2 datasets found
  1. G

    USGS Landsat 9 Level 2, Collection 2, Tier 2

    • developers.google.com
    Updated Apr 20, 2022
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    USGS (2022). USGS Landsat 9 Level 2, Collection 2, Tier 2 [Dataset]. https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_L2
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    Dataset updated
    Apr 20, 2022
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Time period covered
    Oct 31, 2021 - Jun 5, 2025
    Area covered
    Earth
    Description

    This dataset contains atmospherically corrected surface reflectance and land surface temperature derived from the data produced by the Landsat 9 OLI/TIRS sensors. These images contain 5 visible and near-infrared (VNIR) bands and 2 short-wave infrared (SWIR) bands processed to orthorectified surface reflectance, and one thermal infrared (TIR) band processed to orthorectified surface temperature. They also contain intermediate bands used in calculation of the ST products, as well as QA bands. Landsat 9 SR products are created with the Land Surface Reflectance Code (LaSRC). All Collection 2 ST products are created with a single-channel algorithm jointly created by the Rochester Institute of Technology (RIT) and National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Strips of collected data are packaged into overlapping "scenes" covering approximately 170km x 183km using a standardized reference grid. Some assets have only SR data, in which case ST bands are present but empty. For assets with both ST and SR bands, 'PROCESSING_LEVEL' is set to 'L2SP'. For assets with only SR bands, 'PROCESSING_LEVEL' is set to 'L2SR'. Additional documentation and usage examples. Data provider notes: Data products must contain both optical and thermal data to be successfully processed to surface temperature, as ASTER NDVI is required to temporally adjust the ASTER GED product to the target Landsat scene. Therefore, night time acquisitions cannot be processed to surface temperature. A known error exists in the surface temperature retrievals relative to clouds and possibly cloud shadows. The characterization of these issues has been documented by Cook et al., (2014). ASTER GED contains areas of missing mean emissivity data required for successful ST product generation. If there is missing ASTER GED information, there will be missing ST data in those areas. The ASTER GED dataset is created from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. While this dataset has a global spatial extent, there are areas missing mean emissivity information due to persistent cloud contamination in the ASTER measurements. The USGS further screens unphysical values (emissivity < 0.6) in ASTER GED to remove any emissivity underestimation due to undetected clouds. For any given pixel with no ASTER GED input or unphysical emissivity value, the resulting Landsat ST products have missing pixels. The missing Landsat ST pixels will be consistent through time (1982-present) given the static nature of ASTER GED mean climatology data. For more information refer to landsat-collection-2-surface-temperature-data-gaps-due-missing

  2. G

    USGS Landsat 8 Level 2, Collection 2, Tier 2

    • developers.google.com
    Updated Apr 20, 2022
    Share
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    USGS (2022). USGS Landsat 8 Level 2, Collection 2, Tier 2 [Dataset]. https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2_L2
    Explore at:
    Dataset updated
    Apr 20, 2022
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Time period covered
    Mar 18, 2013 - May 22, 2025
    Area covered
    Earth
    Description

    This dataset contains atmospherically corrected surface reflectance and land surface temperature derived from the data produced by the Landsat 8 OLI/TIRS sensors. These images contain 5 visible and near-infrared (VNIR) bands and 2 short-wave infrared (SWIR) bands processed to orthorectified surface reflectance, and one thermal infrared (TIR) band processed to orthorectified surface temperature. They also contain intermediate bands used in calculation of the ST products, as well as QA bands. Landsat 8 SR products are created with the Land Surface Reflectance Code (LaSRC). All Collection 2 ST products are created with a single-channel algorithm jointly created by the Rochester Institute of Technology (RIT) and National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Strips of collected data are packaged into overlapping "scenes" covering approximately 170km x 183km using a standardized reference grid. Some assets have only SR data, in which case ST bands are present but empty. For assets with both ST and SR bands, 'PROCESSING_LEVEL' is set to 'L2SP'. For assets with only SR bands, 'PROCESSING_LEVEL' is set to 'L2SR'. Additional documentation and usage examples. Data provider notes: Data products must contain both optical and thermal data to be successfully processed to surface temperature, as ASTER NDVI is required to temporally adjust the ASTER GED product to the target Landsat scene. Therefore, night time acquisitions cannot be processed to surface temperature. A known error exists in the surface temperature retrievals relative to clouds and possibly cloud shadows. The characterization of these issues has been documented by Cook et al., (2014). ASTER GED contains areas of missing mean emissivity data required for successful ST product generation. If there is missing ASTER GED information, there will be missing ST data in those areas. The ASTER GED dataset is created from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. While this dataset has a global spatial extent, there are areas missing mean emissivity information due to persistent cloud contamination in the ASTER measurements. The USGS further screens unphysical values (emissivity < 0.6) in ASTER GED to remove any emissivity underestimation due to undetected clouds. For any given pixel with no ASTER GED input or unphysical emissivity value, the resulting Landsat ST products have missing pixels. The missing Landsat ST pixels will be consistent through time (1982-present) given the static nature of ASTER GED mean climatology data. For more information refer to landsat-collection-2-surface-temperature-data-gaps-due-missing

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USGS (2022). USGS Landsat 9 Level 2, Collection 2, Tier 2 [Dataset]. https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_L2

USGS Landsat 9 Level 2, Collection 2, Tier 2

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 20, 2022
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Time period covered
Oct 31, 2021 - Jun 5, 2025
Area covered
Earth
Description

This dataset contains atmospherically corrected surface reflectance and land surface temperature derived from the data produced by the Landsat 9 OLI/TIRS sensors. These images contain 5 visible and near-infrared (VNIR) bands and 2 short-wave infrared (SWIR) bands processed to orthorectified surface reflectance, and one thermal infrared (TIR) band processed to orthorectified surface temperature. They also contain intermediate bands used in calculation of the ST products, as well as QA bands. Landsat 9 SR products are created with the Land Surface Reflectance Code (LaSRC). All Collection 2 ST products are created with a single-channel algorithm jointly created by the Rochester Institute of Technology (RIT) and National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Strips of collected data are packaged into overlapping "scenes" covering approximately 170km x 183km using a standardized reference grid. Some assets have only SR data, in which case ST bands are present but empty. For assets with both ST and SR bands, 'PROCESSING_LEVEL' is set to 'L2SP'. For assets with only SR bands, 'PROCESSING_LEVEL' is set to 'L2SR'. Additional documentation and usage examples. Data provider notes: Data products must contain both optical and thermal data to be successfully processed to surface temperature, as ASTER NDVI is required to temporally adjust the ASTER GED product to the target Landsat scene. Therefore, night time acquisitions cannot be processed to surface temperature. A known error exists in the surface temperature retrievals relative to clouds and possibly cloud shadows. The characterization of these issues has been documented by Cook et al., (2014). ASTER GED contains areas of missing mean emissivity data required for successful ST product generation. If there is missing ASTER GED information, there will be missing ST data in those areas. The ASTER GED dataset is created from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. While this dataset has a global spatial extent, there are areas missing mean emissivity information due to persistent cloud contamination in the ASTER measurements. The USGS further screens unphysical values (emissivity < 0.6) in ASTER GED to remove any emissivity underestimation due to undetected clouds. For any given pixel with no ASTER GED input or unphysical emissivity value, the resulting Landsat ST products have missing pixels. The missing Landsat ST pixels will be consistent through time (1982-present) given the static nature of ASTER GED mean climatology data. For more information refer to landsat-collection-2-surface-temperature-data-gaps-due-missing

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