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The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical...
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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...
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This layer represents fundamentally suitable and unsuitable habitat for freshwater mussels in the Meramec Basin as modeled by these authors on May 17, 2017 based on spatial data ranging from 1990 to 2014. Identification of habitat characteristics associated with the presence of freshwater mussels is challenging but crucial for the conservation of this declining fauna. Most mussel species are found in multi-species assemblages suggesting that physical factors influence presence similarly across species. In lotic environments, geomorphic and hydraulic characteristics appear to be important factors for predicting mussel presence. We used maximum entropy (MaxEnt) modeling to evaluate hydrogeomorphic variables associated...
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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...
This data provides locations and technical specifications of the current version of the United States Wind Turbines database. Each release, typically done quarterly, updates the database with newly installed wind turbines, removes wind turbines that have been identified as dismantled, and applies other verifications based on updated imagery and ongoing quality-control. Turbine data were gathered from the Federal Aviation Administration's (FAA) Digital Obstacle File (DOF) and Obstruction Evaluation Airport Airspace Analysis (OE-AAA), the American Clean Power Association (ACP), Lawrence Berkeley National Laboratory (LBNL), and the United States Geological Survey (USGS), and were merged and collapsed into a single...
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The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical...
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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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The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in 2040) or to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. Geospatial data provided in...
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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...
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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.
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Salt marshes of the Northeastern United States (Maine to Virginia) are vulnerable to loss given their history of intensive human alteration. One direct human modification – ditching – was common across the Northeast for salt hay farming since European Colonization and for mosquito control in the first half of the 20th century. We hand-digitized linear ditches across Northeastern intertidal emergent wetlands from contemporary aerial imagery within the bounds of the National Wetland Inventory's Estuarine Intertidal Emergent Wetland areas.
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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...
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The CoRE (Contractions or Range Expansions) database contains a library of published literature and data on species range shifts in response to climate change. Through a systematic review of publications returned from searches on Google Scholar, Web of Science, and Scopus, we selected primary research articles that documented or attempted to document species-level distribution shifts in animal or plant species in response to recent anthropogenic climate change. We extracted data in four broad categories: (i) basic study information (study duration, location, data quality and methodological factors); (ii) basic species information (scientific names and taxonomic groups); (iii) information on the observed range shifts...
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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: Accretion, Atlantic Coast, CMGP, Caribbean, Coastal Research and Planning Institute of Puerto Rico, All tags...
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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...
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The U.S. Geological Survey, in cooperation with the National Park Service, Yellowstone Center for Resources, as part of work for the Yellowstone Volcano Observatory, has compiled a shapefile map of thermal areas and thermal water bodies in Yellowstone National Park. A thermal area is a continuous, or nearly continuous, geologic unit that contains one or more thermal features (e.g., hot springs, mud pots, or fumaroles); hydrothermally altered rocks and/or hydrothermal mineral deposits; heated ground and/or geothermal gas emissions; and is generally barren of vegetation or has stressed / dying vegetation. There are more than 10,000 thermal features in Yellowstone, most of which are clustered together into about 120...


    map background search result map search result map Niche model results predicting fundamentally suitable and unsuitable habitat for freshwater mussel concentrations in the Meramec Basin United States Wind Turbine Database - Current Version (ver. 7.0, May 2024) Shorelines for Vieques, Culebra, and the main island of Puerto Rico from the 1900s to 2018 (ver. 2.0, March 2023) Baseline for the coast of Puerto Rico's main island generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023) Shoreline change rates for the coast of Puerto Rico's main island calculated using the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023) Shoreline intersects for the coast of Puerto Rico's main island generated by the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023) Baseline for the islands of of Vieques and Culebra, Puerto Rico, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Shoreline change rates for the islands of Vieques and Culebra, Puerto Rico, calculated using the Digital Shoreline Analysis System version 5.1 Shoreline intersects for the islands of Vieques and Culebra, Puerto Rico, calculated using the Digital Shoreline Analysis System version 5.1 Shapefile of Areal Reduction Factor (ARF) regions for the state of Florida (ARF_regions.shp) Shapefile of NOAA Atlas 14 stations in Florida (Atlas14_stations.shp) Shapefile of climate regions for the state of Florida (Climate_regions.shp) Estimated Ultimate Recoveries of Oil Wells in the Eagle Ford Group and Associated Cenomanian–Turonian Strata, U.S. Gulf Coast, Texas, 2018 Map of Yellowstone’s Thermal Areas: Updated 2023-12-31 Linear Ditches of Northeastern U.S. Coastal Marshes from Maine to Virginia Derived from 2023 2D Aerial Imagery Basemap Shoreline intersects for the islands of Vieques and Culebra, Puerto Rico, calculated using the Digital Shoreline Analysis System version 5.1 Shoreline change rates for the islands of Vieques and Culebra, Puerto Rico, calculated using the Digital Shoreline Analysis System version 5.1 Baseline for the islands of of Vieques and Culebra, Puerto Rico, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Niche model results predicting fundamentally suitable and unsuitable habitat for freshwater mussel concentrations in the Meramec Basin Map of Yellowstone’s Thermal Areas: Updated 2023-12-31 Estimated Ultimate Recoveries of Oil Wells in the Eagle Ford Group and Associated Cenomanian–Turonian Strata, U.S. Gulf Coast, Texas, 2018 Shapefile of NOAA Atlas 14 stations in Florida (Atlas14_stations.shp) Shapefile of Areal Reduction Factor (ARF) regions for the state of Florida (ARF_regions.shp) Shapefile of climate regions for the state of Florida (Climate_regions.shp) Linear Ditches of Northeastern U.S. Coastal Marshes from Maine to Virginia Derived from 2023 2D Aerial Imagery Basemap United States Wind Turbine Database - Current Version (ver. 7.0, May 2024)