WVDEP LiDAR data was collected by the Natural Resource Analysis Center at WVU under contract with the West Virginia Department of Environmental Protection, Division of Mining and Reclamation.The data was collected between 04/09/2010 and 12/13/2011 during leaf-off, snow and flood free conditions in the spring and fall.The data format is 1.5x1.5 km LAS v1.2 files in UTM 17 NAD83 (CORS96), NAVD88 (GEOID09). Contractor software initially classified ground returns for comprehensive and bare earth tiles, but did not perform other classifications. The Technical Applications and GIS (TAGIS) unit at the WVDEP performed Quality control checking and error correction on a tile-by-tile basis before creating derived products and edited LAS files.Hardware and flight parameters:Scanner: Optech ALTM-3100Post Spacing (Average): 3.3 ft / 1.0 meterFlying Height (Above Ground Level): 5,000-ft / 1,524 metersAverage Ground Speed: 135 knots (155 MPH)Scanner Pulse Rate Frequency: 70,000 HzScanner Frequency / Field of View: 35 Hz / 36 degrees (18 half angle)Overlap (Average): 30%In-depth metadata is available here, halfway down the page:LiDAR MetadataDownloads also available here:TAGIS LiDAR WebAppTAGIS LiDAR RepositoryLooking for 3DEP LiDAR? (*Not hosted or supported by TAGIS) See here:3DEP Downloads

These raster datasets are 3-meter lidar-derived images of Monroe County, West Virginia, and were created using geographic information systems (GIS) software. Lidar-derived elevation data acquired in late December of 2016 were used to create a 3-meter resolution working digital elevation model (DEM), from which a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create a 3-meter resolution lidar-derived image. The data is projected in North America Datum (NAD) 1983 UTM Zone 17.

This data comes from Ross et al., 2016 (ES&T) and is a compliation of LIDAR datasets from ~ 2010.

Dewberry collected LiDAR for ~3,942 square miles in Virginia, West Virginia, and Maryland Counties. Those counties are: Maryland - Allegany, Frederick, Washington Virginia - Clarke, Fairfax, Fauquier, Frederick West Virginia - Berkeley, Jefferson, Morgan The acquisition was performed by Geodigital. The nominal pulse spacing for this project is 1.6 ft (0.5 meters). This project was collect...

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Virginia (VA_FEMA_R3_Southwest _A and VA_FEMA_R3_Southwest_B) Leading Edge Geomatics (LEG) collected 6069.91 square miles in the Virginia counties of Bland, Buchanan, Craig (partial), Dickenson, Giles, Grayson, Lee, Russell, Scott, Smyth, Tazewell, Washington, Wise and Wythe, as well as the cities of Bristol, Galax and Norton in Virginia and the city of Bluefield in West Virginia. The nominal...

This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Kingwood 30 x 60 minute quadrangle in 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 2020 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.

This dataset consists of 575,670 point locations across the state of West Virginia. Those mapped to the “slpF” class (n = 116,413) were interpreted to be initiation locations of slope failures (e.g., landslides, debris flows, rock topples, etc.). Each slope failure location was collected as a point feature at the interpreted slope failure initiation location by an analyst then subsequently checked by another interpreter. Interpretation primarily relied on light detection and ranging (LiDAR)-derived hillshades and slopeshades and other ancillary geospatial data. All non-slope failure points are labeled as “not” (n=459,257) and were collected as random points at least 30 meters away from the mapped slope failure locations and occurring within the state extent. The “not” points serve as pseudo-absence samples. All topographic variables were derived from a 2 m spatial resolution digital terrain model (DTM) produced from LiDAR data. For topographic measures requiring a moving window, a circular window with a 7 cell radius was used. Physiographic regions are defined relative to Major Land Resource Areas (MLRAs): https://www.nrcs.usda.gov/resources/data-and-reports/major-land-resource-area-mlra. The wvSlpFailures.csv file provides only the attributes while the wvSlpFailures.shp file includes the spatial coordinates. We have included a Word document and PDF that further describes the data.

This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Buena Vista 30 x 60 minute quadrangle in Virginia and West 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 2017 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.

