet</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Koenig, L. S.; DiGirolamo, N. E.; Comiso, J.; Shuman, C. A.</p> <p>2011-01-01</p> <p>Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of <span class="hlt">satellite</span> sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>. We use the <span class="hlt">MODIS</span> ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and <span class="hlt">Aqua</span> IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other <span class="hlt">satellite</span> 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 <span class="hlt">satellite</span> sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JPRS...87..137C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JPRS...87..137C"><span id="translatedtitle">Assessment of <span class="hlt">satellite</span> ocean color products of MERIS, <span class="hlt">MODIS</span> and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cui, Tingwei; Zhang, Jie; Tang, Junwu; Sathyendranath, Shubha; Groom, Steve; Ma, Yi; Zhao, Wei; Song, Qingjun</p> <p>2014-01-01</p> <p>The validation of <span class="hlt">satellite</span> ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color <span class="hlt">satellites</span>, namely the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that <span class="hlt">satellite</span> retrievals of the spectral remote sensing reflectance Rrs(λ) at the blue-green and green bands from MERIS, <span class="hlt">MODIS</span> and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APDm) of 15-27% and root-mean-square-error (RMS) of 0.0021-0.0039 sr-1, whereas the Rrs(λ) uncertainty at 412 nm is the highest (APDm 47-62%, RMS 0.0027-0.0041 sr-1). The uncertainties of the aerosol optical thickness (AOT) τa, diffuse attenuation coefficient for downward irradiance at 490 nm Kd(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational <span class="hlt">satellite</span> data processing chain, the uncertainties of <span class="hlt">satellite</span>-derived properties of Kd(490), SPM, and Chl-a may decrease significantly to the level of 20-30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160011149','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160011149"><span id="translatedtitle">The Calibration of the DSCOVR EPIC Multiple Visible Channel Instrument Using <span class="hlt">MODIS</span> and VIIRS as a Reference</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Haney, Conor; Doeling, David; Minnis, Patrick; Bhatt, Rajendra; Scarino, Benjamin; Gopalan, Arun</p> <p>2016-01-01</p> <p>The Deep Space Climate Observatory (DSCOVR), launched on 11 February 2015, is a <span class="hlt">satellite</span> positioned near the Lagrange-1 (L1) point, carrying several instruments that monitor space weather, and Earth-view sensors designed for climate studies. The Earth Polychromatic Imaging Camera (EPIC) onboard DSCOVR continuously views the sun-illuminated portion of the Earth with spectral coverage in the UV, VIS, and NIR bands. Although the EPIC instrument does not have any onboard calibration abilities, its constant view of the sunlit Earth disk provides a unique opportunity for simultaneous viewing with several other <span class="hlt">satellite</span> instruments. This arrangement allows the EPIC sensor to be inter-calibrated using other well-characterized <span class="hlt">satellite</span> instrument reference standards. Two such instruments with onboard calibration are <span class="hlt">MODIS</span>, flown on <span class="hlt">Aqua</span> and Terra, and VIIRS, onboard Suomi-NPP. The <span class="hlt">MODIS</span> and VIIRS reference calibrations will be transferred to the EPIC instrument using both all-sky ocean and deep convective clouds (DCC) ray-matched EPIC and <span class="hlt">MODIS</span>/VIIRS radiance pairs. An automated navigation correction routine was developed to more accurately align the EPIC and <span class="hlt">MODIS</span>/VIIRS granules. The automated navigation correction routine dramatically reduced the uncertainty of the resulting calibration gain based on the EPIC and <span class="hlt">MODIS</span>/VIIRS radiance pairs. The SCIAMACHY-based spectral band adjustment factors (SBAF) applied to the <span class="hlt">MODIS</span>/ VIIRS radiances were found to successfully adjust the reference radiances to the spectral response of the specific EPIC channel for over-lapping spectral channels. The SBAF was also found to be effective for the non-overlapping EPIC channel 10. Lastly, both ray-matching techniques found no discernable trends for EPIC channel 7 over the year of publically released EPIC data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150019885','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150019885"><span id="translatedtitle"><span class="hlt">MODIS</span> Instrument Operation and Calibration Improvements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Angal, A.; Madhavan, S.; Link, D.; Geng, X.; Wenny, B.; Wu, A.; Chen, H.; Salomonson, V.</p> <p>2014-01-01</p> <p>Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for over 14 and 12 years since their respective launches in 1999 and 2002. The <span class="hlt">MODIS</span> on-orbit calibration is performed using a set of on-board calibrators, which include a solar diffuser for calibrating the reflective solar bands (RSB) and a blackbody for the thermal emissive bands (TEB). On-orbit changes in the sensor responses as well as key performance parameters are monitored using the measurements of these on-board calibrators. This paper provides an overview of <span class="hlt">MODIS</span> on-orbit operation and calibration activities, and instrument long-term performance. It presents a brief summary of the calibration enhancements made in the latest <span class="hlt">MODIS</span> data collection 6 (C6). Future improvements in the <span class="hlt">MODIS</span> calibration and their potential applications to the S-NPP VIIRS are also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812037K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812037K"><span id="translatedtitle">Assessing differences in phenology patterns between burned and non burned areas using <span class="hlt">MODIS</span> and Landsat time series <span class="hlt">satellite</span> images. A case study in Peloponnisos (Greece) and Sardinia (Italy)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Koutsias, Nikos; Bajocco, Sofia</p> <p>2016-04-01</p> <p>Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when <span class="hlt">satellite</span> remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series <span class="hlt">satellite</span> images can be used to characterize vegetation phenology and thus can be helpful for assessing, for example, phenology patterns between burned and non-burned areas. The aim of this study is to define phenological patterns for the fire ignition points in two Mediterranean study areas located in Italy (Sardinia) and Greece (Peloponnisos) and compare them with control points created after random sampling techniques restricted to certain buffer zones. Remotely sensed data from <span class="hlt">MODIS</span> (2000-2015) and LANDSAT (1984-2015) <span class="hlt">satellites</span> were acquired and processed to extract the temporal profiles of the spectral signal of fire ignition points and of control points. Apart of the use of the original spectral data, we used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. Different metrics linked to key phenological events have been derived and used to assess vegetation phenology in the fire-affected areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUSM.H41A..01N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUSM.H41A..01N"><span id="translatedtitle"><span class="hlt">Satellite</span> Remote Sensing of Pan-arctic Vegetation Productivity, Soil Respiration and net CO2 Exchange Using <span class="hlt">MODIS</span> and AMSR-E Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nirala, M. L.; Heinsch, F. A.; Kimball, J. S.; Zhao, M.; Running, S.; Oechel, W.; McDonald, K.; Njoku, E.</p> <p>2005-05-01</p> <p>We have developed an approach for regional assessment and monitoring of land-atmosphere carbon dioxide (CO2) exchange, soil heterotrophic respiration (Rh) and vegetation productivity for arctic tundra using global <span class="hlt">satellite</span> remote sensing at optical and microwave wavelengths. We use C- and X-band brightness temperatures from AMSR-E to extract surface wetness and temperature, and <span class="hlt">MODIS</span> data to derive land cover, Leaf Area Index (LAI) and Net Primary Production (NPP) information. Calibration and validation activities involve comparisons between <span class="hlt">satellite</span> remote sensing and tundra CO2 eddy flux tower and biophysical measurement networks and hydro-ecological process model simulations. We analyze spatial and temporal anomalies and environmental drivers of land-atmosphere net CO2 exchange at weekly and annual time steps. Surface soil moisture status and temperature as detected from <span class="hlt">satellite</span> remote sensing observations are found to be major drivers spatial and temporal patterns of tundra net CO2 exchange and photosynthetic and respiration processes. We also find that <span class="hlt">satellite</span> microwave measurements are capable of capturing seasonal variations and regional patterns in tundra soil heterotrophic respiration and CO2 exchange, while our ability to extract spatial patterns at the scale of surface heterogeneity is limited by the coarse spatial scale of the <span class="hlt">satellite</span> remote sensing footprint. Our results also indicate that carbon cycle response to climate change is non-linear and strongly coupled to arctic surface hydrology. This work was performed at The University of Montana and Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFMGC32B..07K&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFMGC32B..07K&link_type=ABSTRACT"><span id="translatedtitle">Fuel for the Fire: Improved Understanding of Fire Behavior in Africa Based on Partitioned Herbaceous and Woody LAI from <span class="hlt">MODIS</span> <span class="hlt">Satellite</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kahiu, M. N.; Hanan, N. P.</p> <p>2014-12-01</p> <p>Fire is an important recurrent phenomenon that determines the distribution of global savanna biomes and tree cover in savanna ecosystems. Tropical savanna fires are almost exclusively ground fires, fueled by senescent herbaceous material, with crown fires being rare. Analyses of <span class="hlt">satellite</span>-based fire activity and burned area (active fires and burn-scars) in tropical savannas reveal a close correlation with <span class="hlt">satellite</span>-based estimates of total net primary productivity (NPP) in drier savannas, and apparent limitation by rainfall (fuel moisture) in wetter systems. However, these analyses of fire frequency and extent at continental scales ignore the different roles played by the herbaceous and woody vegetation components in promoting and/or suppressing fire ignition and spread. In this research we hypothesized that, since herbaceous vegetation provides the primary fuel, fire frequency and burn areas in African savannas and seasonal woodlands should correlate more closely with measurements of herbaceous NPP or end of season leaf area index (LAI), than with the NPP or LAI of the tree layer. Similarly, while fire patterns may correlate with patterns of total LAI and total NPP across Africa, the relationship will be confounded by variations in tree cover. Our objective is to understand how fire frequency and intensity vary with changes in herbaceous cover. To test our hypotheses we will use estimates of herbaceous and woody LAI that we have developed recently by partitioning <span class="hlt">MODIS</span> LAI. We will explore how seasonal maximum herbaceous LAI and leaf area duration (LAD) (both potential proxies for accumulated fuel load) correlate with fire frequency in African savannas. We will demonstrate the <span class="hlt">MODIS</span> LAI partitioning methodology, and present results on the divergent relationships between African savanna fires and total LAI, herbaceous LAI and herbaceous LAD.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9640E..19Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9640E..19Z"><span id="translatedtitle">Time-series <span class="hlt">MODIS</span> <span class="hlt">satellite</span> and in-situ data for spatio-temporal distribution of aerosol pollution assessment over Bucharest metropolitan area</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.</p> <p>2015-10-01</p> <p>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 (<span class="hlt">MODIS</span>) there is detailed global aerosol information available, both over land and oceans The aerosol parameters can be measured directly in situ or derived from <span class="hlt">satellite</span> 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 <span class="hlt">MODIS</span> (Terra-Moderate Resolution Imaging Spectoradiometer) <span class="hlt">satellite</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H51E1238P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H51E1238P"><span id="translatedtitle">Evaluation of hydrological balance in the eastern Amazon using a terrestrial ecosystem model, and <span class="hlt">satellite</span>-based evapotranspiration (<span class="hlt">MODIS</span>) and terrestrial water storage (GRACE)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Panday, P. K.; Coe, M. T.; Macedo, M.; Beck, P.</p> <p>2013-12-01</p> <p>High historical deforestation rates and a rapidly changing agricultural landscape may dramatically alter the energy and water balance of the eastern Amazon basin. Understanding the surface water dynamics and hydrological balance of the region is critical for accurately assessing the historical and potential future impacts of deforestation, land-use change, and land management practices. We examine the water balance of the Xingu river basin by combining the IBIS (Integrated Biosphere Simulator) terrestrial ecosystem model with <span class="hlt">satellite</span>-based models of evapotranspiration (MOD16) and terrestrial water storage (GRACE). IBIS simulations were forced with prescribed climate to produce modeled evapotranspiration and runoff, which were then compared with <span class="hlt">MODIS</span> evapotranspiration and observed discharge at Altamira (PA, Brazil). Results from both <span class="hlt">satellite</span> observations and model simulations support earlier studies demonstrating that dry-season evapotranspiration is higher than wet-season evapotranspiration in the wetter forests of the northern Xingu basin, while the contrary is true in the seasonally dry forests of the southern Xingu. Seasonal variation in modeled soil water storage agrees with the GRACE measurements in both timing and magnitude. Soil moisture anomalies averaged over the Xingu basin suggest that annual changes in soil water storage account for a large part of the interannual variation in observed discharge. Field measurements of discharge and soil moisture in the southern Xingu also support the findings that changes in soil water storage drive inter-annual variations in river discharge. Figure 1. Comparison of observed discharge at Altamira (Pará, Brazil) against <span class="hlt">MODIS</span>- derived P-E (PCRU-MODISET), IBIS simulated discharge, IBIS (PCRU-ETIBIS), and IBIS (PCRU-ETIBIS- Δ Soil moisture IBIS). The bottom panel shows annual basin precipitation from Climatic Research Unit (CRU) climatological data for the 2000-2008 period</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMIN21A1682M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMIN21A1682M"><span id="translatedtitle">Quality Assessment of Collection 6 <span class="hlt">MODIS</span> Atmospheric Science Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.</p> <p>2015-12-01</p> <p>Since the launch of the NASA Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> in December 1999 and May 2002, respectively, atmosphere and land data acquired by the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) sensor on-board these <span class="hlt">satellites</span> have been reprocessed five times at the MODAPS (<span class="hlt">MODIS</span> Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA <span class="hlt">MODIS</span> science team investigators. MODAPS completed Collection 6 reprocessing of <span class="hlt">MODIS</span> Atmosphere science data products in April 2015 and is currently generating the Collection 6 products using the latest version of the science algorithms. This reprocessing has generated one of the longest time series of consistent data records for understanding cloud, aerosol, and other constituents in the earth's atmosphere. It is important to carefully evaluate and assess the quality of this data and remove any artifacts to maintain a useful climate data record. Quality Assessment (QA) is an integral part of the processing chain at MODAPS. This presentation will describe the QA approaches and tools adopted by the <span class="hlt">MODIS</span> Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of <span class="hlt">MODIS</span> operational Atmospheric products produced at MODAPS. Some of the tools include global high resolution images, time series analysis and statistical QA metrics. The new high resolution global browse images with pan and zoom have provided the ability to perform QA of products in real time through synoptic QA on the web. This global browse generation has been useful in identifying production error, data loss, and data quality issues from calibration error, geolocation error and algorithm performance. A time series analysis for various science datasets in the Level-3 monthly product was recently developed for assessing any long term drifts in the data arising from instrument errors or other artifacts. This presentation will describe and discuss some test cases from the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015305','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015305"><span id="translatedtitle">Adjustments to the <span class="hlt">MODIS</span> Terra Radiometric Calibration and Polarization Sensitivity in the 2010 Reprocessing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Franz, Bryan A.</p> <p>2011-01-01</p> <p>The Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on NASA s Earth Observing System (EOS) <span class="hlt">satellite</span> Terra provides global coverage of top-of-atmosphere (TOA) radiances that have been successfully used for terrestrial and atmospheric research. The <span class="hlt">MODIS</span> Terra ocean color products, however, have been compromised by an inadequate radiometric calibration at the short wavelengths. The Ocean Biology Processing Group (OBPG) at NASA has derived radiometric corrections using ocean color products from the SeaWiFS sensor as truth fields. In the R2010.0 reprocessing, these corrections have been applied to the whole mission life span of 10 years. This paper presents the corrections to the radiometric gains and to the instrument polarization sensitivity, demonstrates the improvement to the Terra ocean color products, and discusses issues that need further investigation. Although the global averages of <span class="hlt">MODIS</span> Terra ocean color products are now in excellent agreement with those of SeaWiFS and <span class="hlt">MODIS</span> <span class="hlt">Aqua</span>, and image quality has been significantly improved, the large corrections applied to the radiometric calibration and polarization sensitivity require additional caution when using the data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060047447','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060047447"><span id="translatedtitle">Status of the <span class="hlt">MODIS</span> Level 1B Algorithms and Calibration Tables</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X; Salomonson, V V; Kuyper, J; Tan, L; Chiang, K; Sun, J; Barnes, W L</p> <p>2005-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, launched in December 1999 and May 2002, respectively. The <span class="hlt">MODIS</span> Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) reflectance factors for the sensor's reflective solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the <span class="hlt">MODIS</span> L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the <span class="hlt">MODIS</span> collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JQSRT.153...65Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JQSRT.153...65Y"><span id="translatedtitle">Comparison of CERES-<span class="hlt">MODIS</span> cloud microphysical properties with surface observations over Loess Plateau</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yan, Hongru; Huang, Jianping; Minnis, Patrick; Yi, Yuhong; Sun-Mack, Sunny; Wang, Tianhe; Nakajima, Takashi Y.</p> <p>2015-03-01</p> <p>To enhance the utility of <span class="hlt">satellite</span>-derived cloud properties for studying the role of clouds in climate change and the hydrological cycle in semi-arid areas, it is necessary to know their uncertainties. This paper estimates the uncertainties of several cloud properties by comparing those derived over the China Loess Plateau from the MODerate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span> by the Clouds and Earth's Radiant Energy System (CERES) with surface observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). The comparisons use data from January 2008 to June 2010 limited to single layer and overcast stratus conditions during daytime. Cloud optical depths (τ) and liquid water paths (LWP) from both Terra and <span class="hlt">Aqua</span> generally track the variation of the surface counterparts with modest correlation, while cloud effective radius (re) is only weakly correlated with the surface retrievals. The mean differences between Terra and the SACOL retrievals are -4.7±12.9, 2.1±3.2 μm and 30.2±85.3 g m-2 for τ, re and LWP, respectively. The corresponding differences for <span class="hlt">Aqua</span> are 2.1±8.4, 1.2±2.9 μm and 47.4±79.6 g m-2, respectively. Possible causes for biases of <span class="hlt">satellite</span> retrievals are discussed through statistical analysis and case studies. Generally, the CERES-<span class="hlt">MODIS</span> cloud properties have a bit larger biases over the Loess Plateau than those in previous studies over other locations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160007849&hterms=clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclouds','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160007849&hterms=clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclouds"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> RSB Detector Uniformity Using Deep Convective Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen</p> <p>2016-01-01</p> <p>For <span class="hlt">satellite</span> 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 (<span class="hlt">MODIS</span>). Each detector of <span class="hlt">MODIS</span> RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra <span class="hlt">MODIS</span> Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most <span class="hlt">Aqua</span> bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for <span class="hlt">MODIS</span> band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to reflectance images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.4783C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.4783C"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> RSB detector uniformity using deep convective clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen</p> <p>2016-05-01</p> <p>For <span class="hlt">satellite</span> 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 (<span class="hlt">MODIS</span>). Each detector of <span class="hlt">MODIS</span> RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra <span class="hlt">MODIS</span> Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most <span class="hlt">Aqua</span> bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for <span class="hlt">MODIS</span> band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to reflectance images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040013413&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040013413&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille"><span id="translatedtitle">Dust Transport, Deposition and Radiative Effects Observed from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Y. J.; Koren, I.; Remer, L. A.; Tanre, D.; Ginoux, P.; Fan, S.