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Klamath Marsh January Through June Maximum Surface Water Extent, 1985-2021

Metadata Updated: November 26, 2025

The U.S. Geological Survey Oregon Water Science Center, in cooperation with The Klamath Tribes initiated a project to understand changes in surface-water prevalence of Klamath Marsh, Oregon and changes in groundwater levels within and surrounding the marsh. The initial phase of the study focused on developing datasets needed for future interpretive phases of the investigation. This data release documents the creation of a geospatial dataset of January through June maximum surface-water extent (MSWE) based on a model developed by Jones (2015; 2019) to detect surface-water inundation within vegetated areas from satellite imagery. The Dynamic Surface Water Extent (DSWE) model uses Landsat at-surface reflectance imagery paired with a digital elevation model to classify pixels within a Landsat scene as one of the following types: “not water”, “water – high confidence”, “water – moderate confidence”, “wetland – moderate confidence”, “wetland – low confidence”, and “cloud/shadow/snow” (Jones, 2015; Walker and others, 2020). The model has been replicated by Walker and others (2020) for use within the Google Earth Engine (GEE, https://code.earthengine.google.com/) online geospatial processing platform. The GEE platform was used to create 37 annual composite raster images of maximum surface water inundation within the Klamath Marsh during January through June 1985–2021. The dataset presented here includes surface area calculations of January through June MSWE in tabular (.csv) format, 37 years of composite January through June MSWE datasets in raster (.tif) and vector (.shp) format, and a study area polygon in vector (.shp) format. References Cited: Jones, J.W., 2015, Efficient Wetland Surface Water Detection and Monitoring via Landsat: Comparison with in situ Data from the Everglades Depth Estimation Network. Remote Sensing, 7, 12503–12538. Jones, J.W., 2019, Improved Automated Detection of Subpixel-Scale Inundation—Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests. Remote Sensing, 11, 374. https://doi.org/10.3390/rs11040374 Walker, J.J., Petrakis, R.E., and Soulard, C.E., 2020, Implementation of a Surface Water Extent Model using Cloud-Based Remote Sensing - Code and Maps: U.S. Geological Survey data release, https://doi.org/10.5066/P9LH9YYF.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date September 12, 2025
Metadata Updated Date November 26, 2025

Metadata Source

Harvested from DOI USGS DCAT-US

Additional Metadata

Resource Type Dataset
Metadata Created Date September 12, 2025
Metadata Updated Date November 26, 2025
Publisher U.S. Geological Survey
Maintainer
Identifier http://datainventory.doi.gov/id/dataset/usgs-63ff8b5ad34e176a2a34f8be
Data Last Modified 2024-08-01T00:00:00Z
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://ddi.doi.gov/usgs-data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id b4c910fe-fb77-4fa8-8ea1-a43ab49a59be
Harvest Source Id 2b80d118-ab3a-48ba-bd93-996bbacefac2
Harvest Source Title DOI USGS DCAT-US
Metadata Type geospatial
Source Datajson Identifier True
Source Hash 4e5a38ec4e086f8267c0077eb8940dcabbf1a6f9ad450f73ffd48cd73cb1bffd
Source Schema Version 1.1

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