Filters: Tags: digital elevation models (X)
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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...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
DEM,
Duluth,
Great Lakes,
Hydroacoustic,
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,
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...
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...
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...
Types: Citation;
Tags: Johnson Creek,
Portland, Oregon,
Willamette Valley,
digital elevation models,
floods,
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...
Categories: Data;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Johnson Creek,
Portland, Oregon,
Willamette Valley,
digital elevation models,
floods,
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...
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...
This data release presents beach topography and nearshore bathymetry data from repeated surveys in northern Monterey Bay, California to document changes in shoreline position and coastal morphology as they relate to episodic (storms), seasonal, and interannual and longer (e.g. El Niño) processes. The ongoing monitoring program was initiated in October 2014 with semi-annual surveys performed in late summer (September or October) and Spring (March). Nearshore bathymetry and topography data were collected along a series of shore-perpendicular transects spaced primarily at 50-250 m intervals between Santa Cruz and Moss Landing, California (fig. 1). The transects were located along sandy stretches of the coastline...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
CMGP,
Coastal and Marine Geology Program,
Echo Sounders,
GPS (Global Positioning System),
Digital elevation models (DEMs) of the lower Elwha River, Washington, were created by synthesizing lidar and PlaneCam Structure-from-Motion (SfM) data. Lidar and still digital photographs were collected by airplane during surveys from 2012 to 2016. The digital photographs were used to create a SfM digital surface model. Each DEM represents the ending conditions for that water year (for example, the 2013 DEM represents conditions at approximately September 30, 2013). The final DEMs, presented here, were created from the most recent lidar before September 30 of a given year, supplemented with an error-corrected SfM model from a low-flow summer Elwha PlaneCam flight as close to 30 September as possible. This synthetic...
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.
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...
This dataset presents 28 georeferenced orthomosaic images of the middle and lower reaches of the Elwha River. Each mosaic image was created by stitching together thousands of individual photographs that were matched based on numerous unique tie points shared by the photographs. The individual photographs were taken by a plane-mounted camera during multiple flights over the study area spanning 2012 to 2017. Because each mosaic is orthogonal to the earth's surface and is georeferenced to real-world coordinates, changes to the river channel and surrounding morphology can be seen and measured, including channel width, river braiding, bar formation, and other metrics to assess responses of the river to the removal of...
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the best available National Hydrography Dataset (NHD), the 10-meter 3D Elevation Program Digital Elevation Model (3DEP DEM), and the National Watershed Boundary Dataset (WBD). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to create a stream network with linear referencing, feature naming, "value added attributes" (VAAs), elevation-derived catchments, and other features for hydrologic data analysis. The stream network with linear referencing is a system of data relationships applied to hydrographic systems so that one stream reach "flows" into another and "events" can be tied to and traced...
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the best available National Hydrography Dataset (NHD), the 10-meter 3D Elevation Program Digital Elevation Model (3DEP DEM), and the National Watershed Boundary Dataset (WBD). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to create a stream network with linear referencing, feature naming, "value added attributes" (VAAs), elevation-derived catchments, and other features for hydrologic data analysis. The stream network with linear referencing is a system of data relationships applied to hydrographic systems so that one stream reach "flows" into another and "events" can be tied to and traced...
Vegetation classification model (Veg) and associated metadata for basin A1.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Colorado,
Rio Blanco,
UAS,
Unmanned Aerial Systems,
biota,
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the best available National Hydrography Dataset (NHD), the 10-meter 3D Elevation Program Digital Elevation Model (3DEP DEM), and the National Watershed Boundary Dataset (WBD). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to create a stream network with linear referencing, feature naming, "value added attributes" (VAAs), elevation-derived catchments, and other features for hydrologic data analysis. The stream network with linear referencing is a system of data relationships applied to hydrographic systems so that one stream reach "flows" into another and "events" can be tied to and traced...
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...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
DEM,
Duluth,
Great Lakes,
LAS,
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the best available National Hydrography Dataset (NHD), the 10-meter 3D Elevation Program Digital Elevation Model (3DEP DEM), and the National Watershed Boundary Dataset (WBD). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to create a stream network with linear referencing, feature naming, "value added attributes" (VAAs), elevation-derived catchments, and other features for hydrologic data analysis. The stream network with linear referencing is a system of data relationships applied to hydrographic systems so that one stream reach "flows" into another and "events" can be tied to and traced...
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,
Raster;
Tags: Atlantic Ocean,
Barrier Island,
CMHRP,
Coastal Habitat,
Coastal and Marine Hazards and Resources Program,
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