</p> <p>2003-01-01</p> <p>Carlson (1977) used <span class="hlt">satellite</span> (AVHRR) observation of dust episodes 3 estimate that 90 tg of dust are emitted from Africa (0-30 N) to the Atlantic Ocean between June and August. <span class="hlt">MODIS</span> systematic measurements of aerosol optical thickness (AOT) and the fraction of the AOT (f) due to the fine mode (see Remer et al abstract), are used to derive the column concentration, flux and deposition of African dust over the Atlantic Ocean. The main data set is for 2001 but the results are consistent with <span class="hlt">MODIS</span> measurements from 2002. The analysis first determines the properties of maritime baseline aerosol (AOT=0.06, f=0.5); followed by linear scaling of the dust AOT and the anthropogenic AOT, based on <span class="hlt">MODIS</span> measured values of the fraction "f" being 0.9 for anthropogenic aerosol and 0.5 for dust. NCEP winds are used in the analysis and are evaluated against observed dust movements between the Terra and <span class="hlt">Aqua</span> passes (see Koren et al. abstract). Monthly values of dust transport and deposition are calculated. Preliminary results show that 280 tg of dust are emitted annually from Africa to the Atlantic Ocean between 20s and 30N, with 40 tg returning to Africa and Europe between 30N and 50N. 85 tg reach the Americas, with 130-150 tg are deposited in the Atlantic Ocean. The results are compared with dust transport models that indicate 110-230 tg of dust being deposited in the Ocean. It is interesting to note that the early estimates of Carlson (1977) and Carlson & Prosper0 (1972) are very close to our estimate from <span class="hlt">MODIS</span> of 100 tg for the same latitude range and monthly period.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMNH51E1944S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMNH51E1944S"><span id="translatedtitle">Characterizing 13 Years of Surface Water Variability from <span class="hlt">MODIS</span>-based Near Real-Time Flood Mapping Products in the Indus River, Tonle Sap Lake, and Lake Chad.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Slayback, D. A.; Brakenridge, G. R.; Policelli, F. S.</p> <p>2015-12-01</p> <p>Driven by an increase in extreme weather events in a warming world, flooding appears to be increasing in many regions. Since 2012, we have been using the twice-daily near-global observations of the two <span class="hlt">MODIS</span> instruments to operate a near real-time flood mapping capability. Primarily intended to support disaster response efforts, our system generates daily near-global maps of flood water extent, at 250 m resolution. Although cloud cover is a challenge, the twice-daily coverage from the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> helps to capture most major events. We use the MOD44W product (the "<span class="hlt">MODIS</span> 250-m land-water mask") to differentiate "normal" water from flood water. Products from the system are freely available, and used by disaster response agencies and academic and industry researchers. An open question, however, is: how "normal" are recently observed floods? Destructive and — as reported by the press — record floods seem to be occurring more and more frequently. With the <span class="hlt">MODIS</span> archive going back to 1999 (Terra <span class="hlt">satellite</span>) and 2002 (<span class="hlt">Aqua</span> <span class="hlt">satellite</span>), we now have more than a decade of twice-daily near-global observations to begin answering this question. Although the 13 years of available twice-daily data (2002-2015) are not sufficient to fully characterize surface water normals (e.g., 100-year floods), we can start examining recent trends in surface water extent and flood frequency. To do so, we have back-processed our surface water product through mid-2002 (<span class="hlt">Aqua</span> launch) for a few regions, and have used this to evaluate the variability in surface water extent and flood frequency. These results will eventually feed back into an improved characterization of flood water in our near real-time flood product. Here we will present results on trends in surface water extent and flood frequency for a few regions, including the Indus in Pakistan, the Tonle Sap lake in Cambodia, and lake Chad in Africa.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PCE....83...14Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PCE....83...14Y"><span id="translatedtitle">Integrating TRMM and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> with socio-economic vulnerability for monitoring drought risk over a tropical region of India</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yaduvanshi, Aradhana; Srivastava, Prashant K.; Pandey, A. C.</p> <p></p> <p>Drought is a recurring feature of the climate, responsible for social and economic losses in India. In the present work, attempts were made to estimate the drought hazard and risk using spatial and temporal datasets of Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) in integration with socio-economic vulnerability. The TRMM rainfall was taken into account for trend analysis and Standardized Precipitation Index (SPI) estimation, with aim to investigate the changes in rainfall and deducing its pattern over the area. The SPI and average rainfall data derived from TRMM were interpolated to obtain the spatial and temporal pattern over the entire South Bihar of India, while the <span class="hlt">MODIS</span> datasets were used to derive the Normalized Difference Vegetation Index (NDVI) deviation in the area. The Geographical Information System (GIS) is taken into account to integrate the drought vulnerability and hazard, in order to estimate the drought risk over entire South Bihar. The results indicated that approximately 36.90% area is facing high to very high drought risk over north-eastern and western part of South Bihar and need conservation measurements to combat this disaster.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20010029450&hterms=human+impact+global+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dhuman%2Bimpact%252C%2Bglobal%2Bclimate','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20010029450&hterms=human+impact+global+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dhuman%2Bimpact%252C%2Bglobal%2Bclimate"><span id="translatedtitle">The Use of <span class="hlt">MODIS</span> Instrument on the EOS-Terra <span class="hlt">Satellite</span> to Assess the Impact of Aerosol on Climate</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Y.; Einaudi, Franco (Technical Monitor)</p> <p>2001-01-01</p> <p>Terra will derive the aerosol optical thickness and properties. The aerosol properties can be used to distinguish between natural and human-made aerosol. In the polar orbit Terra will measure aerosol only once a day, around 10:30 am. How will we use this information to study the global radiative impacts of aerosol on climate? We shall present a strategy to address this problem. It includes the following steps: 1) From the Terra aerosol optical thickness and size distribution model we derive the effect of aerosol on reflection of solar radiation at the top of the atmosphere. In a sensitivity study we show that the effect of aerosol on solar fluxes can be derived 10 times more accurately from the <span class="hlt">MODIS</span> data than derivation of the optical thickness itself. Applications to data over several regions will be given. 2) Using 1/2 million AERONET global data of aerosol spectral optical thickness we show that the aerosol optical thickness and properties during the Terra 10:30 pass are equivalent to the daily average. Due to the aerosol lifetime of several days measurements at this time of the day are enough to assess the daily impact of aerosol on radiation. 3) Aerosol impact on the top of the atmosphere is only part of the climate question. The INDOEX experiment showed that addressing the impact of aerosol on climate, requires also measurements of the aerosol forcing at the surface. This can be done by a combination of measurements of <span class="hlt">MODIS</span> and AERONET data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.H32B..04U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.H32B..04U"><span id="translatedtitle">The <span class="hlt">MODIS</span> Vegetation Canopy Water Content product</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ustin, S. L.; Riano, D.; Trombetti, M.</p> <p>2008-12-01</p> <p>Vegetation water stress drives wildfire behavior and risk, having important implications for biogeochemical cycling in natural ecosystems, agriculture, and forestry. Water stress limits plant transpiration and carbon gain. The regulation of photosynthesis creates close linkages between the carbon, water, and energy cycles and through metabolism to the nitrogen cycle. We generated systematic weekly CWC estimated for the USA from 2000-2006. <span class="hlt">MODIS</span> measures the sunlit reflectance of the vegetation in the visible, near-infrared, and shortwave infrared. Radiative transfer models, such as PROSPECT-SAILH, determine how sunlight interacts with plant and soil materials. These models can be applied over a range of scales and ecosystem types. Artificial Neural Networks (ANN) were used to optimize the inversion of these models to determine vegetation water content. We carried out multi-scale validation of the product using field data, airborne and <span class="hlt">satellite</span> cross-calibration. An Algorithm Theoretical Basis Document (ATBD) of the product is under evaluation by NASA. The CWC product inputs are 1) The <span class="hlt">MODIS</span> Terra/<span class="hlt">Aqua</span> surface reflectance product (MOD09A1/MYD09A1) 2) The <span class="hlt">MODIS</span> land cover map product (MOD12Q1) reclassified to grassland, shrub-land and forest canopies; 3) An ANN trained with PROSPECT-SAILH; 4) A calibration file for each land cover type. The output is an ENVI file with the CWC values. The code is written in Matlab environment and is being adapted to read not only the 8 day <span class="hlt">MODIS</span> composites, but also daily surface reflectance data. We plan to incorporate the cloud and snow mask and generate as output a geotiff file. Vegetation water content estimates will help predicting linkages between biogeochemical cycles, which will enable further understanding of feedbacks to atmospheric concentrations of greenhouse gases. It will also serve to estimate primary productivity of the biosphere; monitor/assess natural vegetation health related to drought, pollution or diseases</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.9090C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.9090C"><span id="translatedtitle">Methodology to obtain 30 m resolution of snow cover area from FSCA <span class="hlt">MODIS</span> and NDSI Landsat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cepeda, Javier; Vargas, Ximena</p> <p>2016-04-01</p> <p>In the last years numerous free images and product <span class="hlt">satellites</span> have been released, with different spatial and temporal resolution. Out of them, the most commonly used to describe the snow area are <span class="hlt">MODIS</span> and Landsat. Fractional snow cover area (FSCA) is a daily <span class="hlt">MODIS</span> product with a 500 m spatial resolution; Landsat images have around 16 days and 30 m respectively. In this work we use both images to obtain a new daily 30 m resolution snow distribution product based in probabilistic and geospatial information. This can be useful because a higher resolution can be used to improve the estimation of the accuracy of a physically-based distributed model to represent the snow cover distribution. We choose three basins in central Chile, with an important snow and glacier presence, to analyze the spatial and temporal distribution of snow using (1) the mean value between MOD10A1 (terra) and MYD10A1 (<span class="hlt">aqua</span>) and (2) the corrected images by topography and atmosphere from Landsat 5 and Landsat 8 computing the normalized difference snow index (NDSI). When both <span class="hlt">satellites</span> data are available in the same day, each <span class="hlt">MODIS</span> pixel is studied considering the Landsat pixels contained in it. A new matrix is created, covering all <span class="hlt">MODIS</span> pixels, using a 30 m spatial resolution, where each pixel value represents the probability of snow presence in time from Landsat images, and then each pixel is corrected by its neighbour's pixels, elevation, slope and aspect. Then snow is distributed, for each <span class="hlt">MODIS</span> pixel, considering the corrected probability matrix and sorted between pixels with high probability until the area from FSCA is completed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030054535','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030054535"><span id="translatedtitle">Exploring New Methods of Displaying Bit-Level Quality and Other Flags for <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Khalsa, Siri Jodha Singh; Weaver, Ron</p> <p>2003-01-01</p> <p>The NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC) archives and distributes snow and sea ice products derived from the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>. All <span class="hlt">MODIS</span> standard products are in the Earth Observing System version of the Hierarchal Data Format (HDF-EOS). The <span class="hlt">MODIS</span> science team has packed a wealth of information into each HDF-EOS file. In addition to the science data arrays containing the geophysical product, there are often pixel-level Quality Assurance arrays which are important for understanding and interpreting the science data. Currently, researchers are limited in their ability to access and decode information stored as individual bits in many of the <span class="hlt">MODIS</span> science products. Commercial and public domain utilities give users access, in varying degrees, to the elements inside <span class="hlt">MODIS</span> HDF-EOS files. However, when attempting to visualize the data, users are confronted with the fact that many of the elements actually represent eight different 1-bit arrays packed into a single byte array. This project addressed the need for researchers to access bit-level information inside <span class="hlt">MODIS</span> data files. In an previous NASA-funded project (ESDIS Prototype ID 50.0) we developed a visualization tool tailored to polar gridded HDF-EOS data set. This tool,called the Polar researchers to access, geolocate, visualize, and subset data that originate from different sources and have different spatial resolutions but which are placed on a common polar grid. The bit-level visualization function developed under this project was added to PHDIS, resulting in a versatile tool that serves a variety of needs. We call this the EOS Imaging Tool.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=62621&keyword=landscape+AND+architecture&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=64911636&CFTOKEN=97393792','EPA-EIMS'); return false;" href="http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=62621&keyword=landscape+AND+architecture&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=64911636&CFTOKEN=97393792"><span id="translatedtitle">ANALYSIS OF YEAR 2002 SEASONAL FOREST DYNAMICS USING TIME SERIES IN SITU LAI MEASUREMENTS AND <span class="hlt">MODIS</span> LAI <span class="hlt">SATELLITE</span> PRODUCTS</span></a></p> <p><a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>Multitemporal <span class="hlt">satellite</span> images are the standard basis for regional-scale land-cover (LC) change detection. However, embedded in the data are the confounding effects of vegetation dynamics (phenology). As photosynthetic vegetation progresses through its annual cycle, the spectral ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100020840','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100020840"><span id="translatedtitle"><span class="hlt">MODIS</span> On-Board Blackbody Function and Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiaoxiong, Xiong; Wenny, Brian N.; Wu, Aisheng; Barnes, William</p> <p>2009-01-01</p> <p>Two <span class="hlt">MODIS</span> instruments are currently in orbit, making continuous global observations in visible to long-wave infrared wavelengths. Compared to heritage sensors, <span class="hlt">MODIS</span> was built with an advanced set of on-board calibrators, providing sensor radiometric, spectral, and spatial calibration and characterization during on-orbit operation. For the thermal emissive bands (TEB) with wavelengths from 3.7 m to 14.4 m, a v-grooved blackbody (BB) is used as the primary calibration source. The BB temperature is accurately measured each scan (1.47s) using a set of 12 temperature sensors traceable to NIST temperature standards. The onboard BB is nominally operated at a fixed temperature, 290K for Terra <span class="hlt">MODIS</span> and 285K for <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, to compute the TEB linear calibration coefficients. Periodically, its temperature is varied from 270K (instrument ambient) to 315K in order to evaluate and update the nonlinear calibration coefficients. This paper describes <span class="hlt">MODIS</span> on-board BB functions with emphasis on on-orbit operation and performance. It examines the BB temperature uncertainties under different operational conditions and their impact on TEB calibration and data product quality. The temperature uniformity of the BB is also evaluated using TEB detector responses at different operating temperatures. On-orbit results demonstrate excellent short-term and long-term stability for both the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-board BB. The on-orbit BB temperature uncertainty is estimated to be 10mK for Terra <span class="hlt">MODIS</span> at 290K and 5mK for <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> at 285K, thus meeting the TEB design specifications. In addition, there has been no measurable BB temperature drift over the entire mission of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015EGUGA..17.6757G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015EGUGA..17.6757G&link_type=ABSTRACT"><span id="translatedtitle">Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series <span class="hlt">MODIS</span> and LANDSAT <span class="hlt">satellite</span> images</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Georgopoulou, Danai; Koutsias, Nikos</p> <p>2015-04-01</p> <p>Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when <span class="hlt">satellite</span> remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series <span class="hlt">MODIS</span> and LANDSAT <span class="hlt">satellite</span> images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. <span class="hlt">Satellite</span> remote sensing data from <span class="hlt">MODIS</span> and LANDSAT <span class="hlt">satellites</span> in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the <span class="hlt">satellite</span> data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120002030','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120002030"><span id="translatedtitle">Analysis of Co-Located <span class="hlt">MODIS</span> and CALIPSO Observations Near Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Varnai, Tamas; Marshak, Alexander</p> <p>2011-01-01</p> <p>The purpose of this paper is to help researchers combine data from different <span class="hlt">satellites</span> and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the <span class="hlt">Aqua</span> <span class="hlt">satellite</span>'s <span class="hlt">MODIS</span> instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO <span class="hlt">satellite</span>'s CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the <span class="hlt">satellite</span> orbit by measuring the reflection of its pulses. In contrast, <span class="hlt">MODIS</span> takes images of reflected sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the <span class="hlt">satellite</span> track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that <span class="hlt">MODIS</span> can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between <span class="hlt">MODIS</span> and CALIOP observations have only a minor impact. The study also finds that <span class="hlt">MODIS</span> data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when <span class="hlt">MODIS</span> cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011753','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011753"><span id="translatedtitle">Global Distributions of Mineral Dust Properties from SeaWiFS and <span class="hlt">MODIS</span>: From Sources to Sinks</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina; Bettenhausen, C.; Sayer, A.</p> <p>2011-01-01</p> <p>The impact of natural and anthropogenic sources of mineral dust has gained increasing attention from scientific communities in recent years. Indeed, these airborne dust particles, once lifted over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the oceans resulting in important biogeochemical impacts on the ecosystem. Due to the relatively short lifetime (a few hours to about a week), the distributions of these mineral dust particles vary extensively in both space and time. Consequently, <span class="hlt">satellite</span> observations are needed over both source and sink regions for continuous temporal and spatial sampling of aerosol properties. With the launch of SeaWiFS in 1997, Terra/<span class="hlt">MODIS</span> in 1999, and <span class="hlt">Aqua/MODIS</span> in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented <span class="hlt">satellite</span> data records, studies of the radiative and biogeochemical effects due to dust aerosols are now possible. In this study, we will show the comparisons of <span class="hlt">satellite</span> retrieved aerosol optical thickness using Deep Blue algorithm with data from AERONET sunphotometers over desert and semi-desert regions as well as vegetated areas. Our results indicate reasonable agreements between these two. These new <span class="hlt">satellite</span> products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from Sea WiFS and <span class="hlt">MODIS</span>-like instruments. The multiyear <span class="hlt">satellite</span> measurements since 1997 from Sea WiFS will be compared with those retrieved from <span class="hlt">MODIS</span> and MISR, and will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with the dust outbreaks over the entire globe. Finally, the trends observed over the last decade based upon the SeaWiFS time series in the amounts of tropospheric aerosols due to natural and anthropogenic sources (such as changes in the frequency</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016JGRD..121.5827W&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016JGRD..121.5827W&link_type=ABSTRACT"><span id="translatedtitle">Retrieval of ice cloud properties using an optimal estimation algorithm and <span class="hlt">MODIS</span> infrared observations: 2. Retrieval evaluation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Wind, Gala; Yang, Ping</p> <p>2016-05-01</p> <p>An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) observations is assessed in comparison with the operational retrieval products from <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> <span class="hlt">satellite</span> (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span> Observation (CALIPSO) <span class="hlt">satellite</span> in the Afternoon Constellation (A-Train) with <span class="hlt">Aqua</span>. The results show that OE-IR cloud optical thickness (τ) and effective radius (reff) retrievals perform best for ice clouds having 0.5 < τ < 7 and reff < 50 µm. For global ice clouds, the averaged retrieval uncertainties of τ and reff are 19% and 33%, respectively. For optically thick ice clouds with τ larger than 10, however, the τ and reff retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48 km. Relatively large h uncertainty (e.g., > 1 km) occurs for τ < 0.5. Analysis of 1 month of the OE-IR retrievals shows large τ and reff uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent τ and h retrievals. However, obvious differences between the OE-IR and the <span class="hlt">MODIS</span> Collection 6 reff are found.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003AGUFM.V32B1021F&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003AGUFM.V32B1021F&link_type=ABSTRACT"><span id="translatedtitle">Global Real-Time Volcano Hazard Monitoring with <span class="hlt">Satellites</span>: The Anatahan Eruption</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Flynn, L.; Wright, R.; Pilger, E.; Garbeil, H.</p> <p>2003-12-01</p> <p>On May 10, 2003, the island of Anatahan in the northern Mariana Islands experienced its first historical eruption. Anatahan is a 9 km long and 4 km wide island dominated by two volcanoes having E-W trending elongated and overlapping summit calderas. Following seismic activity in the 1990's, the island was largely evacuated. Thermal <span class="hlt">satellite</span> data not only confirmed the eruption of the eastern crater of Anatahan but also pinpointed the location of continuing activity over a two-week period following the start of the eruption. These data were forwarded to hazard mitigation officials within hours of acquisition. NASA's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) observes the Earth in the visible to infrared portion of the spectrum at 1 km x 1 km spatial resolution. Two <span class="hlt">MODIS</span> instruments on Terra and <span class="hlt">Aqua</span> provide global coverage 2-4 times per day, more towards higher latitudes. The Hawaii Institute of Geophysics and Planetology researchers developed an algorithm (MODVOLC) that mines the global <span class="hlt">Aqua</span> and Terra data sets in order to pinpoint locations of volcanic activity. Currently, the time lag between data acquisition by <span class="hlt">MODIS</span> and display on the web site is ~2-4 hours. Weekly hotspot reports identify active volcanoes around the globe. Many volcanoes (Erebus, Heard, Anatahan, Michael) are in remote locations and otherwise would have gone unobserved or underobserved. The <span class="hlt">MODIS</span> hotspot monitoring system provides reliable, and readily-accessible coverage of the world's volcanoes to support volcanic hazard mitigation efforts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B53G..07R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B53G..07R"><span id="translatedtitle">Comparisons of savanna functioning, phenology, and disturbance in Brazil and Australia using <span class="hlt">MODIS</span> and TRMM <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ratana, P.; Huete, A. R.; Ferreira, L. G.; Ma, X.; Restrepo-Coupe, N.