The Visible Infrared Imaging Radiometer Suite (VIIRS) daily surface reflectance (VNP09GA) product provides an estimate of land surface reflectance from the Suomi National Polar-Orbiting Partnership (S-NPP) VIIRS sensor. Data are provided for three imagery bands (I1, I2, I3) at nominal 500 meter resolution (~463 meter) and nine moderate-resolution bands (M1, M2, M3, M4, M5, M7, M8, M10, M11) at nominal 1 kilometer (~926 meter) resolution. The 500 meter and 1 kilometer datasets are derived through resampling the native 375 meter and 750 meter VIIRS resolutions, respectively, in the L2 input product. These bands are corrected for atmospheric conditions to provide an estimate of the surface spectral reflectance as it would be measured at ground level. The data is temporally aggregated over each of the 16 possible passes per day. When multiple observations are present for each day, only the first of the highest-quality observations is included. The band scale factors are already applied. For additional information, visit the VIIRS Land Product Quality Assessment website Documentation: User's Guide Algorithm Theoretical Basis Document (ATBD)

The Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) daily surface reflectance (VNP09GA) Version 1 product provides an estimate of land surface reflectance from the Suomi National Polar-Orbiting Partnership (Suomi NPP) VIIRS sensor. Data are provided for three imagery bands (I1-I3) at nominal 500 meter resolution (~ 463 meter) and nine moderate resolution bands (M1-M5, M7, M8, M10, M11) at nominal 1 kilometer (~926 meter) resolution. The 500 meter and 1 kilometer datasets are derived through resampling the native 375 meter and 750 meter VIIRS resolutions, respectively, in the Level 2 input product. These bands are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. The inputs to the surface reflectance algorithm are top-of-atmosphere reflectance for the VIIRS visible bands, the VIIRS cloud mask and aerosol product, aerosol optical thickness and atmospheric data obtained from the NOAA National Centers for Environmental Prediction (NCEP) reanalysis system. Along with the twelve reflectance bands are reflectance band quality, sensor azimuth angle, solar azimuth angle, sensor zenith angle, solar zenith angle, and observations layers. The reflectance layers from the VNP09GA data product are used as input data for many of the VIIRS land products.

The VNP09GA VIIRS Version 1 data product was decommissioned on April 8th, 2025. Users are encouraged to use Version 2 data products, which provide better calibration and consistency for the end user. VIIRS Version 2 data products are available from both the SNPP (VNP09GA) and NOAA-20 (VJ109GA) satellites.The Visible Infrared Imaging Radiometer Suite (VIIRS) daily surface reflectance (VNP09GA) Version 1 product provides an estimate of land surface reflectance from the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS sensor. Data are provided for three imagery bands (I1-I3) at nominal 500 meter resolution (~ 463 meter) and nine moderate resolution bands (M1-M5, M7, M8, M10, M11) at nominal 1 kilometer (~926 meter) resolution. The 500 meter and 1 kilometer datasets are derived through resampling the native 375 meter and 750 meter VIIRS resolutions, respectively, in the Level 2 input product. These bands are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. The inputs to the surface reflectance algorithm are top-of-atmosphere reflectance for the VIIRS visible bands,the VIIRS cloud mask and aerosol product, aerosol optical thickness and atmospheric data obtained from the NOAA National Centers for Environmental Prediction (NCEP) reanalysis system. Along with the twelve reflectance bands are reflectance band quality, sensor azimuth angle,solar azimuth angle, sensor zenith angle, solar zenith angle, and observations layers. The reflectance layers from the VNP09GA data product are used as input data for many of the VIIRS land products. Known Issues The VIIRS Land Surface Reflectance product (VNP09) may incorrectly flag retrievals as 'High Aerosol' over brighter surfaces and at higher view angles. This will impact the downstream VIIRS BRDF/Albedo (VNP43) and Vegetation Index (VNP13) data products which use the aerosol quantity flag to screen out high aerosol values. Corrections will be implemented in Collection 2 reprocessing in 2022. * For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website and in Section 4.0 "Caveats and Known Problems" of the User Guide.

