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This dataset is comprised of three files containing northing, easting, and elevation ("XYZ") information for light detection and ranging (LiDAR) data representing beach topography and sonar data representing near-shore bathymetry of Lake Superior at Minnesota Point, Duluth, Minnesota. The point data is the same as that in LAS (industry-standard binary format for storing large point clouds) files that were used to create a digital elevation model (DEM) of the approximately 5.9 square kilometer (2.3 square mile) surveyed area. LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019). Multi-beam sonar data were collected...
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Investigations of coastal change and coastal resources often require continuous elevation profiles from the seafloor to coastal terrestrial landscapes. Differences in elevation data collection in the terrestrial and marine environments result in separate elevation products that may not share a vertical datum. This data release contains the assimilation of multiple elevation products into a continuous digital elevation model at a resolution of 3-arcseconds (approximately 90 meters) from the terrestrial landscape to the seafloor for the contiguous U.S., focused on the coastal interface. All datasets were converted to a consistent horizontal datum, the North American Datum of 1983, but the native vertical datum for...
Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Alabama, CMGP, California, Canadian Hydrographic Service, Chesapeake Bay, All tags...
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This dataset contains the Flow Accumulation (FA) grid for the Asian continent from the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The DEM data were developed and distributed by processing units. There are 19 processing units for Asia. The distribution files have the number of the processing unit appended to the end of the zip file name (e.g. as_dem_3_2.zip contains the DEM data for unit 3-2). The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment...
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This dataset contains the Digital Elevation Model (DEM) for Australasia from the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The data were developed and distributed by processing units. There are 11 processing units for Australasia. The distribution files have the number of the processing unit appended to the end of the zip file name (e.g. au_dem_3_2.zip contains the DEM data for unit 3-2). The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment...
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The basis for these features is U.S. Geological Survey Scientific Investigations Report 2017-5024 Flood Inundation Mapping Data for Johnson Creek near Sycamore, Oregon. The domain of the HEC-RAS hydraulic model is a 12.9-mile reach of Johnson Creek from just upstream of SE 174th Avenue in Portland, Oregon, to its confluence with the Willamette River. Some of the hydraulics used in the model were taken from Federal Emergency Management Agency, 2010, Flood Insurance Study, City of Portland, Oregon, Multnomah, Clackamas, and Washington Counties, Volume 1 of 3, November 26, 2010. The Digital Elevation Model (DEM) utilized for the project was developed from lidar data flown in 2015 and provided by the Oregon Department...
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​The basis for these features is U.S. Geological Survey Scientific Investigations Report 2017-5024 Flood Inundation Mapping Data for Johnson Creek near Sycamore, Oregon. The domain of the HEC-RAS hydraulic model is a 12.9-mile reach of Johnson Creek from just upstream of SE 174th Avenue in Portland, Oregon, to its confluence with the Willamette River. Some of the hydraulics used in the model were taken from Federal Emergency Management Agency, 2010, Flood Insurance Study, City of Portland, Oregon, Multnomah, Clackamas, and Washington Counties, Volume 1 of 3, November 26, 2010. The Digital Elevation Model (DEM) utilized for the project was developed from lidar data flown in 2015 and provided by the Oregon Department...
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This dataset contains the Digital Elevation Model (DEM) for Africa from the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The DEM data were developed and distributed by processing units. There are 19 processing units for Africa. The distribution files have the number of the processing unit appended to the end of the zip file name (e.g. af_dem_3_2.zip contains the DEM data for unit 3-2). The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment...
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This contains the South American portion of the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment boundaries. The coverage of the data is global (-180º, 180º, -90º, 90º) with the underlying DEM being a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) and...
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The data contained in this file is one of several datasets produced in support of the project entitled “Classification and Mapping of Cave and Karst Resources” for the region encompassing the Appalachian Landscape Conservation Cooperative (LCC). The results of this project are divided into a series of geospatial information layers (shapefiles and raster data). The files provide a comprehensive overview of data availability on obligate cave-dwelling fauna and bat ranges useful for examining relationships between environmental factors and biological diversity and distribution within karst areas of the Appalachian LCC.
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This contains the Australasian portion of the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment boundaries. The coverage of the data is global (-180º, 180º, -90º, 90º) with the underlying DEM being a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) and the...