</p> <p>2013-12-01</p> <p>The savanna biome is comprised of complex vegetation structures with multifunctional herbaceous (grass) and woody (tree- shrub) layers, each responding uniquely to different environmental controls. Globally, their rich biodiversity is under pressure from land conversion to crops, pastures, grazing activities, and fire. A better understanding of their vegetation functioning, seasonal dynamics and phenology, and responses to climate, disturbance, and management practices is needed. This study focuses on two contrasting tropical savanna regions; the Brazilian cerrado and the savanna biome in northern Australia. The cerrado has open to closed woodlands and is the most intensively converted (pastures), whereas the Australian savanna is relatively undisturbed and encompasses both wet and dry savanna classes along an ecological rainfall gradient. We investigated these environmental and management drivers on savanna class seasonal functioning patterns using the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) vegetation index (VI) time series from 2000 to 2013 combined with rainfall data over the same time period from the Tropical Rainfall Monitoring Mission (TRMM). We found unique seasonal/ phenological vegetation response patterns with varying tree- grass ratios, rainfall seasonal distribution, and magnitude of land conversion and management. Temporal VI profiles of both regions depicted high seasonal contrasts in vegetation production over the pronounced dry and wet seasons, and seasonal amplitude variations varied negatively with the presence and extent of woody tree cover. We found pronounced shifts in seasonal/ phenology patterns in both Brazilian cerrado and Australian savanna induced by land conversion. Lastly, sensitivity to climate variability was greatest in the areas dominated with low tree-grass ratios.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007SPIE.6680E..0QZ&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007SPIE.6680E..0QZ&link_type=ABSTRACT"><span id="translatedtitle">Possible <span class="hlt">satellite</span> oceanography on coastal waters during the NPP stage</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhu, J.; Asanuma, I.; Zhao, C.; Huang, B.</p> <p>2007-09-01</p> <p>Ocean color monitoring on the coastal water is still under study because of an incomplete atmospheric correction over the turbid water like over the coastal water along the China main land. Currently available sensors for science as <span class="hlt">MODIS</span> on Terra or <span class="hlt">Aqua</span> will terminate their service in the near future and the NPOESS Preparatory Project (NPP) will be the next <span class="hlt">satellite</span> to support the <span class="hlt">satellite</span> oceanography on the coastal water. The Tokyo University of Information Sciences (TUIS) has updated the <span class="hlt">MODIS</span> receiving system to capture and ingest the Visible/Infrared Imager/Radiometer Suite (VIIRS) data from NPP, which will be launched in 2008. Data processing software from the Direct Readout Laboratory (DRL), such as the Real-time Software Telemetry Processing (RT-STPS), Simulcast, and DB algorithms, will be core programs in our system. VIIRS has seven bands in VIS&NIR, which are for ocean color research. The spatial resolution is 0.742×0.259 meters at nadir. While the <span class="hlt">MODIS</span> spatial resolution of the nine ocean color bands is 1000m. The higher spatial resolution <span class="hlt">MODIS</span> data (250 meters) is used to illustrate the advantage of the higher spatial resolution remote sensing data, such as data from VIIRS. In this study, we propose to combine the higher spatial resolution data with the traditional products of chlorophyll-a and sea surface temperature in the low resolution so as to extract further information on the coastal ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A43B0273L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A43B0273L"><span id="translatedtitle">Evaluation of interregional variability in <span class="hlt">MODIS</span> cloud regimes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Leinonen, J. S.; Lebsock, M. D.; Oreopoulos, L.; Cho, N.</p> <p>2015-12-01</p> <p>Clustering techniques have been used in the last few decades to classify cloud types automatically from <span class="hlt">satellite</span> observations, most commonly using cloud top pressure and cloud optical depth. The underlying assumption is that the resulting clusters, called "cloud regimes" or "weather states", represent some type of basic states of the atmosphere, and thus that their occurrence can be used as a proxy for related variables such as radiative balance or precipitation. We have examined the validity of these assumptions by using independent measurements from the CloudSat and CALIPSO <span class="hlt">satellites</span>. The CloudSat radar yields a reflectivity product that is sensitive to many aspects of the physics of the clouds, while CloudSat together with the CALIPSO lidar can retrieve the vertical structure of the cloud column, including multi-layer clouds. These observations have been separated into groups according to the recently published cloud regimes based on data from the <span class="hlt">MODIS</span> instrument, deployed on the <span class="hlt">Aqua</span> <span class="hlt">satellite</span> orbiting in the same constellation with CloudSat and CALIPSO. The distributions of these observations have been constructed both globally and in a number of regions in different parts of the Earth. By analyzing the differences in the distributions between these regions, we can evaluate the usefulness of the cloud regimes as a proxy for the measured variables. Some cloud regimes have been found to be rather stable between regions, while others display considerable variability. Moreover, some cloud regimes appear much more similar to each other in CloudSat observations than they do using the <span class="hlt">MODIS</span> regimes. We analyze the implications of these differences for the usability of the cloud regimes as climate indicators. We also explore various filtering techniques and different clustering methods that can potentially be used to reduce these differences, and thus to improve the universality of the cloud regimes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33E0223X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33E0223X"><span id="translatedtitle">Status of <span class="hlt">MODIS</span> Instruments and Future Calibration Improvements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, X.; Angal, A.; Wu, A.; Salomonson, V. V.</p> <p>2015-12-01</p> <p><span class="hlt">MODIS</span> is one of the key instruments currently operated on two major missions for the NASA's Earth Observing System (EOS) program: Terra and <span class="hlt">Aqua</span> launched in 1999 and 2002, respectively. Nearly 40 data products have been routinely generated from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> observations and widely distributed to the science community and users worldwide for their studies of the earth's system and changes in its geophysical properties. To date, each <span class="hlt">MODIS</span> instrument operation remains nominal and its on-board calibrators (OBC) continue to function satisfactorily. On a regular basis, <span class="hlt">MODIS</span> reflective solar bands (RSB) calibration is performed by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). For the thermal emissive bands (TEB), an on-board blackbody (BB) provides a scan-by-scan calibration reference. Since launch, extensive calibration and characterization activities have been scheduled and implemented by the <span class="hlt">MODIS</span> Characterization Support Team (MCST) to produce and update calibration look-up tables (LUT). This presentation provides an overview of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument status, their on-orbit operation and calibration activities, and radiometric, spectral, and spatial performance. It describes calibration changes (algorithms and look-up tables) made for the <span class="hlt">MODIS</span> Level 1B (L1B) data collection 6 (C6) and discusses remaining challenging issues and ongoing effort for future improvements. As expected, lessons from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have benefitted and will continue to help the S-NPP and JPSS VIIRS instruments in terms of on-orbit operation strategies and calibration enhancements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713613K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713613K"><span id="translatedtitle">Monitoring the state of vegetation in Hungary using 15 years long <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kern, Anikó; Bognár, Péter; Pásztor, Szilárd; Barcza, Zoltán; Timár, Gábor; Lichtenberger, János; Ferencz, Csaba</p> <p>2015-04-01</p> <p>Monitoring the state and health of the vegetation is essential to understand causes and severity of environmental change and to prepare for the negative effects of climate change on plant growth and productivity. <span class="hlt">Satellite</span> remote sensing is the fundamental tool to monitor and study the changes of vegetation activity in general and to understand its relationship with the climate fluctuations. Vegetation indices and other vegetation related measures calculated from remotely sensed data are widely used to monitor and characterize the state of the terrestrial vegetation. Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are among the most popular indices that can be calculated from measurements of the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor onboard the NASA EOS-AM1/Terra and EOS-PM1/<span class="hlt">Aqua</span> <span class="hlt">satellites</span> (since 1999 and 2002 respectively). Based on the available, 15 years long <span class="hlt">MODIS</span> data (2000-2014) the vegetation characteristics of Hungary was investigated in our research, primarily using vegetation indices. The <span class="hlt">MODIS</span> NDVI and EVI (both part of the so-called MOD13 product of NASA) are freely available with a finest spatial resolution of 250 meters and a temporal resolution of 16 days since 2000/2002 (for Terra and <span class="hlt">Aqua</span> respectively). The accuracy, the spatial resolution and temporal continuity of the <span class="hlt">MODIS</span> products makes these datasets highly valuable despite of its relatively short temporal coverage. NDVI is also calculated routinely from the raw <span class="hlt">MODIS</span> data collected by the receiving station of Eötvös Loránd University. In order to characterize vegetation activity and its variability within the Carpathian Basin the area-averaged annual cycles and their interannual variability were determined. The main aim was to find those years that can be considered as extreme according to specific indices. Using archive meteorological data the effects of extreme weather on vegetation activity and growth were investigated with</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001AGUSM...U21A24D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001AGUSM...U21A24D"><span id="translatedtitle">The <span class="hlt">MODIS</span> Reprojection Tool</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dwyer, J.; Weiss, J.; Schmidt, G.; Logar, T.; Burrel, R.; Stubbendieck, G.; Rishea, J.; Misterek, B.; Jia, S.; Heuser, K.</p> <p>2001-05-01</p> <p>A software tool has been developed to reproject and reformat Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) level-3 science data products in order to ease their use with commercial-off-the-shelf software applications. The <span class="hlt">MODIS</span> instrument onboard NASA's Terra <span class="hlt">satellite</span> collects mesurements of the Earth's lands, oceans, atmosphere, and cryosphere that are used to study Earth system processes and the impacts of human interactions with the planet's environment. The USGS Earth Resources Observation Systems (EROS) Data Center (EDC) serves as the Land Processes Distributed Active Archive Center (DAAC) in support of NASA's Earth Observing System (EOS) Data and Information System (EOSDIS). The EDC DAAC archive and distributes the <span class="hlt">MODIS</span> land science data products and provides support services to the users of these data. A second <span class="hlt">MODIS</span> instrument, scheduled for launch in late 2001, will yield a secnd suite of product types identical to those generated from the Terra <span class="hlt">MODIS</span>. The <span class="hlt">MODIS</span> land products are distributed in the hierarchical data format (HDF-EOS) which is the common data format distributed by the EOSDIS. Many of the <span class="hlt">MODIS</span> land products are distributed as geophysical or biophysical parameters formatted as numerical arrays in the Integerized Sinusoidal (ISIN) projection. Neither the HDF-EOS format nor the ISIN projection are broadly supported by the types of applications software commonly used by the land science community. The EDC DAAC and the South Dakota School of Mines and Technology Department of Computer Sciences collaborated to develop a software tool that would reproject and reformat the data to enhance the ease of use of these <span class="hlt">MODIS</span> products. The <span class="hlt">MODIS</span> Reprojection Tool (MRT) enables a user to perform various combinations of the following functions: read HDF-EOS file formats; view metadata; process selective subsets of the data; reproject and resample data to different output projections and grid spacing; and generate alternative file formats to HDF</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC51D0445Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC51D0445Y"><span id="translatedtitle">Towards Monitoring <span class="hlt">Satellite</span> Land Surface Temperature Production</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yu, P.; Yu, Y.; Liu, Y.; Wang, Z.; Zhang, X.</p> <p>2014-12-01</p> <p>Land surface temperature (LST) is of fundamental importance to the net radiation budget at the Earth surface and to monitoring the state of crops and vegetation, as well as an important indicator of both the greenhouse effect and the energy flux between the atmosphere and the land. Since its launch on October 28, 2011, the Suomi National Polar-orbiting Partnership (S-NPP) <span class="hlt">satellite</span> has been continuously providing data for LST production; intensive validation and calibration of the LST data have been conducted since then. To better monitor the performance of the S-NPP LST product and evaluate different retrieval algorithms for potential improvement, a near-real-time monitoring system has been developed and implemented. The system serves as a tool for both the routine monitoring and the deep-dive researches. It currently consists of two major components: the global cross-<span class="hlt">satellite</span> LST comparisons between S-NPP/VIIRS and <span class="hlt">MODIS/AQUA</span>, and the LST validation with respect to in-situ observations from SURFRAD network. Results about cross-<span class="hlt">satellite</span> comparisons, <span class="hlt">satellite</span>-in situ LST validation, and evaluation of different retrieval algorithms are routinely generated and published through an FTP server of the system ftp. The results indicate that LST from the S-NPP is comparable to that from <span class="hlt">MODIS</span>. A few case studies using this tool will be analyzed and presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008694','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008694"><span id="translatedtitle">Implications of <span class="hlt">Satellite</span> Swath Width on Global Aerosol Optical Thickness Statistics</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Colarco, Peter; Kahn, Ralph; Remer, Lorraine; Levy, Robert; Welton, Ellsworth</p> <p>2012-01-01</p> <p>We assess the impact of swath width on the statistics of aerosol optical thickness (AOT) retrieved by <span class="hlt">satellite</span> as inferred from observations made by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). We sub-sample the year 2009 <span class="hlt">MODIS</span> data from both the Terra and <span class="hlt">Aqua</span> spacecraft along several candidate swaths of various widths. We find that due to spatial sampling there is an uncertainty of approximately 0.01 in the global, annual mean AOT. The sub-sampled monthly mean gridded AOT are within +/- 0.01 of the full swath AOT about 20% of the time for the narrow swath sub-samples, about 30% of the time for the moderate width sub-samples, and about 45% of the time for the widest swath considered. These results suggest that future aerosol <span class="hlt">satellite</span> missions with only a narrow swath view may not sample the true AOT distribution sufficiently to reduce significantly the uncertainty in aerosol direct forcing of climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140007328','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140007328"><span id="translatedtitle">Identifying Hail Signatures in <span class="hlt">Satellite</span> Imagery from the 9-10 August 2011 Severe Weather Event</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Dryden, Rachel L.; Molthan, Andrew L.; Cole, Tony A.; Bell, Jordan</p> <p>2014-01-01</p> <p>Severe thunderstorms can produce large hail that causes property damage, livestock fatalities, and crop failure. However, detailed storm surveys of hail damage conducted by the National Weather Service (NWS) are not required. Current gaps also exist between Storm Prediction Center (SPC) hail damage estimates and crop-insurance payouts. NASA's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument aboard the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> can be used to support NWS damage assessments, particularly to crops during the growing season. The two-day severe weather event across western Nebraska and central Kansas during 9-10 August 2011 offers a case study for investigating hail damage signatures by examining changes in Normalized Difference Vegetation Index (NDVI) derived from <span class="hlt">MODIS</span> imagery. By analyzing hail damage swaths in <span class="hlt">satellite</span> imagery, potential economic losses due to crop damage can be quantified and further improve the estimation of weather impacts on agriculture without significantly increasing manpower requirements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C51B0489K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C51B0489K"><span id="translatedtitle">An Artificial Neural Network Approach to Surface Melt Magnitude Retrieval over West Antarctic Ice Shelves Using Coupled <span class="hlt">MODIS</span> Optical and Thermal <span class="hlt">Satellite</span> Measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karmosky, C. C.; Lampkin, D. J.</p> <p>2009-12-01</p> <p>Ice shelf stability is of crucial importance in the Antarctic because shelves serve as buttresses to glacial ice advancing from the Antarctic Ice Sheet. Surface melt has been increasing over recent years, especially over the Antarctic Peninsula, contributing to disintegration of shelves such as Larsen. <span class="hlt">Satellite</span> based assessments of melt from passive microwave systems are limited in that they only provide an indication of melt occurrence and have coarse resolution. Though this is useful in tracking the duration of melt, melt amount of magnitude is still unknown. Coupled optical/thermal surface measurements from <span class="hlt">MODIS</span> were calibrated by estimates of liquid water fraction (LWF) in the upper 1cm of the firn derived from a one-dimensional thermal snowmelt model (SNTHERM). SNTHERM was forced by hourly meteorological data from automatic weather station data at seven reference sites spanning a range of melt conditions across several West Antarctic ice shelves. A calibration “curve” was developed using an artificial neural network platform to derive LWF for <span class="hlt">satellite</span> composite periods covering the Antarctic summer months at a 4km resolution over the Larsen Ice Shelf, Ronne-Filchner Ice Shelf and the Ross Ice Shelf, ranging from near 0% LWF to upwards of 5% LWF on the Larsen Ice Shelf during the time of peak surface melt. Spatial and temporal variations in the amount of surface melt are seen to be related to both katabatic wind strength and wind shifts due to the progression of cyclones along the circumpolar vortex. Sea ice concentration along the ice shelf front, specifically the formation of polynyas, are also thought to be driving factors for surface melt as latent and sensible heat fluxes increase by one to three orders of magnitude as polynyas form.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005JApMe..44..221M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005JApMe..44..221M"><span id="translatedtitle">Evaluation of Cirrus Cloud Properties Derived from <span class="hlt">MODIS</span> Data Using Cloud Properties Derived from Ground-Based Observations Collected at the ARM SGP Site.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mace, Gerald G.; Zhang, Yuying; Platnick, Steven; King, Michael D.; Minnis, Patrick; Yang, Ping</p> <p>2005-02-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board the NASA Terra <span class="hlt">satellite</span> has been collecting global data since March 2000 and the one on the <span class="hlt">Aqua</span> <span class="hlt">satellite</span> since June 2002. In this paper, cirrus cloud properties derived from ground-based remote sensing data are compared with similar cloud properties derived from <span class="hlt">MODIS</span> data on Terra. To improve the space-time correlation between the <span class="hlt">satellite</span> and ground-based observations, data from a wind profiler are used to define the cloud advective streamline along which the comparisons are made. In this paper, approximately two dozen cases of cirrus are examined and a statistical approach to the comparison that relaxes the requirement that clouds occur over the ground-based instruments during the overpass instant is explored. The statistical comparison includes 168 cloudy <span class="hlt">MODIS</span> overpasses of the Southern Great Plains (SGP) region and approximately 300 h of ground-based cirrus observations. The physical and radiative properties of cloud layers are derived from <span class="hlt">MODIS</span> data separately by the <span class="hlt">MODIS</span> Atmospheres Team and the Clouds and the Earth's Radiant Energy System (CERES) Science Team using multiwavelength reflected solar and emitted thermal radiation measurements. Using two ground-based cloud property retrieval algorithms and the two <span class="hlt">MODIS</span> algorithms, a positive correlation in the effective particle size, the optical thickness, the ice water path, and the cloud-top pressure between the various methods is shown, although sometimes there are significant biases. Classifying the clouds by optical thickness, it is demonstrated that the regionally averaged cloud properties derived from <span class="hlt">MODIS</span> are similar to those diagnosed from the ground. Because of a conservative approach toward identifying thin cirrus pixels over this region, the area-averaged cloud properties derived from the <span class="hlt">MODIS</span> Atmospheres MOD06 product tend to be biased slightly toward the optically thicker pixels. This bias tendency has implications for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015781','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015781"><span id="translatedtitle">Developing and Evaluating RGB Composite <span class="hlt">MODIS</span> Imagery for Applications in National Weather Service Forecast Offices</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oswald, Hayden; Molthan, Andrew L.