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These data include 217 median groundwater elevations computed from compiled measurements made in the year 2010 within the transboundary Mesilla/Conejos-Médanos Basin, United States and Mexico, along with their corresponding interpolated groundwater elevations and standard errors from the application of kriging. Of the 217 median groundwater elevation locations, 109 were in the United States and 108 were in Mexico. Considered measurements were limited to wells thought to be completed in the basin-fill/Santa Fe Group aquifer based on well records. This dataset includes a comma-separated values file (Control_points.csv) that provides the median groundwater elevations that were kriged to yield rasters of estimated groundwater...
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This digital elevation model provides a tool for calibrating tsunami risk to observations of the 1945 Makran tsunami in Karachi Harbour. The DEM bathymetry is derived from soundings made mainly during the first eight years after the tsunami. Although deficient in portraying intertidal backwaters and upland topography, the DEM accurately depicts the sheltered setting of one of the two tide gauges that recorded the 1945 tsunami.
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This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Carlisle 30 x 60 minute quadrangle in Pennsylvania. The source data used to construct this imagery consists of 1-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2019 and 2020 and downloaded from the USGS National Map TNM Download. The data were processed using geographic information systems (GIS) software. The data is projected in WGS 1984 Web Mercator. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief according to a topographic position index (TPI) calculation.
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Freshwater Introduction South of Highway 82 (ME-16) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Oyster Bayou Marsh Creation and Terracing (CS-59) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within...
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The Louisiana State Legislature created Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Highway 384 Hydrologic Restoration (CS-21) project for 2015. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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The Louisiana State Legislature created Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the East Sabine Lake Hydrologic Restoration (CS-32) project for 2015. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Bayou Dupont Marsh and Ridge Creation (BA-48) project for 2016. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within...
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The U.S. Geological Survey in cooperation with the Grand River Dam Authority completed a high-resolution multibeam bathymetric survey to compute a new capacity and surface-area table. The capacity and surface-area tables describe the relation between the elevation of the water surface and the volume of water that can be impounded at each given water-surface elevation. The capacity and surface area of Grand Lake O’ the Cherokees were computed from a Triangular Irregular Network (TIN) surface created in Global Mapper Version 21.0.1. The TIN surface was created from three datasets: (1) a multibeam bathymetric survey of Grand Lake O’ the Cherokees in 2019 (Hunter and others 2020), (2) a 2017 USGS bathymetric survey...
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The U.S. Geological Survey (USGS) computed rasters of pre-solved values for the watersheds draining to the pixel delineation point representing the watershed's percent forested land cover from the National Land Cover Dataset (NLCD) 2016 data (land cover values 41-43). These values, which cover the conterminous United States at a scale of 30m pixel size, will be served in the National StreamStats Fire-Hydrology application to describe delineated watersheds ( https://streamstats.usgs.gov/ ). The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate...
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This data set represents initial forest communities developed for Isle Royale National Park. LANDIS-II requires an input data layer that contains the ages of each species cohort present within each cell of the landscape. To develop this layer, we matched the composition of forest inventory plots to a map of forest types, and randomly imputed U.S. Department of Agriculture Forest Inventory plots within each matching forest type
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for tidal marsh areas around San Francisco Bay using the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). Survey-grade GPS survey data (6614 points), NAIP-derived Normalized Difference Vegetation Index, and original 1 m lidar DEM from 2010 were used to generate a model of predicted bias across tidal marsh areas. The predicted bias was then subtracted from the original lidar DEM and merged with the NOAA...
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This dataset was produced by the US Geological Survey as a supporting dataset to be used for the purpose of calculating stream gage basin characteristics in preparation for the South Carolina StreamStats application. This integer raster dataset represents runoff curve numbers for the combinations of hydrological soils groupings and land cover types within the South Carolina StreamStats study area. Soils data are from the USDA, NRCS SSURGO soils database and land cover data are USGS 2019 NLCD data. The dataset will be used in peak flow regression equations that are used to predict flow in South Carolina streams. The StreamStats application provides access to spatial analytical tools that are useful for water-resources...