This tile layer, UEER_Slopes_1m, provides the slope steepness within the boundaries of the Upper Elk River Project, proposed by the U.S. Forest Service in the Monongahela National Forest of West Virginia.Purpose:The data was included to provide additional environmental context for the user’s understanding of the project’s likely environmental impacts.Source & Date:The data was downloaded from the WV Elevation and LIDAR Download Tool, hosted by the West Virginia GIS Technical Center. The data was collected in 2018, and downloaded on 7/20/2021 from (DEM_Mosaic_FEMA_2019-19_Tucker-Randolph_WV_1m_UTM17) and (DEM_Mosaic_FEMA_2016_WV_East_1m_UTM17)Processing:The slope was calculated from the 1-meter LIDAR-derived digital elevation models from two LIDAR projects – FEMA 2016 WV East, and FEMA 2018-19 Tucker-Randolph WV. The slope model was reclassified, as shown below. ABRA published the reclassified mosaic to ArcGIS Online as a tile layer.Symbology:Project Area Slopes (%):0-10%: dark green10-20%: light green20-30%: yellow30-40%: orange40-50%: red>50%: brownMore information can be found on ABRA’s project description page, hosted by the National Forest Integrity Project. Additional detailed information is available on the USFS project page.

Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. The LAS format is a standardized binary format for storing 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of x (longitude), y (latitude) and z (elevation) points. A few older projects in this collection are in ASCII format. Please refer to http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html for additional information.

This tile layer, UCR_Project_Area_Slopes, provides the slope steepness within the boundaries of the Upper Cheat River project, proposed by the U.S. Forest Service in the Monongahela National Forest of West Virginia. Purpose:This data was included to provide additional environmental context for the user’s understanding of the project’s likely environmental impacts.Source & Date:The data was downloaded from the WV Elevation and LIDAR Download Tool, hosted by the West Virginia GIS Technical Center. The data was collected in 2018, and downloaded on 7/20/2021 from (DEM_Mosaic_FEMA_2019-19_Tucker-Randolph_WV_1m_UTM17).Processing:The slope was calculated from the 1-meter LIDAR-derived digital elevation model. The slope model was reclassified, as shown below. ABRA published the reclassified mosaic to ArcGIS Online as a tile layer.Symbology:Project Area Slopes (%):0-10%: dark green10-20%: light green20-30%: yellow30-40%: orange40-50%: red>50%: brown

Monroe County in southeastern West Virginia hosts world-class karst within carbonate units of Mississippian and Ordovician age. Lidar-derived elevation data acquired in late December of 2016 were used to create a 3-meter resolution working digital elevation model (DEM), from which surface depressions were identified using a semi-automated workflow in ArcGIS®. Depressions in the automated inventory were systematically checked by a geologist within a grid of 1.5 square kilometer tiles using aerial imagery, lidar-derived imagery, and 3D viewing of the lidar imagery. Distinguishing features such as modification by human activities or hydrological significance (stream sink, ephemerally ponded, etc.) were noted wherever relevant to a particular depression. Relative confidence in depression identification was provided and determined by whether the depression was visible in the lidar imagery, aerial imagery, or both. Statistics on the geometric morphometry of each depression were calculated in ...

This tile layer describes slope steepness within the boundaries of the Cranberry Spring Creek project, proposed by the U.S. Forest Service in the Monongahela National Forest of West Virginia. Native 1-m resolution data was not available for the entire project area. There is a 3-m resolution version that fills in the gaps. https://abra.maps.arcgis.com/home/item.html?id=89ffd102edc34249858dbb7453c9f7d5Purpose:This data was included to provide additional environmental context for the user’s understanding of the project’s likely environmental impacts.Source & Date:Slope is based on 1m elevation data obtained from the WV Elevation and LIDAR Download Tool on 7/11/2021. https://data.wvgis.wvu.edu/elevation/ - references project: DEM_Mosaic_FEMA_2016_WV_East_1m_UTM17.Processing:The slope was calculated from the 1-meter LIDAR-derived digital elevation model. The slope raster was reclassified, as shown below. ABRA published the reclassified raster to ArcGis Online as a tile layer.Symbology:Project Area Slopes: 1m (%)0-10%: Dark Green10-20%: Light Green20-30%: Yellow30-40%: Orange40-50%: Red>50%: Maroon