</p> <p>2011-01-01</p> <p><span class="hlt">Satellite</span> remote sensing has gained widespread use in the field of operational meteorology. Although raw <span class="hlt">satellite</span> imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral <span class="hlt">satellite</span> imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological <span class="hlt">Satellites</span> (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future <span class="hlt">satellite</span> capabilities to forecasters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110013319','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110013319"><span id="translatedtitle">Quantitative Evaluation of <span class="hlt">MODIS</span> Fire Radiative Power Measurement for Global Smoke Emissions Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Ellison, Luke</p> <p>2011-01-01</p> <p><span class="hlt">Satellite</span> remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the <span class="hlt">MODIS</span> sensors aboard the polar orbiting Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary <span class="hlt">satellite</span>. During the last few years, FRP has steadily gained increasing recognition as an important parameter for facilitating the development of various scientific studies and applications relating to the quantitative characterization of biomass burning and their emissions. To establish the scientific integrity of the FRP as a stable quantity that can be measured consistently across a variety of sensors and platforms, with the potential of being utilized to develop a unified long-term climate data record of fire activity and impacts, it needs to be thoroughly evaluated, calibrated, and validated. Therefore, we are conducting a detailed analysis of the FRP products from <span class="hlt">MODIS</span> to evaluate the uncertainties associated with them, such as those due to the effects of <span class="hlt">satellite</span> variable observation geometry and other factors, in order to establish their error budget for use in diverse scientific research and applications. In this presentation, we will show recent results of the <span class="hlt">MODIS</span> FRP uncertainty analysis and error mitigation solutions, and demonstrate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.B41C0387S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.B41C0387S"><span id="translatedtitle">Collection 5 <span class="hlt">MODIS</span> LAI/FPAR Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Samanta, A.; Ganguly, S.; Schull, M. A.; Shabanov, N. V.; Knyazikhin, Y.; Myneni, R. B.</p> <p>2008-12-01</p> <p><span class="hlt">MODIS</span> LAI algorithm was substantially refined for the Collection 5 reprocessing to optimally use suite of <span class="hlt">MODIS</span> observations from Terra and <span class="hlt">Aqua</span> sensors. Refinements are based on advancements in RT theory, analysis of former versions of global time series of LAI product and product validation with field measurements. The Look-up-tables were regenerated for all vegetation types based on a new Stochastic RT model. The Collection 5 suite of LAI/FPAR products possesses higher quality retrievals than previous versions. The following 1-km products are operationally generated at NASA Science Computing Facilities (SCF): 8-day Terra and <span class="hlt">Aqua</span> products, 8-days Combined Terra and <span class="hlt">Aqua</span> product, and 4-day Combined Terra and <span class="hlt">Aqua</span> product. In addition, monthly Collection 5 Terra products are processed and archived at the Boston University (BU) SCF. In this study, we analyzed Collection 5 LAI/FPAR products over a range of spatial scales: Global, North American continent (single composite during the growing season), at scale of <span class="hlt">MODIS</span> tile (annual time series for three <span class="hlt">MODIS</span> tiles), and at the scale of validation sites (annual time series for three sites). For analysis we used Collection 5 BU monthly Terra products. The LAI retrieval algorithm consists of two parts: main (Radiative Transfer based) and back-up (empirical). The BU monthly compositing scheme consists of 3 main steps: 1) selection of data from 8-day MOD15A2 product; 2) assembling tile data into global map based on a global land cover; and 3) degrading from 1km resolution to 4km resolution. We focused on the following: 1) Enhancement in the number of high quality retrievals in Collection 5; 2) Utility of the product to improve retrievals under atmospheric contamination of surface reflectance (clouds, aerosols) and for dense vegetation under saturation of surface reflectance; 3) Utility of the product to improve temporal resolution of retrievals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012IJBm...56.1179P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012IJBm...56.1179P"><span id="translatedtitle">Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, Isaac W.</p> <p>2012-11-01</p> <p>This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to <span class="hlt">satellite</span>-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080014145','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080014145"><span id="translatedtitle">Integrated Cloud-Aerosol-Radiation Product using CERES, <span class="hlt">MODIS</span>, CALIPSO and CloudSat Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave</p> <p>2007-01-01</p> <p>This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the <span class="hlt">Aqua</span> Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), Cloud-Aerosol Lidar and Infrared Pathfinder <span class="hlt">Satellite</span> Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-<span class="hlt">MODIS</span> analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3- dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-<span class="hlt">MODIS</span> global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008SPIE.7152E..0PK&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008SPIE.7152E..0PK&link_type=ABSTRACT"><span id="translatedtitle">Detection of dust and sandstorms from Taklamakan Desert to Japan by using <span class="hlt">MODIS</span> mosaic images</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kato, Yoshinobu</p> <p>2008-12-01</p> <p>In recent years, the number of days which dust and sandstorms (DSS) events were observed is increasing in Japan, Korea, China and Mongolia. The Aerosol Vapor Index (AVI) method is a DSS detection method. The AVI is defined as AVI=Tb32-Tb31 for <span class="hlt">MODIS</span> data of Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, where Tb31 is the brightness temperature of band 31 (10.780-11.280μm) and Tb32 is that of band 32 (11.770-12.270μm). The <span class="hlt">MODIS</span> mosaic images of true-color, AVI and thermal images are made for the detection of DSS from Taklamakan Desert to Japan. The detection of DSS is possible both at daytime and night, because the AVI method is used. The density of DSS is classified into six levels from 0 (DSS none) to 5 (DSS strong) according to the AVI values. The DSS phenomena during 6-11 April 2006 are analyzed by using the mosaic images of Terra-<span class="hlt">MODIS</span>. The number of pixels, which is approximately equal to the area of square kilometers, at each level of DSS density is measured. The AVI value at sea is about 0.2-2.3K lower than that at land, because of the influence of water vapor. In daytime, the generation place of DSS hidden under the cloud can be estimated by comparing AVI image with true-color and thermal images.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A32C..04W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A32C..04W"><span id="translatedtitle">Validation of AIRS Cloud Cleared Radiances Using <span class="hlt">MODIS</span> and its Affect on QualityControl</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wilson, R. C.; Schreier, M. M.</p> <p>2015-12-01</p> <p>The Atmospheric Infrared Sounder (AIRS) was launched aboard the <span class="hlt">AQUA</span> <span class="hlt">satellite</span> to provide measurements of temperature, humidity, and various trace gases in support of climate research and weather prediction. Only clear sky measurements of the outgoing radiance are used in the AIRS physical retrieval of temperature, water vapor, and certain trace gases. To overcome cloud contamination the clear sky radiance is estimated using an iterative procedure that combines an initial estimate of the clear state from a neural network along with a three by three grid of AIRS measurements. The radiance error estimate, a component critical to the AIRS physical retrieval, must include contributions from all assumed parameters input to the forward model on top of instrument noise and amplification from cloud clearing. When the error estimate is too large the AIRS physical retrieval becomes over-constrained to the first guess profile. Therefore quantifying the cloud cleared error estimate is essential to an effective physical retrieval. We will validate the cloud-cleared radiances through the use of nearby clear ocean scenes and with comparisons to clear pixels from the Moderate Resolution Imaging Spectro-radiometer (<span class="hlt">MODIS</span>). AIRS cloud cleared radiances are spectrally convolved to <span class="hlt">MODIS</span> channels for this comparison. This analysis quantifies error due to cloud-clearing and demonstrates that clear <span class="hlt">MODIS</span> pixels can be used with the standard AIRS quality control procedure to improve identification poor retrievals.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030025758','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030025758"><span id="translatedtitle">Cloud and Aerosol Properties, Precipitable Water, and Profiles of Temperature and Water Vapor from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Menzel, W. Paul; Kaufman, Yoram J.; Tanre, Didier; Gao, Bo-Cai; Platnick, Steven; Ackerman, Steven A.; Remer, Lorraine A.; Pincus, Robert; Hubanks, Paul A.</p> <p>2003-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is an earth-viewing sensor that flies on the Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, launched in 1999 and 2002, respectively. <span class="hlt">MODIS</span> scans a swath width of 2330 km that is sufficiently wide to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km. <span class="hlt">MODIS</span> provides images in 36 spectral bands between 0.415 and 14.235 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to en- able advanced studies of land, ocean, and atmospheric properties. Twenty-six bands are used to derive atmospheric properties such as cloud mask, atmospheric profiles, aerosol properties, total precipitable water, and cloud properties. In this paper we describe each of these atmospheric data products, including characteristics of each of these products such as file size, spatial resolution used in producing the product, and data availability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JGRD..118.7864S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JGRD..118.7864S"><span id="translatedtitle">Validation and uncertainty estimates for <span class="hlt">MODIS</span> Collection 6 "Deep Blue" aerosol data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.</p> <p>2013-07-01</p> <p>The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of <span class="hlt">MODIS</span> products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (τM) from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56τM)/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20τM, comparable in quality to other <span class="hlt">satellite</span> AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050156904','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050156904"><span id="translatedtitle">Crop Surveillance Demonstration Using a Near-Daily <span class="hlt">MODIS</span> Derived Vegetation Index Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don</p> <p>2005-01-01</p> <p>Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument flown on the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily <span class="hlt">MODIS</span> imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI <span class="hlt">MODIS</span> products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013035','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013035"><span id="translatedtitle">Validation and Uncertainty Estimates for <span class="hlt">MODIS</span> Collection 6 "Deep Blue" Aerosol Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.</p> <p>2013-01-01</p> <p>The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of <span class="hlt">MODIS</span> products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other <span class="hlt">satellite</span> AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.B43E0451L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.B43E0451L"><span id="translatedtitle">Development of estimation method for crop yield using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery data and process-based model for corn and soybean in US Corn-Belt region</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.</p> <p>2012-12-01</p> <p>Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using <span class="hlt">satellite</span> remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, <span class="hlt">MODIS</span>-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from <span class="hlt">MODIS</span> and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110007300&hterms=ecosystem+marine&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystem%2Bmarine','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110007300&hterms=ecosystem+marine&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystem%2Bmarine"><span id="translatedtitle">Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, <span class="hlt">MODIS</span>, and MISR</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.</p> <p>2010-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Airborne Simulator (MAS) and <span class="hlt">MODIS</span>/Advanced Spaceborne Thermal Emission and 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 <span class="hlt">MODIS</span> Cloud data from the <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span> (Collection 5). This analysis shows that the cloud mask developed for operational use on <span class="hlt">MODIS</span>, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from <span class="hlt">MODIS</span> on the Terra spacecraft. Finally, this <span class="hlt">MODIS</span>-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AMT.....9.3293G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AMT.....9.3293G&link_type=ABSTRACT"><span id="translatedtitle">A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in <span class="hlt">MODIS</span> Dark Target retrieval algorithm</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gupta, Pawan; Levy, Robert C.; Mattoo, Shana; Remer, Lorraine A.; Munchak, Leigh A.</p> <p>2016-07-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments, aboard the two Earth Observing System (EOS) <span class="hlt">satellites</span> Terra and <span class="hlt">Aqua</span>, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from <span class="hlt">MODIS</span> that can be used for various climate and air-quality applications. However, the application of <span class="hlt">MODIS</span> aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the <span class="hlt">MODIS</span> Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating <span class="hlt">MODIS</span> Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for <span class="hlt">MODIS</span> pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ChJOL.tmp...65Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ChJOL.tmp...65Y"><span id="translatedtitle">Suspended sediment concentration mapping based on the <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery in the East China inland, estuarine, and coastal waters</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Xianping; Sokoletsky, Leonid; Wei, Xiaodao; Shen, Fang</p> <p>2016-04-01</p> <p>The purpose of this research is to improve the retrieval accuracy for the suspended sediment concentration (SSC) from in situ and <span class="hlt">satellite</span> remote sensing measurements in turbid East China estuarine and coastal waters. For this aim, three important tasks are formulated and solved: 1) an estimation of remote-sensing reflectance spectra R rs(λ) after atmospheric correction; 2) an estimation of R rs(λ) from the radiometric signals above the air-water surface; and 3) an estimation of SSC from R rs(λ). Six different models for radiometric R rs(λ) determination and 28 models for SSC versus R rs(λ) are analyzed based on the field observations made in the Changjiang River estuary and its adjacent coastal area. The SSC images based on the above-mentioned analysis are generated for the area.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/22350421','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/22350421"><span id="translatedtitle">Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to <span class="hlt">MODIS</span> <span class="hlt">satellite</span> imagery.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Park, Isaac W</p> <p>2012-11-01</p> <p>This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to <span class="hlt">satellite</span>-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods. PMID:22350421</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113326C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113326C"><span id="translatedtitle">On the evaluation of vegetation resilience in Southern Italy by using <span class="hlt">satellite</span> VEGETATION, <span class="hlt">MODIS</span>, TM time series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Coluzzi, C.; Didonna, I.</p> <p>2009-04-01</p> <p><span class="hlt">Satellite</span> technologies can be profitably used for investigating the dynamics of vegetation re-growth after disturbance at different temporal and spatial scales. Nevertheless, disturbance -induced dynamical processes are very difficult to study since they affect the complex soil-surface-atmosphere system, due to the existence of feedback mechanisms involving human activity, ecological patterns and different subsystems of climate. The remote sensing of vegetation has been traditionally carried out by using vegetation indices, which are quantitative measures, based on vegetation spectral properties, that attempt to measure biomass or vegetative vigor. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. The simplest form of vegetation index is simply a ratio between two digital values from these two spectral bands. The most widely used index is the well-known normalized difference vegetation index NDVI = [NIR-R]/ [NIR+R]. The normalization of the NDVI reduces the effects of variations caused by atmospheric contaminations. High values of the vegetation index identify pixels covered by substantial proportions of healthy vegetation. NDVI is indicative of plant photosynthetic activity and has been found to be related to the green leaf area index and the fraction of photosynthetically active radiation absorbed by vegetation. Therefore variations in NDVI values become indicative of variations in vegetation composition and dynamics. In this study, we analyze the mutiscale <span class="hlt">satellite</span> temporal series ( 1998 to 2008) of NDVI and other vegetation indices from SPOT VEGETATION and Landsat TM data acquired for some significant test areas affetced and unaffected (Southern Italy) by different type of environmenta diturbances (drought, salinity, pollution, etc). Our objective is to characterize quantitatively the resilient effect of vegetation cover at different temporal and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AtmEn.141..186X&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AtmEn.141..186X&link_type=ABSTRACT"><span id="translatedtitle">On the influence of the diurnal variations of aerosol content to estimate direct aerosol radiative forcing using <span class="hlt">MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Hui; Guo, Jianping; Ceamanos, Xavier; Roujean, Jean-Louis; Min, Min; Carrer, Dominique</p> <p>2016-09-01</p> <p>Long-term measurements of aerosol optical depth (AOD) from the Aerosol Robotic Network (AERONET) located in Beijing reveal a strong diurnal cycle of aerosol load staged by seasonal patterns. Such pronounced variability is matter of importance in respect to the estimation of daily averaged direct aerosol radiative forcing (DARF). Polar-orbiting <span class="hlt">satellites</span> could only offer a daily revisit, which turns in fact to be even much less in case of frequent cloudiness. Indeed, this places a severe limit to properly capture the diurnal variations of AOD and thus estimate daily DARF. Bearing this in mind, the objective of the present study is however to evaluate the impact of AOD diurnal variations for conducting quantitative assessment of DARF using Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) AOD data over Beijing. We provide assessments of DARF with two different assumptions about diurnal AOD variability: taking the observed hourly-averaged AOD cycle into account and assuming constant <span class="hlt">MODIS</span> (including Terra and <span class="hlt">Aqua</span>) AOD value throughout the daytime. Due to the AOD diurnal variability, the absolute differences in annual daily mean DARFs, if the constant <span class="hlt">MODIS</span>/Terra (<span class="hlt">MODIS/Aqua</span>) AOD value is used instead of accounting for the observed hourly-averaged daily variability, is 1.2 (1.3) Wm-2 at the top of the atmosphere, 27.5 (30.6) Wm-2 at the surface, and 26.4 (29.3) Wm-2 in the atmosphere, respectively. During the summertime, the impact of the diurnal AOD variability on seasonal daily mean DARF estimates using <span class="hlt">MODIS</span> Terra (<span class="hlt">Aqua</span>) data can reach up to 2.2 (3.9) Wm-2 at the top of the atmosphere, 43.7 (72.7) Wm-2 at the surface, and 41.4 (68.8) Wm-2 in the atmosphere, respectively. Overall, the diurnal variation in AOD tends to cause large bias in the estimated DARF on both seasonal and annual scales. In summertime, the higher the surface albedo, the stronger impact on DARF at the top of the atmosphere caused by dust and biomass burning (continental) aerosol. This</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040171680&hterms=land+cover+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dland%2Bcover%2Bchange','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040171680&hterms=land+cover+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dland%2Bcover%2Bchange"><span id="translatedtitle">Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra <span class="hlt">MODIS</span> Land Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng</p> <p>2004-01-01</p> <p>Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from <span class="hlt">MODIS</span> instruments aboard NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellite</span> platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016PhDT........43M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016PhDT........43M&link_type=ABSTRACT"><span id="translatedtitle">Estimation of suspended particulate matter concentration in the Mississippi Sound using <span class="hlt">MODIS</span> imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Merritt, Danielle</p> <p></p> <p>The discharge of sediment-laden rivers into the Mississippi Sound increases the turbidity of coastal waters. The concentration of suspended particulates is an important parameter in the analysis of coastal water quality factors. The spatiotemporal resolution associated with <span class="hlt">satellite</span> sensors makes remote sensing an ideal tool to monitor suspended particulate concentrations. Accordingly, the presented research evaluated the validity of published algorithms that relate remote sensing reflectance (Rrs) with suspended particulate matter for the Mississippi Sound. Additionally, regression analysis was used to correlate in situ SPM concentrations with coincident observations of visible and nearinfrared band reflectance collected by the <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> sensor in order to develop a predictive model for SPM. The most robust algorithm yielded an RMSE of 15.53% (n = 86) in the determination of SPM concentrations. The application of this algorithm allows for the rapid assessment of water quality issues related to elevated SPM concentrations in the Mississippi Sound.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AIPC.1531...31L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AIPC.1531...31L"><span id="translatedtitle">Growing up <span class="hlt">MODIS</span>: Towards a mature aerosol climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, Robert C.</p> <p>2013-05-01</p> <p>Aerosols are major players within the Earth's climate system, affecting the radiation budget, clouds and the hydrological cycle. In high concentrations near the surface, aerosols (or particulate matter, PM) affect visibility, impact air quality, and can contribute to poor health. Among others, Yoram Kaufman recognized the importance of aerosols to climate, and helped to design new instrumentation and algorithms to retrieve and quantify global aerosol properties. One instrument, known as the Moderate Imaging Resolution Spectro-radiometer (<span class="hlt">MODIS</span>), was deployed on the AM-1 <span class="hlt">satellite</span> (later known as Terra), part of NASA's Earth Observing System (EOS). In 1998, armed with an M.S. and job experience in neither aerosols nor <span class="hlt">satellites</span>, I was looking for a new job. I somehow found my way to the <span class="hlt">MODIS</span> Aerosol team. It was only a year before Terra launch, and most major decisions about the <span class="hlt">MODIS</span> aerosol retrieval algorithms had been finalized. Since then, we worked through launch, initial evaluation of the product with AERONET and field deployments, and continued efforts to understand the product and refine retrieval algorithms. I have had opportunities to participate in field experiments, write papers, and earn my PhD. The "second generation" algorithm for aerosol retrieval over land has been hugely successful. We have collected nearly a half-million collocations with AERONET and other dataseis, made new discoveries, and have contributed to research and operational projects globally. Due to the dedication of the entire team, the <span class="hlt">MODIS</span> aerosol product now is one of the highlights of NASA's EOS program. It is used for climate research and air quality forecasting, as well for applications not even considered before the <span class="hlt">MODIS</span> era. More recently, a focus is on stitching the <span class="hlt">MODIS</span> aerosol product into the "climate data record" (CDR) for global aerosol, determining whether the product has sufficient length, consistency and continuity to determine climate variability and change</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003GeoRL..30.2095W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003GeoRL..30.2095W"><span id="translatedtitle">Intercomparison between <span class="hlt">satellite</span>-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Jun; Christopher, Sundar A.