Folders: ROOT > ScienceBase Catalog > USGS Wetland and Aquatic Research Center > An Unvegetated to Vegetated Ratio (UVVR) for coastal wetlands of the Conterminous United States (2014-2018) > A NAIP and Sentinel-2 based quantification of fractional composition of unvegetated, vegetated, and water in the conterminous United States, 2014-2019 used for calibration and validation of Landsat based datasets ( Show all descendants )
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ROOT _ScienceBase Catalog __USGS Wetland and Aquatic Research Center ___An Unvegetated to Vegetated Ratio (UVVR) for coastal wetlands of the Conterminous United States (2014-2018) ____A NAIP and Sentinel-2 based quantification of fractional composition of unvegetated, vegetated, and water in the conterminous United States, 2014-2019 used for calibration and validation of Landsat based datasets Filters
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These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Conterminous United States,
Florida,
Gulf of Mexico Coast,
Louisiana,
These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.
These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.
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