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS is attached to the International Space Station (ISS) and collects data globally between 52° N and 52° S latitudes. A map of the acquisition coverage can be found in figure 2 on the ECOSTRESS website(https://ecostress.jpl.nasa.gov/science).

The ECOSTRESS Tiled Ancillary NDVI and Albedo Level 2 Global 70 m (ECO_L2T_STARS) Version 2 data product provides Normalized Difference Vegetation Index (NDVI) and albedo aligned with each daytime ECOSTRESS overpass. ECO_L2T_STARS is an ancillary data product derived from Visible Infrared Imaging Radiometer Suite (VIIRS) and Harmonized Landsat Sentinel (HLS) Version 2 data sources with application to the ECOSTRESS mission. This data product fuses fine resolution inputs from HLS surface reflectance products and moderate resolution inputs from the daily NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS surface reflectance (VNP09GA) product. The data fusion is performed using a variant of the Spatial Timeseries for Automated high-Resolution multi-Sensor data fusion (STARS) algorithm to create tiles matching the ECOSTRESS standard resolution of 70 meters (m). STARS is a Bayesian timeseries methodology that provides streaming data fusion and uncertainty quantification through efficient Kalman filtering. Refer to Section 3.1 of the ECOSTRESS Jet Propulsion Laboratory (JPL) EvapoTranspiration (JET) Level-3 Algorithm Theoretical Basis Document (ATBD) for further details of the Bidirectional Reflectance Distribution Function (BRDF) implementation and albedo calculations.

The ECO_L2T_STARS Version 2 data product is provided in Cloud Optimized GeoTIFF (COG) format using a modified version of the Military Grid Reference System (MGRS), which divides Universal Transverse Mercator (UTM) zones into square tiles that are 109.8 km by 109.8 km with a 70 m spatial resolution. Each band is distributed as a separate COG. This product contains four layers including NDVI, NDVI uncertainty, albedo, and albedo uncertainty. The ECO_L2T_STARS ancillary NDVI and albedo product is only generated for corresponding daytime ECOSTRESS Tiled Land Surface Temperature and Emissivity Instantaneous Level 2 Global 70 m (ECO_L2T_LSTE) Version 2 tiles.

The ECOSTRESS Tiled Ancillary NDVI and Albedo Level 2 Global 70 m (ECO_L2T_STARS) Version 2 data product provides Normalized Difference Vegetation Index (NDVI) and albedo aligned with each daytime ECOSTRESS overpass. ECO_L2T_STARS is an ancillary data product derived from Visible Infrared Imaging Radiometer Suite (VIIRS) ( https://lpdaac.usgs.gov/product_search/?query=viirs&status=Operational&view=list&sort=title) and Harmonized Landsat Sentinel (HLS) ( https://lpdaac.usgs.gov/product_search/?collections=HLS&status=Operational&view=list) Version 2 data sources with application to the ECOSTRESS mission. This data product fuses fine resolution inputs from HLS surface reflectance products and moderate resolution inputs from the daily NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS surface reflectance (VNP09GA) ( https://doi.org/10.5067/VIIRS/VNP09GA.001) product. The data fusion is performed using a variant of the Spatial Timeseries for Automated high-Resolution multi-Sensor data fusion (STARS) algorithm to create tiles matching the ECOSTRESS standard resolution of 70 meters (m). STARS is a Bayesian timeseries methodology that provides streaming data fusion and uncertainty quantification through efficient Kalman filtering. Refer to Section 3.1 of the ECOSTRESS Jet Propulsion Laboratory (JPL) EvapoTranspiration (JET) Level-3 Algorithm Theoretical Basis Document (ATBD) for further details of the Bidirectional Reflectance Distribution Function (BRDF) implementation and albedo calculations.

The ECO_L2T_STARS Version 2 data pr