</p> <p>2003-11-01</p> <p>We explore the relationship between column aerosol optical thickness (AOT) derived from the Moderate Resolution Imaging SpectroRadiometer (<span class="hlt">MODIS</span>) on the Terra/<span class="hlt">Aqua</span> <span class="hlt">satellites</span> and hourly fine particulate mass (PM2.5) measured at the surface at seven locations in Jefferson county, Alabama for 2002. Results indicate that there is a good correlation between the <span class="hlt">satellite</span>-derived AOT and PM2.5 (linear correlation coefficient, R = 0.7) indicating that most of the aerosols are in the well-mixed lower boundary layer during the <span class="hlt">satellite</span> overpass times. There is excellent agreement between the monthly mean PM2.5 and <span class="hlt">MODIS</span> AOT (R > 0.9), with maximum values during the summer months due to enhanced photolysis. The PM2.5 has a distinct diurnal signature with maxima in the early morning (6:00 ~ 8:00AM) due to increased traffic flow and restricted mixing depths during these hours. Using simple empirical linear relationships derived between the <span class="hlt">MODIS</span> AOT and 24hr mean PM2.5 we show that the <span class="hlt">MODIS</span> AOT can be used quantitatively to estimate air quality categories as defined by the U.S. Environmental Protection Agency (EPA) with an accuracy of more than 90% in cloud-free conditions. We discuss the factors that affect the correlation between <span class="hlt">satellite</span>-derived AOT and PM2.5 mass, and emphasize that more research is needed before applying these methods and results over other areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9876E..2AK','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9876E..2AK"><span id="translatedtitle">Comparison of INSAT-3D AOD over Indian region with <span class="hlt">satellite</span>- and ground-based measurements: a data assimilation perspective</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kumar, Sumit; George, John P.; Sreevathsa, M. N. Raghavendra; Indira Rani, S.</p> <p>2016-05-01</p> <p>This paper aims at comparing the INSAT-3D AOD with other space based observations over the continental regions. INSAT-3D launched in 2013 is an advanced geostationary weather <span class="hlt">satellite</span> of India at 82° East longitude provides Aerosol Optical Depth (AOD) observations at 650 nm over both land and ocean. The level-3 daily AOD measurements from <span class="hlt">MODIS</span> (both <span class="hlt">Aqua</span> and Terra) and MISR are used for comparison with that from INSAT-3D. This work is applied during premonsoon season of 2015. Overall statistical scores and systematic errors are compared to characterize various error sources. Our study indicates that significant differences exist between different aerosol observations which may be partly due to retrieval algorithm, sensor configurations and temporal sampling. Comparison of INSAT observed AOD shows less bias towards MISR and <span class="hlt">MODIS</span>-Terra observed AOD than with <span class="hlt">MODIS-Aqua</span>. The INSAT observations over oceanic region have better correlation, minimum bias and rmse than land region. Overall, the mean bias of the dataset is ±0.05, with a root mean square error of 0.22, but these errors are also found highly dependent on geographical region. Additionally, we compared INSAT 660 nm AOD with two AERONET ground stations. The comparison of INSAT with different observations shows that the retrieved AOD is closer to the ground-based data than the MISR and <span class="hlt">MODIS</span> AOD.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C21C0629J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C21C0629J"><span id="translatedtitle"><span class="hlt">MODIS</span> Data at the National Snow and Ice Data Center: Improvements for Collection 6</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Johnston, T.; Fowler, D. K.; McAllister, M.; Hall, D. K.; Riggs, G. A.</p> <p>2012-12-01</p> <p>For more than a decade, the National Snow and Ice Data Center (NSIDC) has archived and distributed snow cover and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments, onboard NASA's Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span>. As the <span class="hlt">MODIS</span> science team studies and refines the algorithms that generate these products, the Earth Observing System Data and Information System (EOSDIS) periodically reprocesses an entire collection of <span class="hlt">MODIS</span> data and produces a new suite of products incorporating the latest enhancements. Collection 6 represents the next revision to NSIDC's <span class="hlt">MODIS</span> archive, mainly affecting the snow-cover products. Based on scores of journal papers and workshop proceedings, Collection 6 specifically addresses the needs of the <span class="hlt">MODIS</span> science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps. Although <span class="hlt">MODIS</span> snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered region, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Finally, Collection 6 introduces new <span class="hlt">MODIS</span> snow products, including a daily climate modeling-grid, cloud gap-filled (CGF) snow-cover map. The CGF algorithm generates cloud-free maps by using the most recent clear observation of the surface when the current day is cloudy, and tracks cloud persistence to account for uncertainties created by the age of a snow observation. By considering prior days, the CGF dramatically increases the number of observable grid cells and can potentially improve the accuracy of other snow-cover products</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A14C..02H&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A14C..02H&link_type=ABSTRACT"><span id="translatedtitle">Extending <span class="hlt">MODIS</span> Cloud Top and Infrared Phase Climate Records with VIIRS and CrIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heidinger, A. K.; Platnick, S. E.; Ackerman, S. A.; Holz, R.; Meyer, K.; Frey, R.; Wind, G.; Li, Y.; Botambekov, D.</p> <p>2015-12-01</p> <p>The <span class="hlt">MODIS</span> imagers on the NASA EOS Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> have generated accurate and well-used cloud climate data records for 15 years. Both missions are expected to continue until the end of this decade and perhaps beyond. The Visible and Infrared Imaging Radiometer Suite (VIIRS) imagers on the Suomi-NPP (SNPP) mission (launched in October 2011) and future NOAA Joint Polar <span class="hlt">Satellite</span> System (JPSS) platforms are the successors for imager-based cloud climate records from polar orbiting <span class="hlt">satellites</span> after <span class="hlt">MODIS</span>. To ensure product continuity across a broad suite of EOS products, NASA has funded a SNPP science team to develop EOS-like algorithms that can be use with SNPP and JPSS observations, including two teams to work on cloud products. Cloud data record continuity between <span class="hlt">MODIS</span> and VIIRS is particularly challenging due to the lack of VIIRS CO2-slicing channels, which reduces information content for cloud detection and cloud-top property products, as well as down-stream cloud optical products that rely on both. Here we report on our approach to providing continuity specifically for the <span class="hlt">MODIS</span>/VIIRS cloud-top and infrared-derived thermodynamic phase products by combining elements of the NASA <span class="hlt">MODIS</span> science team (MOD) and the NOAA Algorithm Working Group (AWG) algorithms. The combined approach is referred to as the MODAWG processing package. In collaboration with the NASA Atmospheric SIPS located at the University of Wisconsin Space Science and Engineering Center, the MODAWG code has been exercised on one year of SNPP VIIRS data. In addition to cloud-top and phase, MODAWG provides a full suite of cloud products that are physically consistent with <span class="hlt">MODIS</span> and have a similar data format. Further, the SIPS has developed tools to allow use of Cross-track Infrared Sounder (CrIS) observations in the MODAWG processing that can ameliorate the loss of the CO2 absorption channels on VIIRS. Examples will be given that demonstrate the positive impact that the CrIS data can provide</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMED43C..04G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMED43C..04G"><span id="translatedtitle">SatCam: A mobile application for coordinated ground/<span class="hlt">satellite</span> observation of clouds and validation of <span class="hlt">satellite</span>-derived cloud mask products.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gumley, L.; Parker, D.; Flynn, B.; Holz, R.; Marais, W.</p> <p>2011-12-01</p> <p>SatCam is an application for iOS devices that allows users to collect observations of local cloud and surface conditions in coordination with an overpass of the Terra, <span class="hlt">Aqua</span>, or NPP <span class="hlt">satellites</span>. SatCam allows users to acquire images of sky conditions and ground conditions at their location anywhere in the world using the built-in iPhone or iPod Touch camera at the same time that the <span class="hlt">satellite</span> is passing overhead and viewing their location. Immediately after the sky and ground observations are acquired, the application asks the user to rate the level of cloudiness in the sky (Completely Clear, Mostly Clear, Partly Cloudy, Overcast). For the ground observation, the user selects their assessment of the surface conditions (Urban, Green Vegetation, Brown Vegetation, Desert, Snow, Water). The sky condition and surface condition selections are stored along with the date, time, and geographic location for the images, and the images are uploaded to a central server. When the <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span>) or VIIRS (NPP) imagery acquired over the user location becomes available, a <span class="hlt">MODIS</span> or VIIRS true color image centered at the user's location is delivered back to the SatCam application on the user's iOS device. SSEC also proposes to develop a community driven SatCam website where users can share their observations and assessments of <span class="hlt">satellite</span> cloud products in a collaborative environment. SSEC is developing a server side data analysis system to ingest the SatCam user observations, apply quality control, analyze the sky images for cloud cover, and collocate the observations with <span class="hlt">MODIS</span> and VIIRS <span class="hlt">satellite</span> products (e.g., cloud mask). For each observation that is collocated with a <span class="hlt">satellite</span> observation, the server will determine whether the user scored a "hit", meaning their sky observation and sky assessment matched the automated cloud mask obtained from the <span class="hlt">satellite</span> observation. The hit rate will be an objective assessment of the accuracy of the user's sky observations. Users with</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150001342','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150001342"><span id="translatedtitle">OMMYDCLD: a New A-train Cloud Product that Co-locates OMI and <span class="hlt">MODIS</span> Cloud and Radiance Parameters onto the OMI Footprint</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fisher, Brad; Joiner, Joanna; Vasilkov, Alexander; Veefkind, Pepijn; Platnick, Steven; Wind, Galina</p> <p>2014-01-01</p> <p>Clouds cover approximately 60% of the earth's surface. When obscuring the <span class="hlt">satellite</span>'s field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing <span class="hlt">satellites</span>. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing <span class="hlt">satellites</span> in the NASA A-Train: Aura/OMI and <span class="hlt">Aqua/MODIS</span>. OMMYDCLD co-locates high resolution cloud and radiance information from <span class="hlt">MODIS</span> onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for <span class="hlt">MODIS</span> scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016FrEaS...4...43S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016FrEaS...4...43S"><span id="translatedtitle">Inter-annual and geographical variations in the extent of bare ice and dark ice on the Greenland ice sheet derived from <span class="hlt">MODIS</span> <span class="hlt">satellite</span> images</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shimada, Rigen; Takeuchi, Nozomu; Aoki, Teruo</p> <p>2016-04-01</p> <p>Areas of dark ice have appeared on the Greenland ice sheet every summer in recent years. These are likely to have a great impact on the mass balance of the ice sheet because of their low albedo. We report annual and geographical variations in the bare ice and dark ice areas that appeared on the Greenland Ice Sheet from 2000 to 2014 by using <span class="hlt">MODIS</span> <span class="hlt">satellite</span> images. The July monthly mean of the extent of bare ice showed a positive trend over these 15 years, and large annual variability ranging from 89,975 km2 to 279,075 km2, 5% and 16% of the entire ice sheet, respectively. The extent of dark ice also showed a positive trend and varied annually, ranging from 3,575 km2 to 26,975 km2, 4% and 10% of the bare ice extent. These areas are geographically varied, and their expansion is the greatest on the western side, particularly the southwestern side of the ice sheet. The bare ice extent correlates strongly with the monthly mean air temperature in July, suggesting that the extent was determined by snow melt. The dark ice extent also correlates with the air temperature; however, the correlation is weaker. The dark ice extent further correlates negatively with solar radiation. This suggests that the extent of dark ice is not only controlled by snow melt on the ice, but also by changes in the surface structures of the bare ice surface, such as cryoconite holes, which are associated with impurities appearing on the ice surface.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1112835C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1112835C&link_type=ABSTRACT"><span id="translatedtitle">Regional scale net radiation estimation by means of Landsat and TERRA/<span class="hlt">AQUA</span> imagery and GIS modeling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Ninyerola, M.; Pons, X.; Llorens, P.; Poyatos, R.</p> <p>2009-04-01</p> <p> balance among the net shortwave radiation Rn and the net longwave radiation. In addition, two types of approaches have been carried out for its determination: the estimation of the variables implied in the calculation of Rn at daily level (Rndl); and the calculation of the Rn at the time of <span class="hlt">satellite</span> pass (Rni) and its subsequent conversion to daily Rn by means of the Rn ratio. Net shortwave radiation has been computed by means of albedo and a solar radiation model obtained through a DEM following the methodology of Pons and Ninyerola (2008).This methodology takes into account the position of the Sun, the angles of incidence, the projected shadows and the distance from the Earth to the Sun at one hour intervals. The diffuse radiation is estimated from the direct radiaton and the exoatmospheric direct solar irradiance is estimated with the Page equation (1986) and fitted by Baldasano et al. (1994). Net longwave radiation has been calculated through land surface temperature and emissivity, atmospheric water vapour and air temperature. Air temperature has been modeled by means of multiple regression analysis and GIS interpolation using ground meteorological stations. Finally, air emissivity has been computed using air temperature models and atmospheric water vapour following the methodology developed by Dilley and O'Brien (1998). Finally, models have been validated through a set of 13 ground meteorological standard stations and an experimental station placed in a Mediterranean mountain area over a Pinus sylvestris stand. Obtained results show a mean RMSE of 20 W m-2 in the case of Landsat and a mean RMSE of 22 W m-2 in the case of TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span>, being these results in agreement with other published results, but also offering better RMSE in some cases. Keywords: Net radiation, Landsat, TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span>, GIS modeling, regional scale.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/6541267','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/6541267"><span id="translatedtitle"><span class="hlt">Satellites</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Burns, J.A.; Matthews, M.S.</p> <p>1986-01-01</p> <p>The present work is based on a conference: Natural <span class="hlt">Satellites</span>, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of <span class="hlt">satellites</span>, protosatellite swarms, the tectonics of icy <span class="hlt">satellites</span>, the physical characteristics of <span class="hlt">satellite</span> surfaces, and the interactions of planetary magnetospheres with icy <span class="hlt">satellite</span> surfaces. Other topics include the surface composition of natural <span class="hlt">satellites</span>, the cratering of planetary <span class="hlt">satellites</span>, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the <span class="hlt">satellites</span> of Saturn, small <span class="hlt">satellites</span>, <span class="hlt">satellites</span> of Uranus and Neptune, and the Pluto-Charon system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.C31D0544K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.C31D0544K"><span id="translatedtitle">Surface Melt Magnitude Retrieval Over Ross Ice Shelf, Antarctica Using Coupled <span class="hlt">MODIS</span> Optical and Thermal <span class="hlt">Satellite</span> Measurements During the 2002-03 Melt Season</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karmosky, C. C.; Lampkin, D. J.</p> <p>2008-12-01</p> <p>Ice shelf stability is of crucial importance in the Antarctic because shelves serve as buttresses to glacial ice advancing from the Antarctic Ice Sheet. Surface melt has been increasing over recent years, especially over the Antarctic Peninsula, contributing to disintegration of shelves such as Larsen. Unfortunately, we are not realistically able to quantify surface snowmelt from ground-based methods because there is sparse coverage in automatic weather stations. <span class="hlt">Satellite</span> based assessments of melt from passive microwave systems are limited in that they only provide an indication of melt occurrence and have coarse resolution. Though this is useful in tracking the duration of melt, melt amount of magnitude is still unknown. Coupled optical/thermal surface measurements from <span class="hlt">MODIS</span> were calibrated by estimates of liquid water fraction (LWF) in the upper 1cm of the firn derived from a one-dimensional thermal snowmelt model (SNTHERM). SNTHERM was forced by hourly meteorological data from automatic weather station data at reference sites spanning a range of melt conditions across the Ross Ice Shelf during a particularly intense melt season. Melt intensities or LWF were derived for <span class="hlt">satellite</span> composite periods covering the Antarctic summer months at a 4km resolution over the entire Ross Ice Shelf, ranging from 0-2 percent LWF in early December to areas along the coast with upwards of 10 percent LWF during the time of peak surface melt. Spatial and temporal variations in the amount of surface melt are seen to be related to both katabatic wind strength and wind shifts due to the progression of cyclones along the circumpolar vortex. Sea ice concentration along the ice shelf front, specifically the formation of polynyas, are also thought to be driving factors for surface melt as latent and sensible heat fluxes increase by one to three orders of magnitude as polynyas form. A future application of surface melt mapping using this empirical retrieval model is to determine melt</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSM.A51A..03S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSM.A51A..03S"><span id="translatedtitle">A basin-wide assessment of the GOES and <span class="hlt">MODIS</span> active fire products for the Brazilian Amazon</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schroeder, W.; Csiszar, I.; Prins, E.; Schmidt, C.; Setzer, A.; Longo, K.; Freitas, S.; Morisette, J.; Brunner, J.</p> <p>2007-05-01</p> <p>This LBE-ECO Phase III study is designed to assess the performance of active fire products which have been used to delineate the fire dynamics in the Brazilian Amazon basin and which are routinely used to feed biomass burning emissions models for the region. The initial analyses are focused primarily on the creation of a validated long term (1995-present) record for the WF-ABBA active fire product using GOES East geostationary <span class="hlt">satellite</span> data. Active fire masks were produced for 285 ASTER and ETM+ scenes distributed across the Brazilian Amazon representing our ground truth for the validation of the WF-ABBA. For comparison purposes we also included the <span class="hlt">MODIS</span>/Terra "Thermal Anomalies" (MOD14) data in our analyses. Approximately 14,500 fire pixels were analyzed for the GOES data and 7,300 fire pixels were analyzed for the <span class="hlt">MODIS</span> data. We found that at the 50% detection probability mark (p<0.001), the GOES fire product requires four times more active fire area than it is necessary for <span class="hlt">MODIS</span> to achieve the same probability of detection. However, the higher observation frequency of GOES resulted in less than 40% omission error compared to 80% with <span class="hlt">MODIS</span>. Basin-wide commission errors for <span class="hlt">MODIS</span> and GOES were approximately 15 and 17%, respectively. Commission errors were higher over areas of active deforestation due to the high thermal contrast between the deforested sites and the adjacent green forests which can cause multiple false detections. Burnt area estimates were also produced based on ETM+ data to assess the average burnt area size associated with the coarse resolution active fire data above. For this application over 2,700 burn scar polygons were digitized representing all major biomass burning regions across the Brazilian Amazon. Burn scar polygons were then intersected with the <span class="hlt">MODIS</span>/Terra and <span class="hlt">Aqua</span> active fire data. 50% of all polygons containing active fires in the <span class="hlt">MODIS</span> imagery showed a burnt area size larger than 300ha. Burnt areas of less than 100ha in size</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014SPIE.9261E..0QS&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014SPIE.9261E..0QS&link_type=ABSTRACT"><span id="translatedtitle">Features of <span class="hlt">satellite</span> remote sensing of seawater biological parameters in the eastern part of Russian Arctic waters</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Salyuk, Pavel A.; Bukin, Oleg A.; Stepochkin, Igor E.; Sokolova, Ekaterina B.; Akmaykin, Denis</p> <p>2014-11-01</p> <p>Comparative analysis of chlorophyll-a concentrations obtained using flow fluorometric measurements carried out on the board vessel, and chlorophyll-a concentrations calculated by <span class="hlt">MODIS-Aqua</span> and VIIRS <span class="hlt">satellite</span> data of ocean color was conducted. The ship data were adjusted to standard spectrophotometric measurements and vertical depth distribution of phytoplankton. Investigations were done in the Bering and Chukchi Seas, De Long Strait in August 2013. In waters of the Russian Eastern Arctic <span class="hlt">satellite</span> radiometers versus ship-borne measurements of chlorophyll-a concentration were overestimated, which was associated with relatively high content of colored dissolved organic matter at upper layers. In De Long Straight <span class="hlt">satellite</span> estimation didn't reflect overall viewing on the depth integrated chlorophyll-a concentration, as in this area the bulk of the phytoplankton with chlorophyll-a concentration around 10-20 mg/m3 was located in the depth layer with 3-5% illumination relative to the surface light level. In the analyzed waters VIIRS gave more accurate measurements of chlorophyll-a concentration as compared to using <span class="hlt">MODIS-Aqua</span> <span class="hlt">satellite</span> data with processing procedures № 2013.1.