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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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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 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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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey prepared a geospatial raster dataset describing impervious surface in the SC StreamStats study area derived from the 30m resolution National Land Cover Dataset (NLCD) 2019. This layer, which covers the SC StreamStats study area, has been resampled from the source resolution to a scale of 30ft pixels and reprojected to the common projection of the other project data layers (SC State Plane NAD 1983 International Feet WKID 2273). It will be served as part of the SC StreamStats application (https://streamstats.usgs.gov) to describe delineated watersheds. The StreamStats application provides access to spatial analytical tools...
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We created a single map of surface water presence by intersecting water classes from available land cover products (National Wetland Inventory, Gap Analysis Program, National Land Cover Database, and Dynamic Surface Water Extent) across the U.S. state of Arizona. We derived classified samples for four wetland classes from the harmonized map: water, herbaceous wetlands, wooded wetlands, and non-wetland cover. In Google Earth Engine (GEE) we developed a random forest model that combined the training data with spatially explicit predictor variables of vegetation greenness indices, wetness indices, seasonal index variation, topographic variables, and hydrologic parameters. The final product is a wall-to-wall map of...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Radford 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 2018 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...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Beckley 30 x 60 minute quadrangle in West Virginia, Virginia and Kentucky. 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 2020 and 2022. 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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This USGS Data Release represents geospatial and tabular data for the Nisqually River Delta historical habitat mapping. The data release was produced in compliance with the new 'open data' requirements as a way to make the scientific products associated with USGS research efforts and publications available to the public. The dataset consists of 9 separate items: 1. Forest Change (raster dataset) 2. Forest Type Change (raster dataset) 3. Functional Pathway Change (raster dataset) 4. 1957 Habitat Map (raster dataset) 5. 1980 Habitat Map (raster dataset) 6. 2015 Habitat Map (raster dataset) 7. 1980 Species Map (raster dataset) 8. 2015 Species Map (raster dataset) 9. Wetland Change (raster dataset) These data support...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Pittsburgh East 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 2020 and 2021 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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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Johnstown 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 in 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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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Lewisburg 30 x 60 minute quadrangle in Virginia and West Virginia. 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 2020 and 2021. 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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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Cumberland 30 x 60 minute quadrangle in Pennsylvania, West Virginia and Maryland. The source data used to construct this imagery consists of 1-meter lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2019 and 2023. The data were processed using geographic information systems (GIS) software. The data is projected in WGS 1984. 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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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Marlinton 30 x 60 minute quadrangle in West Virginia. 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 2020 and 2021. 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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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Bluefield 30 x 60 minute quadrangle in West Virginia and Virginia. The source data used to construct this imagery consists of 1-meter lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2020 and 2022. 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.


    map background search result map search result map Historical Time-series Classification of Habitat for 1957, 1980 and 2015 in the Nisqually River Delta, Washington DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Lookout, NC, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Hatteras, NC, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014 Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States Impervious Land Cover Raster Derived from the National Land Cover Dataset (NLCD) 2019 for South Carolina StreamStats 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 Johnstown 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Pittsburgh East 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Radford 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Wetlands in the state of Arizona Enhanced Terrain Imagery of the Lewisburg 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Cumberland 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Marlinton 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Bluefield 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Beckley 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Lookout, NC, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Hatteras, NC, 2014 Enhanced Terrain Imagery of the Cumberland 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Marlinton 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Bluefield 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Radford 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Pittsburgh East 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Johnstown 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Lewisburg 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 Enhanced Terrain Imagery of the Beckley 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Historical Time-series Classification of Habitat for 1957, 1980 and 2015 in the Nisqually River Delta, Washington Impervious Land Cover Raster Derived from the National Land Cover Dataset (NLCD) 2019 for South Carolina StreamStats Wetlands in the state of Arizona Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States