Data release for climate change impacts on surface water extents across the central United States

Principal Investigator(s):  View help for Principal Investigator(s) U.S. Geological Survey; Heather E Golden; Charles R Lane; Laurie C Alexander; Jay R Christensen; Melanie K Vanderhoof

Version:  View help for Version V1

Name File Type Size Last Modified
metadata_Vanderhoof_etal_surface_water_climate_change.xml application/xml 15.6 KB 11/13/2025 08:53:AM
surface_water_extent_2017_2021.zip application/zip 437.8 MB 11/13/2025 08:58:AM

Project Citation: 

U.S. Geological Survey, Golden, Heather E , Lane, Charles R, Alexander, Laurie C, Christensen, Jay R, and Vanderhoof, Melanie K. Data release for climate change impacts on surface water extents across the central United States. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-11-13. https://doi.org/10.3886/E240262V1

Project Description

Project Title:  View help for Project Title Data release for climate change impacts on surface water extents across the central United States
Summary:  View help for Summary 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 was developed distinct from the Sentinel-2 model to enable the two time series to be integrated into a single high-frequency time series, while open water and vegetated water were both mapped to retain mixed pixel inundation. Results were validated against 7,200 visually inspected points derived from WorldView and PlanetScope imagery. Classification accuracy for open water was high across the 5-year period, with an omission and commission error of only 3.1% and 0.9% for Sentinel-1 and 3.1% and 0.5% for Sentinel-2, respectively. Vegetated water accuracy was lower, as expected given that the class represents mixed pixels. Sentinel-2 showed higher accuracy (10.7% omission and 7.9% commission error) relative to Sentinel-1 (28.4% omission and 16.0% commission error). Our results demonstrated that Sentinel-1 and Sentinel-2 time series can be integrated to improve the temporal resolution when mapping open and vegetated waters, although sensor-specific differences, such as sensitivity to vegetation structure versus pixel color, complicate the data integration for subpixel, vegetated water compared with open water.
Original Distribution URL:  View help for Original Distribution URL https://www.sciencebase.gov/catalog/item/64c80b47d34e70357a349f08

Scope of Project

Subject Terms:  View help for Subject Terms Climatology; Hydrology; Remote Sensing; Water Resources; United States; Midwest; Southeast; Southwest
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 1/1/2017 – 12/31/2021
Universe:  View help for Universe surface water extents in Arkansas, Iowa, Louisiana, Midwest, Minnesota, Missouri, North Dakota, Oklahoma, South Dakota, and Texas
Data Type(s):  View help for Data Type(s) geographic information system (GIS) data
Collection Notes:  View help for Collection Notes Date downloaded: 2025-11-13


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