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1112471Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1112471Z"><span id="translatedtitle">Comparasion of Cloud Cover restituted by POLDER and <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.</p> <p>2009-04-01</p> <p>PARASOL and <span class="hlt">AQUA</span> are two sun-synchronous orbit <span class="hlt">satellites</span> in the queue of A-Train <span class="hlt">satellites</span> that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and <span class="hlt">MODIS</span> provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and <span class="hlt">MODIS</span> level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and <span class="hlt">MODIS</span>. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, <span class="hlt">MODIS</span> can better detect the fractional clouds thus explaining as one part</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110020728','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110020728"><span id="translatedtitle"><span class="hlt">MODIS</span> On-orbit Calibration Uncertainty Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chiang, Vincent; Sun, Junqiang; Wu, Aisheng</p> <p>2011-01-01</p> <p><span class="hlt">MODIS</span> has 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, <span class="hlt">MODIS</span> was developed with very stringent calibration uncertainty requirements. As a result, <span class="hlt">MODIS</span> was designed and built with a set of on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated. In terms of its calibration traceability, <span class="hlt">MODIS</span> RSB calibration is reflectance based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of <span class="hlt">MODIS</span> calibration methodologies and an in-depth analysis of its on-orbit calibration uncertainties. Also discussed in this paper are uncertainty contributions from individual components and differences due to Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument characteristics and on-orbit performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015385','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015385"><span id="translatedtitle"><span class="hlt">MODIS</span> On-Orbit Calibration and Lessons Learned</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Jack</p> <p>2012-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is a key instrument for NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> missions. Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for more than 12 and 10 years, respectively, and generated an unprecedented amount of data products for the science and user community over a wide range of applications. <span class="hlt">MODIS</span> was developed with improved design and stringent calibration requirements over its heritage sensors in order . to extend and enhance their long-term data records. Its follow-on instrument, the Visible/Infrared Imager Radiometer Suite (VIIRS), was launched on-board the Suomi National Polar-orbiting Partnership (NPP) spacecraft October 28, 2011. <span class="hlt">MODIS</span> collects data in 36 spectral bands, covering wavelengths from 0.41 to 14.S!Jlll, and at 250m, SOOm, and lkm spatial resolutions (nadir). <span class="hlt">MODIS</span> on-orbit calibration is provided by a set of onboard calibrators (OBC), including a solar diffuser (SO), a solar diffuser stability monitor (SDSM), a blackbody (BB), and a spectroradiometric calibration assembly (SRCA). In addition to the onboard calibrators, regular lunar observations are made by both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> to track their calibration stability in the reflective solar region. This tutorial session provides an overview of <span class="hlt">MODIS</span> on-orbit calibration and characterization methodologies. It discusses challenging issues and lessons learned from sensor design, operation, calibration, and inter-comparisons. Examples of instrument on-orbit performance are illustrated with a focus on the improvements made based on various lessons learned. It is expected that <span class="hlt">MODIS</span> experience and lessons will continue to provide valuable information for future earth observing missions/sensors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSM.B41B..05D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSM.B41B..05D"><span id="translatedtitle">Mapping the Distribution of Cloud Forests Using <span class="hlt">MODIS</span> Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Douglas, M. W.; Mejia, J.; Murillo, J.; Orozco, R.</p> <p>2007-05-01</p> <p>Tropical cloud forests - those forests that are frequently immersed in clouds or otherwise very humid, are extremely difficult to map from the ground, and are not easily distinguished in <span class="hlt">satellite</span> imagery from other forest types, but they have a very different flora and fauna than lowland rainforest. Cloud forests, although found in many parts of the tropics, have a very restricted vertical extent and thus are also restricted horizontally. As a result, they are subject to both human disturbance (coffee growing for example) and the effects of possible climate change. Motivated by a desire to seek meteorological explanations for the distribution of cloud forests, we have begun to map cloudiness using <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> visible imagery. This imagery, at ~1030 LT and 1330 LT, is an approximation for mid-day cloudiness. In tropical regions the amount of mid-day cloudiness strongly controls the shortwave radiation and thus the potential for evaporation (and aridity). We have mapped cloudiness using a simple algorithm that distinguishes between the cloud-free background brightness and the generally more reflective clouds to separate clouds from the underlying background. A major advantage of <span class="hlt">MODIS</span> imagery over many other sources of <span class="hlt">satellite</span> imagery is its high spatial resolution (~250m). This, coupled with precisely navigated images, means that detailed maps of cloudiness can be produced. The cloudiness maps can then be related to the underlying topography to further refine the location of the cloud forests. An advantage of this technique is that we are mapping the potential cloud forest, based on cloudiness, rather than the actual cloud forest, which are commonly based on forest estimates from <span class="hlt">satellite</span> and digital elevation data. We do not derive precipitation, only estimates of daytime cloudiness. Although only a few years of <span class="hlt">MODIS</span> imagery has been used in our studies, we will show that this is sufficient to describe the climatology of cloudiness with acceptable</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20050156603&hterms=effect+climatic+changes+db&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Deffect%2Bclimatic%2Bchanges%2Bdb','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20050156603&hterms=effect+climatic+changes+db&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Deffect%2Bclimatic%2Bchanges%2Bdb"><span id="translatedtitle"><span class="hlt">MODIS</span> Direct Broadcast and Remote Sensing Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tsay, Si-Chee</p> <p>2004-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and <span class="hlt">Aqua</span> spacecraft on May 4, 2002. <span class="hlt">MODIS</span> scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the <span class="hlt">MODIS</span> measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/<span class="hlt">Aqua-MODIS</span> Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using <span class="hlt">MODIS</span> data, focusing primarily on the <span class="hlt">MODIS</span> cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20000105141&hterms=bottleneck&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dbottleneck','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20000105141&hterms=bottleneck&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dbottleneck"><span id="translatedtitle">Production and Distribution of Global Products From <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Masuoka, Edward; Smith, David E. (Technical Monitor)</p> <p>2000-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer was launched on the EOS Terra spacecraft in December 1999 and will also fly on EOS <span class="hlt">Aqua</span> in December 2000. With 36 spectral bands from the visible through thermal infrared and spatial resolution of 250m to 1 kilometer, each <span class="hlt">MODIS</span> instrument will image the entire Earth surface in 2 days. This paper traces the flow of <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> products. As most components of the ground system are severely limited in their capacity to distribute <span class="hlt">MODIS</span> products, it also describes the key characteristics of <span class="hlt">MODIS</span> products and their metadata that allow a user to optimize their selection of products given anticipate bottlenecks in distribution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC41C0824S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC41C0824S"><span id="translatedtitle">Accessing Recent Trend of Land Surface Temperature from <span class="hlt">Satellite</span> Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shen, S.; Leptoukh, G. G.; Romanov, P.</p> <p>2011-12-01</p> <p>Land surface temperature (LST) is an important element to measure the state of the terrestrial ecosystems and to study the surface energy budgets. In support of the land cover/land use change related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected the global monthly LST measured by <span class="hlt">MODIS</span> since the beginning of the missions. The <span class="hlt">MODIS</span> LST time series have ~11 years of data from Terra since 2000 and ~9 years of data from <span class="hlt">Aqua</span> since 2002, which makes possible to study the recent climate, such as trend and variability. In this study, monthly climatology from two <span class="hlt">satellite</span> platforms are calculated and compared. The spatial patterns of LST trends are accessed, focusing on the Asian Monsoon region. Furthermore, the <span class="hlt">MODIS</span> LST trends are compared with the skin temperature trend from the NASA's atmospheric assimilation model, MERRA (MODERN ERA RETROSPECTIVE-ANALYSIS FOR RESEARCH AND APPLICATIONS), which has longer data record since 1979. The calculated climatology and anomaly of <span class="hlt">MODIS</span> LST will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy access and use by scientists and general public.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009SPIE.7452E..0KX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009SPIE.7452E..0KX"><span id="translatedtitle"><span class="hlt">MODIS</span> solar reflective calibration traceability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong; Butler, Jim</p> <p>2009-08-01</p> <p>Long-term climate data records often consist of observations made by multiple sensors. It is, therefore, extremely important to have instrument overlap, to be able to track instrument stability, to quantify measurement uncertainties, and to establish an absolute measurement scale traceable to the International System of Units (SI). The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is a key instrument for both the Terra and <span class="hlt">Aqua</span> missions, which were launched in December 1999 and May 2002, respectively. It has 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2μm and observes the Earth at three nadir spatial resolutions: 0.25km, 0.5km, and 1km. <span class="hlt">MODIS</span> RSB on-orbit calibration is reflectance based with reference to the bi-directional reflectance factor (BRF) of its on-board solar diffuser (SD). The SD BRF characterization was made pre-launch by the instrument vendor using reference samples traceable directly to the National Institute of Standards and Technology (NIST). On-orbit SD reflectance degradation is tracked by an on-board solar diffuser stability monitor (SDSM). This paper provides details of this calibration chain, from pre-launch to on-orbit operation, and associated uncertainty assessments. Using <span class="hlt">MODIS</span> as an example, this paper also discusses challenges and key design requirements for future missions developed for accurate climate studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110006353','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110006353"><span id="translatedtitle"><span class="hlt">MODIS</span> Solar Reflective Calibration Traceability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Butler, Jim</p> <p>2009-01-01</p> <p>Long-term climate data records often consist of observations made by multiple sensors. It is, therefore, extremely important to have instrument overlap, to be able to track instrument stability, to quantify, measurement uncertainties, and to establish absolute scale traceable to the International System of Units (SI). The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is a key instrument for both the Terra and <span class="hlt">Aqua</span> missions, which were launched in December 1999 and May 2002, respectively. It has 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers and observes the Earth at three nadir spatial resolutions: 0.25km, 0.5km, and 1km. <span class="hlt">MODIS</span> RSB on-orbit calibration is reflectance based with reference to the bidirectional reflectance factor (BRF) of its on-board solar diffuser (SD). The SD BRF characterization was made pre-launch by the instrument vendor using reference samples traceable directly to the National Institute of Standards and Technology (NIST). On-orbit SD reflectance degradation is tracked by an on-board solar diffuser monitor (SDSM). This paper provides details of this calibration chain, from prelaunch to on-orbit operation, and associated uncertainty assessments. Using <span class="hlt">MODIS</span> as an example, this paper also discusses challenges and key design requirements for future missions developed for accurate climate studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008655','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008655"><span id="translatedtitle">A Real-Time <span class="hlt">MODIS</span> Vegetation Composite for Land Surface Models and Short-Term Forecasting</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.</p> <p>2011-01-01</p> <p>The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor aboard the polar orbiting NASA <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span>, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the <span class="hlt">MODIS</span> NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time <span class="hlt">satellite</span> observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the <span class="hlt">MODIS</span> real-time GVF data. This presentation will describe the methodology used to develop the 1-km <span class="hlt">MODIS</span> NDVI composites and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001471&hterms=colder+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcolder%2Bnear%2Bocean','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001471&hterms=colder+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcolder%2Bnear%2Bocean"><span id="translatedtitle"><span class="hlt">MODIS</span> Global Sea Surface Temperature</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>Every day the Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) measures sea surface temperature over the entire globe with high accuracy. This false-color image shows a one-month composite for May 2001. Red and yellow indicates warmer temperatures, green is an intermediate value, while blues and then purples are progressively colder values. The new <span class="hlt">MODIS</span> sea surface temperature product will be particularly useful in studies of temperature anomalies, such as El Nino, as well as research into how air-sea interactions drive changes in weather and climate patterns. In the high resolution image, notice the amazing detail in some of the regional current patterns. For instance, notice the cold water currents that move from Antarctica northward along South America's west coast. These cold, deep waters upwell along an equatorial swath around and to the west of the Galapagos Islands. Note the warm, wide currents of the Gulf Stream moving up the United States' east coast, carrying Caribbean warmth toward Newfoundland and across the Atlantic toward Western Europe. Note the warm tongue of water extending from Africa's east coast to well south of the Cape of Good Hope. <span class="hlt">MODIS</span> was launched in December 1999 aboard NASA's Terra <span class="hlt">satellite</span>. For more details on this and other <span class="hlt">MODIS</span> data products, please see NASA Unveils Spectacular Suite of New Global Data Products from <span class="hlt">MODIS</span>. Image courtesy <span class="hlt">MODIS</span> Ocean Group, NASA GSFC, and the University of Miami</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B33C0193L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B33C0193L"><span id="translatedtitle">Mapping Crop Cycles in China Using <span class="hlt">MODIS</span>-EVI Time Series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, L.; Friedl, M. A.; Xin, Q.; Gray, J. M.; Pan, Y.; Frolking, S. E.</p> <p>2014-12-01</p> <p>As the Earth's population continues to grow and demand for food increases, multiple cropping is an effective way to increase crop production. Cropping intensity, which we define here as the number of cropping cycles per year, is an important dimension of land use that is strongly influences water demand and agricultural production. <span class="hlt">Satellite</span> data provide global land cover maps with indispensable information regarding areal extent of global croplands and its distribution. However, the land use information such as cropping intensity is not routinely provided by global land cover products from instruments such as <span class="hlt">MODIS</span>, because mapping this information from remote sensing is challenging. We present a straight forward but efficient algorithm for automated mapping of agricultural intensity over large geographic regions using 8-day <span class="hlt">MODIS</span> EVI time series data derived from Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> surface reflectance products. The proposed algorithm first applies an adaptive Savitzky-Golay filter to smooth Enhanced Vegetation Index (EVI) time series derived from <span class="hlt">MODIS</span> surface reflectance data, and then uses an iterative moving-window methodology to identify cropping cycles from the smoothed EVI time series. Comparison of results from our algorithm with national survey data at both the provincial and prefectural level in China show that the algorithm provides estimates of gross sown area that agree well with inventory data. Accuracy assessment using data generated by expert classification of randomly selected pixel samples indicates an overall accuracy of 91.0% for three agricultural intensity classes. More generally, the algorithm shows significant potential to automatically estimate reliable cropping intensity information in support of large-scale studies of agricultural land use and land cover dynamics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..120.4132C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..120.4132C"><span id="translatedtitle">Frequency and causes of failed <span class="hlt">MODIS</span> cloud property retrievals for liquid phase clouds over global oceans</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; -Labonnote, Laurent C.; Cornet, Céline; Riedi, Jerome; Holz, Robert E.</p> <p>2015-05-01</p> <p>Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) retrieves cloud droplet effective radius (r_e) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r_e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed <span class="hlt">MODIS</span> retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 μm and 2.1 μm <span class="hlt">MODIS</span> channel combination has an overall failure rate of about 16% (10% for the 0.86 μm and 3.7 μm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the "r_e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the "r_e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-<span class="hlt">satellite</span> viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r_e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070034809&hterms=html&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dhtml','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070034809&hterms=html&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dhtml"><span id="translatedtitle">Generating a Long-Term Land Data Record from the AVHRR and <span class="hlt">MODIS</span> Instruments</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pedelty, Jeffrey; Devadiga, Sadashiva; Masuoka, Edward; Brown, Molly; Pinzon, Jorge; Tucker, Compton; Vermote, Eric; Prince, Stephen; Nagol, Jyotheshwar; Justice, Christopher; Roy, David; Ju, Junchang; Schaaf, Crystal; Liu, Jicheng; Privette, Jeffrey; Pincheiro, Ana</p> <p>2007-01-01</p> <p>The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and <span class="hlt">MODIS</span> instruments for land climate studies. The project will create daily surface reflectance and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for <span class="hlt">MODIS</span> products from EOS Terra and <span class="hlt">Aqua</span>. Higher order products such as burned area, land surface temperature, albedo, bidirectional reflectance distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA <span class="hlt">satellites</span> by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in <span class="hlt">MODIS</span> processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface reflectance product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for <span class="hlt">MODIS</span> land product quality assessment. The land surface reflectance products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AGUFM.A31K..08M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AGUFM.A31K..08M&link_type=ABSTRACT"><span id="translatedtitle">Bias Correction of high resolution <span class="hlt">MODIS</span> Aerosol Optical Depth in urban areas using the Dragon AERONET Network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malakar, N. K.; Atia, A.; Gross, B.; Moshary, F.; Ahmed, S. A.; Lary, D. J.</p> <p>2013-12-01</p> <p>Aerosol optical depth (AOD) is widely used parameter used to quantify aerosol abundance. <span class="hlt">Satellite</span> retrievals of aerosols over land is fundamentally more complex than aerosol retrieval over oceans. Due to wide coverage and the extensive validation the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), on board the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> is the workhorse instrument used to retrieve AOD from space. However, <span class="hlt">satellite</span> algorithms of AOD are extremely complex and depends strongly on sun/view geometry, spectral surface albedo, aerosol model assumptions and surface heterogeneity. This issue becomes even more severe when considering the new <span class="hlt">MODIS</span> 3 km aerosol retrieval products within version 6. To assess <span class="hlt">satellite</span> retrievals of these high resolution 3 km products, we use the summer 2011 Dragon AERONET data to assess accuracy as well as major retrieval bias that can occur in <span class="hlt">MODIS</span> measurements. In this study, we explore in detail the factors that can drive these biases statistically. As discussed above, our considers multiple conditions such as surface reflectivity at various wavelengths, solar and sensor zenith angles, the solar and sensor azimuth, scattering angles as well as meteorological factors and aerosol type (angstrom coefficient) etc which are used inputs are used to train neural network in regression mode to compensate for biases against the Dragon AERONET AOD values. In particular, we confirm the results of previous studies where the land cover (urban fraction) appears to be a strong factor in AOD bias and develop a NN estimator which includes land cover directly. The algorithm will be tested not only in the Baltimore/Washington area but assessed in the general North East US where urban biases in the NYC area have been previously identified.