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The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release, and other associated...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Coast, CMGP, Caribbean, Coastal Research and Planning Institute of Puerto Rico, Coastal and Marine Geology Program, All tags...
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This dataset is associated with a USGS publication "Assessment of Undiscovered Oil and Gas Resources in the Eagle Ford Group and Associated Cenomanian-Turonian Strata, U.S. Gulf Coast, Texas, 2018" and summarizes data generated by the author for the publication using IHS Harmony DeclinePlus software. Data includes average estimated ultimate recoveries per square mile for three continuous oil assessment units with location information. Data is derived from IHS Markit data. No proprietary information is contained in this release.


    map background search result map search result map Shorelines for Vieques, Culebra, and the main island of Puerto Rico from the 1900s to 2018 (ver. 2.0, March 2023) Estimated Ultimate Recoveries of Oil Wells in the Eagle Ford Group and Associated Cenomanian–Turonian Strata, U.S. Gulf Coast, Texas, 2018 Shorelines for Vieques, Culebra, and the main island of Puerto Rico from the 1900s to 2018 (ver. 2.0, March 2023) Estimated Ultimate Recoveries of Oil Wells in the Eagle Ford Group and Associated Cenomanian–Turonian Strata, U.S. Gulf Coast, Texas, 2018