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As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey developed a suite of high-resolution lidar-derived raster datasets for the Greater Raleigh Area, North Carolina, using repeat lidar data from the years 2013, 2015, and 2022. These datasets include raster representations of digital elevation models (DEMs), DEM of difference, the ten most common geomorphons (i.e. geomorphologic feature), lidar point density, and positive topographic openness. Raster footprints vary by year based on extent of lidar data collection. All files are available as Cloud Optimized GeoTIFF, meaning they are formatted to work on the cloud or can be directly downloaded. These metrics have been...
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The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the National Hydrography Dataset (NHD), National Watershed Boundary Dataset (WBD), and 3D Elevation Program Digital Elevation Model (3DEP DEM). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to a data suite that includes the NHD stream network with linear referencing functionality, the WBD hydrologic units, elevation-derived catchment areas for each stream segment, "value added attributes" (VAAs), and other features that enhance hydrologic data analysis and routing.
Tags: AK, Alaska, Downloadable Data, Esri File GeoDatabase 10, FileGDB, All tags...
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The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the National Hydrography Dataset (NHD), National Watershed Boundary Dataset (WBD), and 3D Elevation Program Digital Elevation Model (3DEP DEM). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to a data suite that includes the NHD stream network with linear referencing functionality, the WBD hydrologic units, elevation-derived catchment areas for each stream segment, "value added attributes" (VAAs), and other features that enhance hydrologic data analysis and routing.
Tags: AK, Alaska, Downloadable Data, Esri File GeoDatabase 10, FileGDB, All tags...
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The Middle Fork Willamette River basin encompasses 3,548 square kilometers of western Oregon and drains to the mainstem Willamette River. Fall Creek basin encompasses 653 square kilometers and drains to the Middle Fork Willamette River. In cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey evaluated geomorphic responses of downstream river corridors to annual drawdowns to streambed at Fall Creek Lake. This study of geomorphic change is focused on the major alluvial channel segments downstream of the U.S. Army Corps of Engineers’ dams on Fall Creek and the Middle Fork Willamette River, as well as the 736 hectare Fall Creek Lake. Reservoir erosion during streambed drawdown results in sediment...
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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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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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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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMHRP, Coastal Erosion, All tags...
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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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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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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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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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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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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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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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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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Digital flood-inundation maps for a 9.9-mile reach of Dardenne Creek, St. Charles County, Missouri, were created by the U.S. Geological Survey (USGS) in cooperation with St. Charles County, Missouri Department of Transportation, and the cities of O'Fallon and St. Peters, Missouri. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Program at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to select water levels (stages) at the USGS streamgages 05514860 Dardenne Creek at Old Town St. Peters, Missouri, and 05587450 Mississippi River at Grafton, Illinois. Near-real-time stages at these streamgages may...
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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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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...
This study applies spatial analyses to examine the consequences of accelerated urban expansion on a hydrologic system over a period of 24 years. Three sets of historical aerial photos are used in a GIS analysis to document the geomorphic history of Las Vegas Wash, which drains the rapidly growing Las Vegas urban area in southern Nevada. New spatial techniques are introduced to make quantitative measurements of the erosion at three specific time intervals in the hydrologic evolution of the channel and floodplain. Unlike other erosion studies that use two different elevation surfaces to assess erosion, this study used a single elevation surface to remove systematic and nonsystemic elevation errors. The spatial analysis...
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These polygon boundaries, inundation extents, and depth rasters were created to provide an extent of flood inundation along the Lumber River within the community of Fair Bluff, North Carolina. The upstream and downstream reach extent is determined by the location of high-water marks, not extending the boundary far past the outermost high-water marks. In areas of uncertainty of flood extent, the model boundary is lined up with the flood inundation polygon extent. This boundary polygon was used to extract the final flood inundation polygon and depth layer from the flood water surface raster file. The passage of Hurricane Matthew through central and eastern North Carolina during October 7-9, 2016, brought heavy rainfall...


map background search result map search result map Lumber River at Fair Bluff, North Carolina Flood Map Files from October 2016 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2012 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 DisOcean: Distance to the ocean: Monomoy Island, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Cape Lookout, NC, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014 DisOcean: Distance to the ocean: 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: Wreck Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014 Agisoft output report for structure-from-motion datasets for Fall Creek Lake, Oregon, during annual drawdown to streambed November 9, 2016 Flood-Inundation Shapefile for Dardenne Creek, St. Charles County, Missouri, 2019 Lidar-derived rasters of point density, elevation, and geomorphological features for 2013, 2015, and 2022 for the Greater Raleigh Area, North Carolina USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 8 - 19060501 (published 20220712) USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 8 - 19060505 (published 20220927) FileGDB DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Wreck Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 Lumber River at Fair Bluff, North Carolina Flood Map Files from October 2016 Agisoft output report for structure-from-motion datasets for Fall Creek Lake, Oregon, during annual drawdown to streambed November 9, 2016 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 DisOcean: Distance to the ocean: Smith Island, VA, 2014 Flood-Inundation Shapefile for Dardenne Creek, St. Charles County, Missouri, 2019 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 DisOcean: Distance to the ocean: Monomoy Island, MA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014 Lidar-derived rasters of point density, elevation, and geomorphological features for 2013, 2015, and 2022 for the Greater Raleigh Area, North Carolina ElevMHW: Elevation adjusted to local mean high water: Cape Lookout, NC, 2014 USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 8 - 19060501 (published 20220712) USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 8 - 19060505 (published 20220927) FileGDB