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20100034941&hterms=Wilcox&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DWilcox','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20100034941&hterms=Wilcox&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DWilcox"><span id="translatedtitle">Estimate of the Impact of Absorbing Aerosol Over Cloud on the <span class="hlt">MODIS</span> Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wilcox, Eric M.; Harshvardhan; Platnick, Steven</p> <p>2009-01-01</p> <p>Two independent <span class="hlt">satellite</span> retrievals of cloud liquid water path (LWP) from the NASA <span class="hlt">Aqua</span> <span class="hlt">satellite</span> are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the <span class="hlt">MODIS</span> retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the <span class="hlt">MODIS</span> tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. <span class="hlt">MODIS</span> LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and <span class="hlt">MODIS</span> LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura <span class="hlt">satellite</span>. The LWP difference (AMSR-E minus <span class="hlt">MODIS</span>) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean <span class="hlt">MODIS</span> LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70031513','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70031513"><span id="translatedtitle"><span class="hlt">MODIS</span> imagery as a tool for synoptic water quality assessments in the southern California coastal ocean</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Nezlin, N.P.; DiGiacomo, P.M.; Jones, B.H.; Reifel, K.M.; Warrick, J.A.; Johnson, S.C.; Mengel, M.J.</p> <p>2007-01-01</p> <p>The dynamics of rainstorm plumes in the coastal waters of southern California was studied during the Bight'03 Regional Water Quality Program surveys. Measurements of surface salinity and bacterial counts collected from research vessels were compared to <span class="hlt">MODIS-Aqua</span> <span class="hlt">satellite</span> imagery. The spectra of normalized water-leaving radiation (nLw) were different in plumes and ambient ocean waters, enabling plumes discrimination and plume area size assessments from remotely-sensed data. The plume/ocean nLw differences (i.e., plume optical signatures) were most evident during first days after the rainstorm over the San Pedro shelf and in the San Diego region and less evident in Santa Monica Bay, where suspended sediments concentration in discharged water was lower than in other regions. In the Ventura area, plumes contained more suspended sediments than in other regions, but the grid of ship-based stations covered only a small part of the freshwater plume and was insufficient to reveal the differences between the plume and ocean optical signatures. The accuracy of plume area assessments from <span class="hlt">satellite</span> imagery was not high (77% on average), seemingly because of inexactitude in <span class="hlt">satellite</span> data processing. Nevertheless, <span class="hlt">satellite</span> imagery is a useful tool for the estimation of the extent of polluted plumes, which is hardly achievable by contact methods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007SPIE.6680E..0TN','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007SPIE.6680E..0TN"><span id="translatedtitle"><span class="hlt">MODIS</span> imagery as a tool for synoptic water quality assessments in the southern California coastal ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nezlin, Nikolay P.; DiGiacomo, Paul M.; Jones, Burton H.; Reifel, Kristen M.; Warrick, Jonathan A.; Johnson, Scott C.; Mengel, Michael J.</p> <p>2007-09-01</p> <p>The dynamics of rainstorm plumes in the coastal waters of southern California was studied during the Bight'03 Regional Water Quality Program surveys. Measurements of surface salinity and bacterial counts collected from research vessels were compared to <span class="hlt">MODIS-Aqua</span> <span class="hlt">satellite</span> imagery. The spectra of normalized water-leaving radiation (nLw) were different in plumes and ambient ocean waters, enabling plumes discrimination and plume area size assessments from remotely-sensed data. The plume/ocean nLw differences (i.e., plume optical signatures) were most evident during first days after the rainstorm over the San Pedro shelf and in the San Diego region and less evident in Santa Monica Bay, where suspended sediments concentration in discharged water was lower than in other regions. In the Ventura area, plumes contained more suspended sediments than in other regions, but the grid of ship-based stations covered only a small part of the freshwater plume and was insufficient to reveal the differences between the plume and ocean optical signatures. The accuracy of plume area assessments from <span class="hlt">satellite</span> imagery was not high (77% on average), seemingly because of inexactitude in <span class="hlt">satellite</span> data processing. Nevertheless, <span class="hlt">satellite</span> imagery is a useful tool for the estimation of the extent of polluted plumes, which is hardly achievable by contact methods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSMOS23A..02N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSMOS23A..02N"><span id="translatedtitle"><span class="hlt">MODIS</span> imagery as a tool for water quality assessments in southern California coastal ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nezlin, N. P.; Digiacomo, P. M.; Jones, B. H.; Reifel, K. M.; Warrick, J. A.; Johnson, S. C.; Mengel, M.</p> <p>2007-05-01</p> <p>Stormwater plumes are main source of coastal pollution in southern California coastal waters. The data on surface salinity, concentrations of total suspended solids (TSS), colored dissolved organic matter (CDOM) and bacterial counts collected during the Bight'03 Regional Water Quality Program surveys in February 2004 and February-March 2005 were compared to <span class="hlt">MODIS-Aqua</span> <span class="hlt">satellite</span> imagery. The spectra of normalized water-leaving radiation (nLw) were different in plumes and in ambient ocean waters, enabling plumes discrimination and plume area size assessments from remotely-sensed data. The plume/ocean nLw differences (i.e., plume optical signatures) were most evident during first days after the rainstorm and less evident in the area where TSS concentration in discharged water was lower than in other regions. The accuracy of plume area assessments from <span class="hlt">satellite</span> imagery was not high (77% on average), seemingly because of inexactitude in <span class="hlt">satellite</span> data processing. In particular, the expected correlation between remotely-sensed CDOM absorption estimated by Lee's quasi-analytical algorithm (QAA) and CDOM concentrations in water column was often obscured by external factors including wind-driven sea state and phytoplankton blooms. Nevertheless, <span class="hlt">satellite</span> imagery is a useful tool for estimation of the extension of polluted plumes, which is hardly achievable by contact methods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20050123914&hterms=gis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dgis','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20050123914&hterms=gis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dgis"><span id="translatedtitle">NASA GES DISC DAAC <span class="hlt">Satellite</span> Data for GIS</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nickless, Darryl; Leptoukh, Gregory; Morahan, Michael; Pollack, Nathan; Savtchenko, Andrey; Teng, William</p> <p>2005-01-01</p> <p>NASA's Goddard Earth Science (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC) makes available a large and continually growing collection of spatially continuous global <span class="hlt">satellite</span> observations of environmental parameters. These products include those from the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) on both Terra and <span class="hlt">Aqua</span> platforms, and the Tropical Rainfall Measuring Mission (TRMM). These data products are well suited for use within Geographic Information Systems (GIS), as both backdrops to cartographic products as well as spatial analysis. However, data format, file size, and other issues have limited their widespread use by traditional GIS users. To address these data usability issues, the GES DISC DAAC recently updated tools and improved documentation of conversion procedures. In addition, the GES DISC DAAC has also been working with a major GIS software vendor to incorporate the ability to read the native Hierarchial Data Format (HDF), the format in which most of the NASA data is stored. The result is the enabling of GIS users to realize the benefit of GES DISC DAAC data without a substantial expenditure in resources to incorporate these data into their GIS. Several documents regarding the potential uses of GES DISC DAAC <span class="hlt">satellite</span> data in GIS have recently been created. These show the combinations of concurrent data from different <span class="hlt">satellite</span> products with traditional GIS vector products for given geographic areas. These map products include <span class="hlt">satellite</span> imagery of Hurricane Isabel and the California wildfires, and can be viewed at http://daac.gsfc.nasa.gov/<span class="hlt">MODIS</span>/GIS/.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007SPIE.6677E..0OX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007SPIE.6677E..0OX"><span id="translatedtitle">Characterization of <span class="hlt">MODIS</span> solar diffuser on-orbit degradation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, X.; Xie, X.; Angal, A.; Choi, J.; Sun, J.; Barnes, W. L.</p> <p>2007-09-01</p> <p><span class="hlt">MODIS</span> has 20 reflective solar bands (RSB) that are calibrated on-orbit using a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). The <span class="hlt">MODIS</span> SD bi-directional reflectance factor (BRF) was characterized pre-launch. Its on-orbit degradation is regularly monitored by the SDSM at wavelengths ranging from 0.41 to 0.94μm. During each SD/SDSM calibration event, the SDSM views alternately the sunlight directly through a fixed attenuation screen and the sunlight diffusely reflected from the SD panel. The time series of SDSM measurements (ratios of the SD view response to the Sun view response) is used to determine the SD BRF degradation at SDSM wavelengths. Since launch Terra <span class="hlt">MODIS</span> has operated for more than seven years and <span class="hlt">Aqua</span> for over five years. The SD panel on each <span class="hlt">MODIS</span> instrument has experienced noticeable degradation with the largest changes observed in the VIS spectral region. This paper provides a brief description of <span class="hlt">MODIS</span> RSB calibration methodology and SD/SDSM operational activities, and illustrates the SD on-orbit degradation results for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. It also discusses the impact on the SD degradation due to sensor operational activities and SD solar exposure time. <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> has been operated under nearly the same condition for more than five years. Its SD annual degradation rate is estimated to be 2.7% at 0.41μm, 1.7% at 0.47μm, and less than 1.0% at wavelengths above 0.53μm. Terra <span class="hlt">MODIS</span>, on the other hand, has experienced two different SD solar exposure conditions due to an SD door (SDD) operation related anomaly that occurred in May 2003 that had led to a decision to keep the SDD permanently at its "open" position. Prior to this event, Terra <span class="hlt">MODIS</span> SD degradation rates were very similar to <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. Since then its SD has experienced much faster degradation rates due to more frequent solar exposure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040031769&hterms=cloud+bases&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcloud%2Bbases','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040031769&hterms=cloud+bases&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcloud%2Bbases"><span id="translatedtitle">Global Multispectral Cloud Retrievals from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.</p> <p>2003-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and <span class="hlt">Aqua</span> spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for <span class="hlt">Aqua</span>. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the <span class="hlt">MODIS</span> atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and <span class="hlt">Aqua</span>, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26421659','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26421659"><span id="translatedtitle">Estimation of surface-level PM concentration from <span class="hlt">satellite</span> observation taking into account the aerosol vertical profiles and hygroscopicity.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kim, Kwanchul; Lee, Kwon H; Kim, Ji I; Noh, Youngmin; Shin, Dong H; Shin, Sung K; Lee, Dasom; Kim, Jhoon; Kim, Young J; Song, Chul H</p> <p>2016-01-01</p> <p>Surface-level PM10 distribution was estimated from the <span class="hlt">satellite</span> aerosol optical depth (AOD) products, taking the account of vertical profiles and hygroscopicity of aerosols over Jeju, Korea during March 2008 and October 2009. In this study, <span class="hlt">MODIS</span> AOD data from the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> were corrected with aerosol extinction profiles and relative humidity data. PBLH (Planetary Boundary Layer Height) was determined from MPLNET lidar-derived aerosol extinction coefficient profiles. Through statistical analysis, better agreement in correlation (R = 0.82) between the hourly PM10 concentration and hourly average Sunphotometer AOD was the obtained when vertical fraction method (VFM) considering Haze Layer Height (HLH) and hygroscopic growth factor f(RH) was used. The validity of the derived relationship between <span class="hlt">satellite</span> AOD and surface PM10 concentration clearly demonstrates that <span class="hlt">satellite</span> AOD data can be utilized for remote sensing of spatial distribution of regional PM10 concentration. PMID:26421659</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4435130','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4435130"><span id="translatedtitle">Evaluation and Intercomparison of <span class="hlt">MODIS</span> and GEOV1 Global Leaf Area Index Products over Four Sites in North China</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping</p> <p>2015-01-01</p> <p>This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011–2013. The Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and Terra <span class="hlt">MODIS</span> LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The <span class="hlt">MODIS</span> products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra <span class="hlt">MODIS</span> (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both <span class="hlt">MODIS</span> and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than <span class="hlt">MODIS</span>. <span class="hlt">MODIS</span> anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and <span class="hlt">MODIS</span> surface reflectances. This study suggests that further improvements of the <span class="hlt">MODIS</span> LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of <span class="hlt">MODIS</span> observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/25781509','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/25781509"><span id="translatedtitle">Evaluation and intercomparison of <span class="hlt">MODIS</span> and GEOV1 global leaf area index products over four sites in North China.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping</p> <p>2015-01-01</p> <p>This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011-2013. The Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and Terra <span class="hlt">MODIS</span> LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The <span class="hlt">MODIS</span> products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra <span class="hlt">MODIS</span> (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both <span class="hlt">MODIS</span> and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than <span class="hlt">MODIS</span>. <span class="hlt">MODIS</span> anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and <span class="hlt">MODIS</span> surface reflectances. This study suggests that further improvements of the <span class="hlt">MODIS</span> LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of <span class="hlt">MODIS</span> observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.2391E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.2391E"><span id="translatedtitle">Remote sensing measurements of biomass burning aerosol optical properties during the 2015 Indonesian burning season from AERONET and <span class="hlt">MODIS</span> <span class="hlt">satellite</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p></p> <p>2016-04-01</p> <p>The strong El Nino event in 2015 resulted in below normal rainfall leading to very dry conditions throughout Indonesia from August though October 2015. These conditions in turn allowed for exceptionally large numbers of biomass burning fires with very high emissions of aerosols. Over the island of Borneo, three AERONET sites (Palangkaraya, Pontianak, and Kuching) measured monthly mean fine mode aerosol optical depth (AOD) at 500 nm from the spectral deconvolution algorithm in September and October ranging from 1.6 to 3.7, with daily average AOD as high as 6.1. In fact, the AOD was sometimes too high to obtain any significant signal in the mid-visible wavelengths, therefore a previously developed new algorithm in the AERONET Version 3 database was invoked to retain the measurements in as many of the red and near-infrared wavelengths (675, 870, 1020, and 1640 nm) as possible to analyze the AOD in those wavelengths. These AOD at longer wavelengths are then utilized to provide some estimate the AOD in the mid-visible. Additionally, <span class="hlt">satellite</span> retrievals of AOD at 550 nm from <span class="hlt">MODIS</span> sensor data and the Dark Target, Beep Blue, and MAIAC algorithms were also analyzed and compared to AERONET measured AOD. Not surprisingly, the AOD was often too high for the <span class="hlt">satellite</span> algorithms to also measure accurate AOD on many days in the densest smoke regions. The AERONET sky radiance inversion algorithm was utilized to analyze retrievals of the aerosol optical properties of complex refractive indices and size distributions. Since the AOD was often extremely high there was sometimes insufficient direct sun signal for the larger solar zenith angles (> 50 degrees) required for almucantar retrievals. However, the new hybrid sky radiance scan can attain sufficient scattering angle range even at small solar zenith angles when 440 nm direct beam irradiance can be accurately measured, thereby allowing for many more retrievals and also at higher AOD levels during this event. Due to extreme</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AtmRe..99..415D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AtmRe..99..415D"><span id="translatedtitle">Evaluating aerosol optical properties observed by ground-based and <span class="hlt">satellite</span> remote sensing over the Mediterranean and the Middle East in 2006</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>de Meij, A.; Lelieveld, J.</p> <p>2011-03-01</p> <p>This study evaluates the spatial and temporal variation of the aerosol optical depth (AOD), the particle size characteristics (Ångström coefficients) and single scattering albedos during selected episodes over the Mediterranean area in 2006, based on independent observational datasets. We compare the <span class="hlt">satellite</span> data of <span class="hlt">MODIS</span> and MISR with those of the ground-based AERONET and in situ measurements. In general the yearly mean <span class="hlt">MODIS</span> and MISR AODs as well as their temporal variation are in good agreement with AERONET. The highest AODs are caused by mineral dust outbreaks and the accumulation of anthropogenic aerosols during stagnant meteorological conditions. The comparison of <span class="hlt">MODIS</span> with MISR aerosol optical properties for June corroborates that the AODs, Ångström coefficients and single scattering albedos agree well, and indicates the presence of high dust loads over the Mediterranean. Later in summer, however, MISR AOD is generally lower than <span class="hlt">MODIS</span>, which is consistent with previous studies that show that MISR tends to underestimate and <span class="hlt">MODIS</span> tends to overestimate AOD over land when compared to AERONET observations. Comparing <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> Deep Blue with MISR for June over the Saharan desert reveals some differences in the location and the maxima of the AODs. Over the eastern Mediterranean highest dust loads occur during spring and autumn. Biomass burning activities around the Black Sea during July and August cause high AODs (e.g. by agricultural waste burning), and the particulate pollution is transported to the eastern Mediterranean and the Middle East by the prevailing northerly Etesian winds.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814073T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814073T"><span id="translatedtitle">Discharge forecasting using <span class="hlt">MODIS</span> and radar altimetry: potential application for transboundary flood risk management in Niger-Benue River basin</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tarpanelli, Angelica; Amarnath, Giriraj; Brocca, Luca; Moramarco, Tommaso</p> <p>2016-04-01</p> <p>Flooding is one of most widespread natural disasters in the world. Its impact is particularly severe and destructive in Asia and Africa, because the living conditions of some settlements are inadequate to cope with this type of natural hazard. In this context, the estimation of discharge is extremely important to address water management and flood risk assessment. However, the inadequate monitoring network hampers any control and prediction activity that could improve these disastrous situations. In the last few years, remote sensing sensors have demonstrated their effectiveness in retrieving river discharge, especially in supporting discharge nowcasting and forecasting activities. Recently, the potential of radar altimetry was apparent when used for estimating water levels in an ungauged river site with good accuracy. It has also become a very useful tool for estimation and prediction of river discharge. However, the low temporal resolution of radar altimeter observations (10 or 35 days, depending on the <span class="hlt">satellite</span> mission) may be not suitable for day-by-day hydrological forecasting. Differently, MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), considering its proven potential for quantifying the variations in discharge of the rivers at daily time resolution may be more suited to this end. For these reasons, <span class="hlt">MODIS</span> and radar altimetry data were used in this study to predicting and forecasting the river discharge along the Niger-Benue River, where severe flooding with extensive damage to property and loss of lives occurred. Therefore, an effective method to forecast flooding can support efforts towards creating an early warning system. In order to estimate river discharge, four <span class="hlt">MODIS</span> products (daily, 8-day, and from <span class="hlt">AQUA</span> and TERRA <span class="hlt">satellites</span>) connected at three sites (two gauged and one ungauged) were used. The capability of remote sensing sensors to forecast discharge a few days in advance at a downstream section using <span class="hlt">MODIS</span> and ENVISAT radar altimetry data</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010486','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010486"><span id="translatedtitle">Absolute Calibration of Optical <span class="hlt">Satellite</span> Sensors Using Libya 4 Pseudo Invariant Calibration Site</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mishra, Nischal; Helder, Dennis; Angal, Amit; Choi, Jason; Xiong, Xiaoxiong</p> <p>2014-01-01</p> <p>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 <span class="hlt">MODIS</span> 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 (<span class="hlt">MODIS</span>) observations over Libya 4 and the resulting model was validated with nadir data acquired from <span class="hlt">satellite</span> sensors such as <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> 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 <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, 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 <span class="hlt">satellite</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130013087','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130013087"><span id="translatedtitle"><span class="hlt">Aqua</span> 10 Years After Launch</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2013-01-01</p> <p>A little over ten years ago, in the early morning hours of May 4, 2002, crowds of spectators stood anxiously watching as the Delta II rocket carrying NASA's <span class="hlt">Aqua</span> spacecraft lifted off from its launch pad at Vandenberg Air Force Base in California at 2:55 a.m. The rocket quickly went through a low-lying cloud cover, after which the main portion of the rocket fell to the waters below and the rockets second stage proceeded to carry <span class="hlt">Aqua</span> south across the Pacific, onward over Antarctica, and north to Africa, where the spacecraft separated from the rocket 59.5 minutes after launch. Then, 12.5 minutes later, the solar array unfurled over Europe, and <span class="hlt">Aqua</span> was on its way in the first of what by now have become over 50,000 successful orbits of the Earth.