Organization
Science Systems and Applications, Inc.
Email
Business Address
One Enterprise Parkway
Suite 200
Hampton, VA 23666
United States
Co-Authored Publications
-
Doelling, D., et al. (2023), Daily monitoring algorithms to detect geostationary imager visible radiance anomalies, Terms of Use, doi:10.1117/1.JRS.16.014502.
-
Bhatt, R., et al. (2020), Response Versus Scan-Angle Assessment of MODIS Reflective Solar Bands in Collection 6.1 Calibration, IEEE Trans. Geosci. Remote Sens., 1-14, doi:10.1109/TGRS.2019.2946963.
-
Doelling, D., et al. (2019), Inter-Calibration of the OSIRIS-REx NavCams with Earth-Viewing Imagers, doi:10.3390/rs11222717.
-
Doelling, D., et al. (2019), The Inter-Calibration of the DSCOVR EPIC Imager with Aqua-MODIS and NPP-VIIRS, doi:10.3390/rs11131609.
-
Bhatt, R., et al. (2018), Consideration of Radiometric Quantization Error in Satellite Sensor Cross-Calibration, Remote Sensing, 10, 1131, doi:10.3390/rs10071131.
-
Doelling, D., et al. (2018), Geostationary Visible Imager Calibration for the CERES SYN1deg Edition 4 Product, Remote Sensing, 10, 288, doi:10.3390/rs10020288.
-
Bhatt, R., et al. (2017), Development of Seasonal BRDF Models to Extend the Use of Deep Convective Clouds as Invariant Targets for Satellite SWIR-Band Calibration, Remote Sensing, 9, 1061, doi:10.3390/rs9101061.
-
Bhatt, R., et al. (2017), Characterizing response versus scan-angle for MODIS reflective solar bands using deep convective clouds, Journal of Applied Remote Sensing, 11, 16014, doi:10.1117/1.JRS.11.016014.
-
Bhatt, R., et al. (2016), A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part I: Methodology, J. Atmos. Oceanic Technol., 33, 2499-2515, doi:10.1175/JTECH-D-16-0044.1.
-
Doelling, D., et al. (2016), A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part II: Validation, J. Atmos. Oceanic Technol., 33, 2517-2534, doi:10.1175/JTECH-D-16-0042.1.
-
Doelling, D., et al. (2016), Improvements to the Geostationary Visible Imager Ray-Matching Calibration Algorithm for CERES Edition 4, J. Atmos. Oceanic Technol., 33, 2679-2698, doi:10.1175/JTECH-D-16-0113.1.
-
Scarino, B., et al. (2016), A Web-Based Tool for Calculating Spectral Band Difference Adjustment Factors Derived From SCIAMACHY Hyperspectral Data, IEEE Trans. Geosci. Remote Sens., 54, 2529-2542, doi:10.1109/TGRS.2015.2502904.
-
Bhatt, R., et al. (2014), Desert-Based Absolute Calibration of Successive Geostationary Visible Sensors Using a Daily Exoatmospheric Radiance Model, IEEE Trans. Geosci. Remote Sens., 52, 3670-3682, doi:10.1109/TGRS.2013.2274594.
-
Doelling, D., et al. (2013), The Intercalibration of Geostationary Visible Imagers Using Operational Hyperspectral SCIAMACHY Radiances, IEEE Trans. Geosci. Remote Sens., 51, 1245-1254, doi:10.1109/TGRS.2012.2227760.
-
Doelling, D., et al. (2013), The Characterization of Deep Convective Clouds as an Invariant Calibration Target and as a Visible Calibration Technique, IEEE Trans. Geosci. Remote Sens., 51, 1147-1159, doi:10.1109/TGRS.2012.2225066.
-
Jin, Z., et al. (2012), Correlation between SCIAMACHY, MODIS, and CERES reflectance measurements: Implications for CLARREO, J. Geophys. Res., 117, D05114, doi:10.1029/2011JD017051.
-
Levy, R.C., et al. (2009), A Critical Look at Deriving Monthly Aerosol Optical Depth From Satellite Data, IEEE Trans. Geosci. Remote Sens., 47, 2942-2956, doi:10.1109/TGRS.2009.2013842.
-
Savtchenko, A., et al. (2008), A-Train Data Depot: Bringing Atmospheric Measurements Together, IEEE Trans. Geosci. Remote Sens., 46, 2788-2795, doi:10.1109/TGRS.2008.917600.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