This tile layer describes slopes in the action area of the Grassy Ridge project, proposed by the USFS in the Monongahela National Forest, West Virginia.Purpose:This data was included to provide additional environmental context for the user’s understanding of the project’s likely environmental impacts.Source & Date:Slope is based on 1m elevation data obtained from the WV Elevation and LIDAR Download Tool on 7/11/2021.https://data.wvgis.wvu.edu/elevation/Processing:1-meter elevation models of Pocahontas and Pendleton counties, West Virginia, were mosaicked in ArcMap. The slope was calculated from the 1-meter LIDAR-derived digital elevation model mosaic. The mosaic was reclassified, as shown below. ABRA published the reclassified mosaic to ArcGIS Online as a tile layer.Symbology:GRID Project Area Slopes (%)0 - 10%: Dark Green10 - 20%: Light Green20 - 30%: Yellow30 - 40%: Orange40 -50%: Red> 50%: Maroon

This tile layer, UCR_Project_Area_Slopeshade, provides a hillshade view of the slope steepness within the boundaries of the Upper Cheat River project, proposed by the U.S. Forest Service in the Monongahela National Forest of West Virginia. Purpose:This data was included to provide additional environmental context for the user’s understanding of the project’s likely environmental impacts. Hillshaded slope maps, or "slopeshades", highlight changes in slope steepness and are particularly useful for identifying roads, trails and other linear features, as well as cliffs, escarpments and active and historical landslides.Source & Date:The data was downloaded from the WV Elevation and LIDAR Download Tool, hosted by the West Virginia GIS Technical Center. The data was collected in 2018, and downloaded on 7/20/2021 from (DEM_Mosaic_FEMA_2019-19_Tucker-Randolph_WV_1m_UTM17).Processing:The slope was calculated from the 1-meter LIDAR-derived digital elevation model. The slope model was displayed with a hillshade filter and exported as a TIFF image file. An image tile set was created from the TIFF image and uploaded to ArcGIS Online as an image tile layer.Symbology:Project Area Slope (grayscale):Flat or gentle slopes: white to light graySteeper slopes: dark gray to black

Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. The LAS format is a standardized binary format for storing 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of x (longitude), y (latitude) and z (elevation) points. A few older projects in this collection are in ASCII format. Please refer to http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html for additional information. This data set is a LAZ (compressed LAS) format file containing lidar point cloud data. Compression to an LAZ file was done with the LAStools 'laszip' program and can be unzipped with the same free program (laszip.org). LICENSE: US Government Public Domain https://www.usgs.gov/faqs/what-are-terms-uselicensing-map-services-and-data-national-map

This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Elkins 30 x 60 minute quadrangle in Virginia and West 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 2015 and 2021. 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.

This study mapped land cover (water, bare ground, forest, grass, marsh, algal flat, building, bridge culvert, and agriculture) around Matagorda Bay, Texas. The study area was defined by a 2-km buffer around the West Matagorda Bay shoreline and extended from the western portion of the Colorado River Delta through the eastern portion of Matagorda Island, Texas. This study incorporated WorldView-2 (WV-2; acquired on 2012-11-17, 2013-05-05, and 2013-12-16) and lidar (acquired 2018-01-04 - 2018-02-23 and 2019-01-24 – 2019-01-29) to obtain a 2-m resolution habitat map for the entire study area. A novel stacked classification approach was developed to take advantage of high-resolution satellite imagery and airborne lidar point clouds. Ultimately, a rule-based classifier was stacked on a group of machine learning classifiers for multispectral images and a filter classifier for lidar point clouds. The data were created for the Texas Office of the Comptroller project titled “Matagorda Bay Ecosystem Assessment.†Maps of vegetation, sand, and water coverage for discrete dates from 1850 to 2020 are available in related dataset HI.x833.000:0020 (https://doi.org/10.7266/zs2f74bj).

This tile layer displays slopes found within the boundaries of the proposed Greenbrier Southeast project.Purpose:The data was included to provide additional environmental context for the user’s understanding of the project’s likely environmental impacts.Source & Date: This data was downloaded from the WV Elevation and LIDAR Tool. https://data.wvgis.wvu.edu/elevation/Processing:The slope was calculated from the 1-meter LIDAR-derived digital elevation model mosaic. The mosaic was reclassified, as shown below. ABRA published the reclassified mosaic to ArcGIS Online as a tile layer.Symbology:GSE Slopes: 10% Classes0-10%: Dark Green10-20%: Light Green20-30%: Yellow30-40%: Orange40-50%: Red>50%: Maroon