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This dataset is a digital elevation model (DEM) of the beach topography of Lake Superior at Minnesota Point, Duluth, Minnesota. The DEM has a 1-meter (m; 3.28084 foot [ft]) cell size and was created from a LAS (industry-standard binary format for storing large point clouds) dataset of terrestrial light detection and ranging (LiDAR) data with an average point spacing of 0.137 m (0.45 ft). LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019). References: Huizinga, R.J. and Wagner, D.M., 2019, Erosion monitoring along selected bank locations of the Coosa River in Alabama using terrestrial light detection and ranging...
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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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These data were compiled to provide a resource for other researchers interested in water-surface elevations and flow velocity across a wide range of discharge in the study reach for the project. Objective(s) of our study were to construct a two-dimensional hydrodynamic model for the 15.8 mile tailwater reach of the Colorado River in Glen Canyon between Glen Canyon Dam and Lees Ferry, Arizona. These data represent the results of the two-dimensional modeling effort with each data table (50) including the results of each run of the model. Additionally, other data represent a comparison of modeled water surface elevations to measured water surface elevations for historic Bureau of Reclamation cross sections in the study...
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These topographic/bathymetric digital elevation models (DEMs) were collected and compiled to characterize erosion and deposition in the Colorado River and in an adjacent zone of laterally recirculating flow (eddy) during both average flow conditions and during a controlled flood that occurred in March 2008. The objectives of the study were to measure changes sandbar morphology that occurred during changes in discharge associated with the controlled flood. These data were collected between February 6 and March 31, 2008 in a 1-mile study reach on the Colorado River within Grand Canyon National Park beginning 44.5 miles downstream from Lees Ferry, Arizona. These data were collected by the USGS Grand Canyon Monitoring...
Tags: Arizona, Colorado River, Eminence Break, Eminence Break field site, Glen Canyon Dam, All tags...
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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...


map background search result map search result map Shuttle Radar Topography Mission (SRTM) elevation interpolated at 1 km resolution across the Appalachian Landscape Conservation Cooperative (LCC) region Elevation artifacts in digital bathymetric and topographic models for United States east (east_cdem_v1.tif) and west (west_cdem_v.tif) coasts (polygon shapefile, geographic, NAD83) Areas of uncertainty for flood inundation extents at gage 14211500, Johnson Creek near Sycamore, Oregon (sycor_breach.shp) Flood inundation depth for a flow of 2,578 cfs (stage 15) at gage 14211500, Johnson Creek near Sycamore, Oregon (sycor_15.tif) Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South America Digital Elevation Model (DEM) from the Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- Africa ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014 Digital elevation model (DEM) of beach topography of Lake Superior at Minnesota Point, Duluth, MN, August 2019 XYZ files of LiDAR and sonar data collected at Lake Superior at Minnesota Point, Duluth, MN, August 2019 Vegetation classification model (Veg) for basin A1 Digital terrain model (DTM) for basin B1 Final surface model (SRF) for basin B1 Digital Elevation Models (DEM) Data Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: tables of model results and accuracy assessment Vegetation classification model (Veg) for basin A1 Digital terrain model (DTM) for basin B1 Final surface model (SRF) for basin B1 Digital elevation model (DEM) of beach topography of Lake Superior at Minnesota Point, Duluth, MN, August 2019 XYZ files of LiDAR and sonar data collected at Lake Superior at Minnesota Point, Duluth, MN, August 2019 Areas of uncertainty for flood inundation extents at gage 14211500, Johnson Creek near Sycamore, Oregon (sycor_breach.shp) Flood inundation depth for a flow of 2,578 cfs (stage 15) at gage 14211500, Johnson Creek near Sycamore, Oregon (sycor_15.tif) Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: tables of model results and accuracy assessment Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Digital Elevation Models (DEM) Data Shuttle Radar Topography Mission (SRTM) elevation interpolated at 1 km resolution across the Appalachian Landscape Conservation Cooperative (LCC) region Elevation artifacts in digital bathymetric and topographic models for United States east (east_cdem_v1.tif) and west (west_cdem_v.tif) coasts (polygon shapefile, geographic, NAD83) Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South America Digital Elevation Model (DEM) from the Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- Africa