High-frequency observations of surface water at fine spatial scales are critical to effectively manage aquatic habitat, flood risk and water quality. We developed inundation algorithms for Sentinel-1 and Sentinel-2 across 12 sites within the conterminous United States (CONUS) covering >536,000 km2 and representing diverse hydrologic and vegetation landscapes. These algorithms were trained on data from 13,412 points spread throughout the 12 sites. Each scene in the 5-year (2017-2021) time series was classified into open water, vegetated water, and non-water at 20 m resolution using variables not only from Sentinel-1 and Sentinel-2, but also variables derived from topographic and weather datasets. The Sentinel-1 model...
Categories: Data;
Tags: Aquatic Biology,
Arizona,
Arkansas,
California,
Delaware, All tags...
Delmarva Peninsula,
Google Earth Engine,
Hydrology,
Iowa,
Kansas,
Louisiana,
Maryland,
Minnesota,
Missouri,
Montana,
North Dakota,
Prairie Pothole Region,
Remote Sensing,
South Carolina,
South Dakota,
Texas,
USGS Science Data Catalog (SDC),
United States,
Water Quality,
climate,
inundation frequency,
lakes,
python,
streams,
surface water,
wetlands, Fewer tags
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