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The U.S. Geological Survey (USGS) computed rasters of pre-solved values for the watersheds draining to the pixel delineation point representing the watershed's mean maximum and minimum January temperature from PRISM 1981-2010 4km data (resampled to 30m resolution). These values, which cover the conterminous United States, will be served in the National StreamStats Fire-Hydrology application to describe delineated watersheds (https://streamstats.usgs.gov/). The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate drainage areas, to retrieve basin...
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The Louisiana State Legislature created Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Grand Liard Marsh and Ridge Restoration (BA-68) project for 2016. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Cameron-Creole Maintenance (CS-04a) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their project boundary....
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Pecan Island Terracing (ME-14) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their project...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Roanoke 30 x 60 minute quadrangle in Virginia. It also covers a part of the Appalachian Basin Province. The source data used to construct this imagery consists of 1-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2017 and 2021 and downloaded from the USGS National Map TNM Download. The data were processed using geographic information systems (GIS) software. The data spatial reference is the WGS 1984 geographic coordinate system. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief...
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Of the approximately 6.6 million people living in the Mississippi embayment (MISE) region in the central United States, approximately 65 percent rely on groundwater for their drinking water (Dieter, Linsey, and others, 2017). Regional assessments of water quality in principal aquifer systems provide context for the long-term availability of these water resources for drinking-water supplies. To assess the current (2018) status of water quality in MISE in relation to drinking water supplies, groundwater withdrawal zones used for domestic and public supply were modeled using available groundwater well and hydrogeologic framework data. Three dimensional surfaces were modeled to map the depth zones at which groundwater...


map background search result map search result map Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour Highway 384 Hydrologic Restoration (CS-21): 2015 land-water classification LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 Grand Liard Marsh and Ridge Restoration (BA-68): 2016 land-water classification Bayou Dupont Marsh and Ridge Creation (BA-48): 2016 land-water classification East Sabine Lake Hydrologic Restoration (CS-32): 2015 land-water classification Groundwater withdrawal zones for drinking water from the Mississippi River Valley alluvial aquifer and Mississippi embayment aquifers Data release of Bathymetric Map, Surface Area, and Capacity of Grand Lake O' the Cherokees, Northeastern Oklahoma, 2019 Isle Royal National Park (ISRO): Initial Forest Communities of Isle Royale National Park Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Pre-computed mean January maximum and minimum temperature rasters from PRISM 1981-2010 from the conterminous United States, for the StreamStats Fire-Hydrology application 2021 Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States Cameron-Creole Maintenance (CS-04a) 2018 land-water classification Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Estimated groundwater elevations and standard errors from the application of kriging to median groundwater elevation data from 2010 in the Mesilla/Conejos-Médanos Basin, United States and Mexico Oyster Bayou Marsh Creation and Terracing (CS-59): 2018 land-water classification Pecan Island Terracing (ME-14): 2018 land-water classification Gridded South Carolina StreamStats Runoff Curve Numbers by NLCD Landcover and SSURGO Soils Class Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Roanoke 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Bayou Dupont Marsh and Ridge Creation (BA-48): 2016 land-water classification Oyster Bayou Marsh Creation and Terracing (CS-59): 2018 land-water classification Grand Liard Marsh and Ridge Restoration (BA-68): 2016 land-water classification Highway 384 Hydrologic Restoration (CS-21): 2015 land-water classification Pecan Island Terracing (ME-14): 2018 land-water classification Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour East Sabine Lake Hydrologic Restoration (CS-32): 2015 land-water classification Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Cameron-Creole Maintenance (CS-04a) 2018 land-water classification Data release of Bathymetric Map, Surface Area, and Capacity of Grand Lake O' the Cherokees, Northeastern Oklahoma, 2019 Enhanced Terrain Imagery of the Roanoke 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Isle Royal National Park (ISRO): Initial Forest Communities of Isle Royale National Park LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 Estimated groundwater elevations and standard errors from the application of kriging to median groundwater elevation data from 2010 in the Mesilla/Conejos-Médanos Basin, United States and Mexico Gridded South Carolina StreamStats Runoff Curve Numbers by NLCD Landcover and SSURGO Soils Class Groundwater withdrawal zones for drinking water from the Mississippi River Valley alluvial aquifer and Mississippi embayment aquifers Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Pre-computed mean January maximum and minimum temperature rasters from PRISM 1981-2010 from the conterminous United States, for the StreamStats Fire-Hydrology application 2021 Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States