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMNH14A..05L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMNH14A..05L"><span id="translatedtitle">Frost monitoring and forecasting using <span class="hlt">MODIS</span> Land Surface Temperature data and a Numerical Weather Prediction model forecasts for Eastern Africa</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Limaye, A. S.; Kabuchanga, E. S.; Flores, A.; Mungai, J.; Sakwa, V. N.; Shaka, A.; Malaso, S.; Irwin, D.</p> <p>2014-12-01</p> <p>Frost is a major challenge across Eastern Africa, severely impacting agriculture. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. <span class="hlt">MODIS</span> Land Surface Temperature (LST) data, derived from NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150002549','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150002549"><span id="translatedtitle">Frost Monitoring and Forecasting Using <span class="hlt">MODIS</span> Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh</p> <p>2014-01-01</p> <p>Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. <span class="hlt">MODIS</span> Land Surface Temperature (LST) data, derived from NASA's Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412863K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412863K"><span id="translatedtitle">An evaluation of a semi-analytical cloud property retrieval using Meteosat Second Generation, <span class="hlt">MODIS</span> and CloudSat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kühnlein, M.; Nauss, T.; Appelhans, T.; Kokhanovsky, A. A.; Thies, B.</p> <p>2012-04-01</p> <p>Knowledge of cloud properties such as cloud effective radius and optical thickness is essential to understand their role in the dynamic radiation budget and climate change. The Spinning Enhanced Visible and Infrared Instrument (SEVIRI) on board Meteosat Second Generation (MSG) with its high temporal resolution (15 minutes) permits a non-continuous monitoring of the evolution of cloud properties what has motivated the adaptation of the SLALOM algorithm developed by Nauss and Kokhanovsky (2011) to MSG SEVIRI. The optical properties of SLALOM are compared against the LUT-based approach by Platnick et al. (2003) using data from the <span class="hlt">MODIS</span> sensor on-board of the NASA EOS <span class="hlt">Aqua</span> and Terra <span class="hlt">satellites</span> (King and Greenstone, 1999) as well as the cloud optical depth product (2B-TAU) of CloudSat (Polonsky et al., 2008) and results are shown over ocean and land. Over water the retrievals show very close results where differences increase over land.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN11B1279W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN11B1279W"><span id="translatedtitle"><span class="hlt">MODIS</span> Near real-time (NRT) data for fire applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wong, M.; Davies, D.; Ilavajhala, S.; Molinario, G.; Justice, C.; Latham, J.; Martucci, A.; Murphy, K. J.</p> <p>2011-12-01</p> <p>This paper describes the lessons learned from the development of the Fire Information for Resource Management System (FIRMS) prototype and its transition to an operational system, the Global Fire Information Management System (GFIMS), at the United Nations Food and Agriculture Organization (FAO) in August 2010. These systems provide active fire data from the <span class="hlt">MODIS</span> sensor, on board NASA's Terra and <span class="hlt">Aqua</span> Earth Observing <span class="hlt">Satellites</span>, to users at no cost, in near-real time and in easy-to-use formats. The FIRMS prototype evolved from simply providing daily active fire text files via FTP, to include services such as providing fire data in various data formats, an interactive WebGIS allowing users to view and query the data and an email alert service enabling users to receive emails of near real-time fire data of their chosen area of interest. FIRMS was designed to remove obstacles to the uptake and use of fire data by addressing issues often associated with <span class="hlt">satellite</span> data: cost, timeliness of delivery, limited data formats and the need for technical expertise to process and analyze the data. We also illustrate how the <span class="hlt">MODIS</span> active fire data are routinely used for firefighting and conservation monitoring. We present results from a user survey, completed by approximately 345 people from 65 countries, and provide case studies highlighting how the provision of <span class="hlt">MODIS</span> active fire data have made an impact on conservation and firefighting, especially in remote areas where it is difficult to have on-the-ground surveillance. We highlight the gaps in current capabilities, both with users and the data. A major obstacle still for some users is having low or no internet connectivity and a possible solution is through the use of cell phone technologies such as SMS text messaging of fire locations and information. GFIMS, and its precursor, FIRMS, were developed by the University of Maryland with funding from NASA's Applied Sciences Program. With GFIMS established at FAO as an operational</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030032934','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030032934"><span id="translatedtitle"><span class="hlt">MODIS</span> Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most <span class="hlt">MODIS</span> data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. <span class="hlt">MODIS</span> Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). <span class="hlt">MODIS</span> data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the <span class="hlt">MODIS</span> Science Teams. <span class="hlt">MODIS</span>/Terra Level 1, and all <span class="hlt">MODIS</span>/Terra 11 micron SST products are announced as validated. At the time of this publication, the <span class="hlt">MODIS</span> Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of <span class="hlt">MODIS</span>/Terra Ocean products. <span class="hlt">MODIS/Aqua</span> Level 1 and cloud mask products are released with provisional maturity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC23L1260Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC23L1260Z"><span id="translatedtitle">Air Temperature Estimation over the Third Pole Using <span class="hlt">MODIS</span> LST</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, H.; Zhang, F.; Ye, M.; Che, T.</p> <p>2015-12-01</p> <p>The Third Pole is centered on the Tibetan Plateau (TP), which is the highest large plateau around the world with extremely complex terrain and climate conditions, resulting in very scarce meteorological stations especially in the vast west region. For these unobserved areas, the remotely sensed land surface temperature (LST) can greatly contribute to air temperature estimation. In our research we utilized the <span class="hlt">MODIS</span> LST production from both TERRA and <span class="hlt">AQUA</span> to estimate daily mean air temperature over the TP using multiple statistical models. Other variables used in the models include longitudes, latitudes, Julian day, solar zenith, NDVI and elevation. To select a relatively optimal model, we chose six popular and representative statistical models as candidate models including the multiple linear regression (MLR), the partial least squares regression (PLS), back propagate neural network (BPNN), support vector regression (SVR), random forests (RF) and Cubist regression (CR). The performances of the six models were compared for each possible combination of LSTs at four <span class="hlt">satellite</span> pass times and two quality situations. Eventually a ranking table consisting of optimal models for each LST combination and quality situation was built up based on the validation results. By this means, the final production is generated providing daily mean air temperature with the least cloud blockage and acceptable accuracy. The average RMSEs of cross validation are mostly around 2℃. Stratified validations were also performed to test the expansibility to unobserved and high-altitude areas of the final models selected.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006614','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006614"><span id="translatedtitle">Consistency of CERES Radiances and Fluxes from <span class="hlt">Aqua</span> and Suomi-NPP</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liang, Lusheng; Miller, Walter; Su, Wenying; Loeb, Norman</p> <p>2015-01-01</p> <p>The Clouds and Earth's Radiant Energy System (CERES) instruments on board Terra, <span class="hlt">Aqua</span>, and Suomi-NPP have been providing data products critical to advancing our understanding of the effects of clouds and aerosols on radiative energy within the Earth-atmosphere system. The CERES instrument consists of a threechannel broadband scanning radiometer. The scanning radiometer measures radiances in shortwave (SW, 0.3-5 micron), window (WN, 8-12 micron), and total (0.3-200 micron) channels. The longwave (LW) component is derived as the difference between total and SW channels. These measured radiances at a given sun-Earthsatellite geometry are converted to outgoing reflected solar and emitted thermal TOA radiative fluxes by using CERES scene-type dependent angular distribution models (ADMs). The CERES instruments must remain radiometrically stable and correctly inter-calibrated to accurately capture changes in Earth"s radiation budget from interannual to decadal timescales. This presentation will focus on comparisons between collocated radiance measurements from CERES instruments on <span class="hlt">Aqua</span> and on Suomi-NPP. As we do not have a set of ADMs that is constructed specifically for the CERES instrument on Suomi-NPP, CERES <span class="hlt">Aqua</span> ADMs are used to invert fluxes from radiance measurements on Suomi-NPP. But the CERES <span class="hlt">Aqua</span> footprint size is smaller than the CERES Suomi-NPP footprint size and the scene identifications provided by <span class="hlt">MODIS</span> and VIIRS can also be different from each other. Will using <span class="hlt">Aqua</span> ADMs for Suomi-NPP flux inversion increase the flux uncertainty? We will examine the deseasonalized flux anomaly time series using <span class="hlt">Aqua</span> data alone and using combined <span class="hlt">Aqua</span> and Suomi-NPP data. We will also present a simulation study to assess the Suomi-NPP flux uncertainty from using <span class="hlt">Aqua</span> ADMs for the flux inversion.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8528E..09X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8528E..09X"><span id="translatedtitle">Comparison of <span class="hlt">MODIS</span> and VIIRS solar diffuser stability monitor performance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong; Fulbright, Jon; Angal, Amit; Sun, Junqiang; Wang, Zhipeng</p> <p>2012-11-01</p> <p>Launched in December 1999 and May 2002, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for more than 12 and 10 years, respectively. <span class="hlt">MODIS</span> reflective solar bands (RSB) are calibrated on-orbit by a solar diffuser (SD). Its on-orbit degradation, or the change in its bi-directional reflectance factor (BRF), is tracked by a solar diffuser stability monitor (SDSM). The <span class="hlt">MODIS</span> SDSM makes alternate observations of direct sunlight through an attenuation screen (Sun view) and of sunlight reflected diffusely off the SD (SD view) during each SDSM calibration event. The <span class="hlt">MODIS</span> SDSM has 9 detectors, covering wavelengths from 0.41 to 0.94 μm. Due to a design error in <span class="hlt">MODIS</span> SDSM sub-system (identified post-launch), relatively large ripples were noticed in its Sun view responses. As a result, an alternative approach was developed by the <span class="hlt">MODIS</span> calibration team to minimize the uncertainty in determining the SD on-orbit degradation. The first VIIRS, on-board the Suomi NPP spacecraft, was successfully launched in October 2011. It carries a <span class="hlt">MODIS</span>-like SD and SDSM system for its RSB on-orbit calibration. Its design was improved based on lessons learned from <span class="hlt">MODIS</span>. Operationally, the VIIRS SDSM is used more frequently than <span class="hlt">MODIS</span>. VIIRS SDSM collects data using 8 individual detectors, covering a similar wavelength range as <span class="hlt">MODIS</span>. This paper provides an overview of <span class="hlt">MODIS</span> and VIIRS SDSM design features, their on-orbit operations, and calibration strategies. It illustrates their on-orbit performance in terms of on-orbit changes in SDSM detector on-orbit responses and on-orbit degradations of their SD. Results show that on-orbit changes of both <span class="hlt">MODIS</span> and VIIRS SD BRF and SDSM response have similar wavelength dependency: the SD degradation is faster at shorter visible wavelengths while the decrease of SDSM detector responses (gains) is greater at longer near-infrared wavelengths.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020081113','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020081113"><span id="translatedtitle"><span class="hlt">MODIS</span> Snow-Cover Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)</p> <p>2002-01-01</p> <p>On December 18, 1999, the Terra <span class="hlt">satellite</span> was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Many geophysical products are derived from <span class="hlt">MODIS</span> data including global snow-cover products. <span class="hlt">MODIS</span> snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. <span class="hlt">MODIS</span> snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the <span class="hlt">MODIS</span> products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The <span class="hlt">MODIS</span> snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving <span class="hlt">MODIS</span> data and field and aircraft measurements, is presented to show some early validation work.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUSM.H51A..07W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUSM.H51A..07W"><span id="translatedtitle">Evaluation of the GCIP/GAPP Short-Wave Surface Radiative fluxes against independent <span class="hlt">satellite</span> observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, H.; Pinker, R. T.; Laszlo, I.</p> <p>2004-05-01</p> <p>The University of Maryland Global Energy and Water Cycle Experiment (GEWEX) Continental Scale International Project (GCIP) and GEWEX Americas Prediction Project (GAPP) Surface Radiation Budget inference scheme is implemented operationally and in real time at the National Oceanic and Atmospheric Administration (NOAA)/National Environmental <span class="hlt">Satellite</span> Data and Information Service (NESDIS), and provided to the scientific community by the University of Maryland at http://www.atmos.umd.edu/~srb/gcip/webgcip.htm. The radiative fluxes are derived from Geostationary Operational Environmental <span class="hlt">Satellites</span> (GOES) over the United States. The model has been extensively evaluated against ground observations however there is also a need to evaluate this product against independent <span class="hlt">satellite</span> estimates. Geostationary <span class="hlt">satellites</span> are important in radiation budget research due to their capability to capture the diurnal cycle of the energy received at the earth surface. Due to their instrument configuration, much of these <span class="hlt">satellites</span> are limited in their capability to detect accurately cloud and aerosol optical properties. Polar orbiting <span class="hlt">satellites</span> tend to have higher spatial resolution than geostationary <span class="hlt">satellites</span>, as well as more spectrally resolving instruments. In this study, an attempt will be made to evaluate the operational product against products obtained from independent geostationary <span class="hlt">satellite</span> inputs like the ISCCP DX data, as well as those obtained from polar orbiting <span class="hlt">satellites</span> such as the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) instrument on board Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, and ADEOS II. The derived fluxes will be also evaluated against ground observation at six SURFRED stations and at the ARM sites.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040000975','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040000975"><span id="translatedtitle">Improved Prediction of Momentum and Scalar Fluxes Using <span class="hlt">MODIS</span> Imagery</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Crago, Richard D.; Jasinski, Michael F.</p> <p>2003-01-01</p> <p>There are remote sensing and science objectives. The remote sensing objectives are: To develop and test a theoretical method for estimating local momentum aerodynamic roughness length, z(sub 0m), using <span class="hlt">satellite</span> multispectral imagery. To adapt the method to the <span class="hlt">MODIS</span> imagery. To develop a high-resolution (approx. 1km) gridded dataset of local momentum roughness for the continental United States and southern Canada, using <span class="hlt">MODIS</span> imagery and other <span class="hlt">MODIS</span> derived products. The science objective is: To determine the sensitivity of improved <span class="hlt">satellite</span>-derived (<span class="hlt">MODIS</span>-) estimates of surface roughness on the momentum and scalar fluxes, within the context of 3-D atmospheric modeling.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990004142','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990004142"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1996-01-01</p> <p>The objectives of the last six months were: (1) Complete sensitivity analysis of fluorescence; line height algorithms (2) Deliver fluorescence algorithm code and test data to the University of Miami for integration; (3) Complete analysis of bio-optical data from Southern Ocean cruise; (4) Conduct laboratory experiments based on analyses of field data; (5) Analyze data from bio-optical mooring off Hawaii; (6) Develop calibration/validation plan for <span class="hlt">MODIS</span> fluorescence data; (7) Respond to the Japanese Research Announcement for GLI; and (8) Continue to review plans for EOSDIS and assist ECS contractor.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010069265','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010069265"><span id="translatedtitle"><span class="hlt">MODIS</span> Snow-Cover Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)</p> <p>2001-01-01</p> <p>On December 18, 1999, the Terra <span class="hlt">satellite</span> was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Many geophysical products are derived from <span class="hlt">MODIS</span> data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. <span class="hlt">MODIS</span> snow-cover products represent potential improvement to the currently available operation products mainly because the <span class="hlt">MODIS</span> products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving <span class="hlt">MODIS</span> data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070017429','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070017429"><span id="translatedtitle">The Plane-parallel Albedo Bias of Liquid Clouds from <span class="hlt">MODIS</span> Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cahalan, Robert F.; Platnick, Steven</p> <p>2007-01-01</p> <p>In our most advanced modeling tools for climate change prediction, namely General Circulation Models (GCMs), the schemes used to calculate the budget of solar and thermal radiation commonly assume that clouds are horizontally homogeneous at scales as large as a few hundred kilometers. However, this assumption, used for convenience, computational speed, and lack of knowledge on cloud small scale variability, leads to erroneous estimates of the radiation budget. This paper provides a global picture of the solar radiation errors at scales of approximately 100 km due to warm (liquid phase) clouds only. To achieve this, we use cloud retrievals from the instrument <span class="hlt">MODIS</span> on the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span>, along with atmospheric and surface information, as input into a GCM-style radiative transfer algorithm. Since the <span class="hlt">MODIS</span> product contains information on cloud variability below 100 km we can run the radiation algorithm both for the variable and the (assumed) homogeneous clouds. The difference between these calculations for reflected or transmitted solar radiation constitutes the bias that GCMs would commit if they were able to perfectly predict the properties of warm clouds, but then assumed they were homogeneous for radiation calculations. We find that the global average of this bias is approx.2-3 times larger in terms of energy than the additional amount of thermal energy that would be trapped if we were to double carbon dioxide from current concentrations. We should therefore make a greater effort to predict horizontal cloud variability in GCMs and account for its effects in radiation calculations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011241','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011241"><span id="translatedtitle">Reduction of Aerosol Absorption in Beijing Since 2007 from <span class="hlt">MODIS</span> and AERONET</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.; Tanre, D.; Dubovik, O.; Goloub, P.; Chen, H.-B.; Sinyuk, A.; Wang, Y.; Korkin, S.</p> <p>2011-01-01</p> <p>An analysis of the time series of <span class="hlt">MODIS</span>-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The <span class="hlt">MODIS</span> data from both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10-20% in the prior period, the bias mostly disappears after mid-2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Angstrom exponent. At the same time, it shows an increasing trend in the single scattering albedo, by approx.0.02 in 9 years. As MAIAC was using the same aerosol model for the entire 2000-2010 period, the decrease in AOT bias after 2007 can be explained only by a corresponding decrease of aerosol absorption caused by a reduction in local black carbon emissions. The observed changes correlate in time with the Chinese government's broad measures to improve air quality in Beijing during preparations for the Summer Olympics of 2008.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120003919&hterms=chinese&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dchinese','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120003919&hterms=chinese&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dchinese"><span id="translatedtitle">Reduction of Aerosol Absorption in Beijing Since 2007 from <span class="hlt">MODIS</span> and AERONET</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.; Tanre, D.; Dubovik, O.; Goloub, P.; Chen, H.-B.; Sinyuk, A.; Wang, Y.; Korkin, S.</p> <p>2011-01-01</p> <p>An analysis of the time series of <span class="hlt">MODIS</span>-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The <span class="hlt">MODIS</span> data from both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10-20% in the prior period, the bias mostly disappears after mid- 2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Angstrom exponent. At the same time, it shows an increasing trend in the single scattering albedo, by 0.02 in 9 years. As MAIAC was using the same aerosol model for the entire 2000-2010 period, the decrease in AOT bias after 2007 can be explained only by a corresponding decrease of aerosol absorption caused by a reduction in local black carbon emissions. The observed changes correlate in time with the Chinese government's broad measures to improve air quality in Beijing during preparations for the Summer Olympics of 2008.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011GeoRL..3810803L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011GeoRL..3810803L"><span id="translatedtitle">Reduction of aerosol absorption in Beijing since 2007 from <span class="hlt">MODIS</span> and AERONET</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lyapustin, A.; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.; Tanré, D.; Dubovik, O.; Goloub, P.; Chen, H.-B.; Sinyuk, A.; Wang, Y.; Korkin, S.</p> <p>2011-05-01</p> <p>An analysis of the time series of <span class="hlt">MODIS</span>-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The <span class="hlt">MODIS</span> data from both the Terra and <span class="hlt">Aqua</span> <span class="hlt">satellites</span> were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10-20% in the prior period, the bias mostly disappears after mid-2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Ångström exponent. At the same time, it shows an increasing trend in the single scattering albedo, b