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

Virginia LiDARThe Virginia LiDAR Inventory Web Mapping Application provides access to LiDAR point cloud and individual project metadata collected in the Commonwealth of Virginia according to the USGS 3DEP specification. Data is obtained from NOAA and USGS data portals. LiDAR Point Clouds are compressed for file storage and transfer. Informational Access Type:1) LiDAR Project Metadata: To download individual LiDAR project Metadata, click on a LiDAR inventory polygon for link to the host FTP site. Once at the host site, locate appropriate directory and .zip file to receive project documentation and accompanying project files. For use within ArcGIS, the geospatial grid and inventory data powering the VGIN LiDAR download inventory services can be downloaded under conversion and analysis resources below.2) LiDAR Point Clouds (Single): To download individual tiles, zoom in on the map until the tile grid appears. The VGIN Composite Geocoding service is available to use when querying by physical address, feature, or community anchor institution name. Click a tile to identify grid information for individual LiDAR Point clouds. Columns note where the LiDAR is hosted and what format is available for download. In many instances, multiple results are returned due to multiple file formats and flight years. If LiDAR data is missing spatial reference information please refer to the metadata in step 1 above. Tile grids are stacked so you will need to scroll through selections:3) LiDAR Point Clouds (Bulk): To download multiple files in a single FTP directory folder, which can be a necessity in many instances, consider the use of a multi-file download manager plugin to use with your browser in conjunction with the URLs provided on the LiDAR inventory polygon. If LiDAR data is missing spatial reference information please refer to the metadata in step 1 above. For use within ArcGIS, the geospatial grid and inventory data powering the VGIN LiDAR Download Inventory Services can be downloaded under conversion and resources below.Conversion and Resources:Convert to LAS from USGS/NOAA hosted .LAZ filesDownload LiDAR Inventory Data Project FootprintsDownload LiDAR Inventory Tile GridContact:For questions about the data please contact USGS For questions about the application please contact vbmp@vdem.virginia.gov

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...

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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 including perimeter, area, depth, length of major and minor elliptical axes, and azimuth of the major axis. Center points were created for each surface depression and were used to create a point density raster. The density raster displays the number of closed depression points per square kilometer.

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These files contain rasterized lidar elevations generated from data collected by the Coastal Zone Mapping and Imaging Lidar (CZMIL) system. CZMIL integrates a lidar sensor with topographic and bathymetric capabilities, a digital camera and a hyperspectral imager on a single remote sensing platform for use in coastal mapping and charting activities. The 3-D position data are used to generate a s...

Dewberry collected LiDAR for ~3,942 square miles in various Virginia, West Virginia, and Maryland Counties. The acquisition was performed by Geodigital. This metadata covers the LiDAR produced for the Washington County project area. The nominal pulse spacing for this project is 1.6 ft (0.5 meters). This project was collected with a sensor which collects intensity values for each discrete pulse extracted from the waveform. GPS Week Time, Intensity, Flightline and echo number attributes were provided for each LiDAR point. Dewberry used proprietary procedures to classify the LAS according to contract specifications: 1-Unclassified, 2-Ground, 7-Noise, 9-Water, 10-Ignored Ground due to breakline proximity, and 11-Withheld. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro flattened DEMs for the 638 tiles (1500 m x 1500 m) that cover this deliverable.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://lidar.geodata.md.gov/imap/rest/services/Washington/MD_washington_aspect_m/ImageServer

Updated in mid 2021 to include all new lidar funded by FEMA and delivered through the USGS 3DEP program. Source data is an entirely lidar-based, 3-meter resolution elevation grid. Most data within the state has been acquired since 2017, except for the eastern panhandle.

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

Dewberry collected LiDAR for ~3,942 square miles in various Virginia, West Virginia, and Maryland Counties. The acquisition was performed by Geodigital. This metadata covers the LiDAR produced for the Washington County project area. The nominal pulse spacing for this project is 1.6 ft (0.5 meters). This project was collected with a sensor which collects intensity values for each discrete pulse extracted from the waveform. GPS Week Time, Intensity, Flightline and echo number attributes were provided for each LiDAR point. Dewberry used proprietary procedures to classify the LAS according to contract specifications: 1-Unclassified, 2-Ground, 7-Noise, 9-Water, 10-Ignored Ground due to breakline proximity, and 11-Withheld. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro flattened DEMs for the 638 tiles (1500 m x 1500 m) that cover this deliverable.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://lidar.geodata.md.gov/imap/rest/services/Washington/MD_washington_dem_ft/ImageServer

Dewberry collected LiDAR for ~3,942 square miles in various Virginia, West Virginia, and Maryland Counties. The acquisition was performed by Geodigital. This metadata covers the LiDAR produced for the Washington County project area. The nominal pulse spacing for this project is 1.6 ft (0.5 meters). This project was collected with a sensor which collects intensity values for each discrete pulse extracted from the waveform. GPS Week Time, Intensity, Flightline and echo number attributes were provided for each LiDAR point. Dewberry used proprietary procedures to classify the LAS according to contract specifications: 1-Unclassified, 2-Ground, 7-Noise, 9-Water, 10-Ignored Ground due to breakline proximity, and 11-Withheld. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro flattened DEMs for the 638 tiles (1500 m x 1500 m) that cover this deliverable.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://lidar.geodata.md.gov/imap/rest/services/Washington/MD_washington_hillshade_m/ImageServer

This package is part of the Watershed Function SFA Data Collection and contains remote sensing data and geophysical measurements acquired at the Pumphouse hillslope-floodplain site, in the East River, Colorado. This package was used in the study: “Investigating Microtopographic and Soil Controls on a Mountainous Meadow Plant Community Using High-Resolution Remote Sensing and Surface Geophysical Data”, published on Journal of Geophysical Research - Biogeosciences, May 2019, DOI: https://doi.org/10.1029/2018JG004394. The remote sensing dataset includes: a) a WorldView-2 (WV-2) pan-sharpened multi-spectral remote sensing image, and b) LiDAR derived products. The WV-2 image was acquired on September 24th, 2015, and it is composed of eight spectral bands (coastal, blue, green, yellow, red, red edge, NIR1, and NIR2) with a spatial resolution of 0.5 m, covering an area of 750x750 m. The LiDAR products are a digital surface model (DSM), representing the top-of-canopy elevation, and a digital terrain model (DTM), representing the bare-ground elevation, at the spatial resolution of 0.5 m. Such data are extracted from the LiDAR point-cloud dataset acquired over the entire watershed on August 2015 (http://dx.doi.org/10.21952/WTR/1412542). The geophysical dataset is composed of the electrical resistivity tomography (ERT) data acquired along a 158.75 m long transect, spanning the hillslope topographical gradient with 1.25 m electrode spacing. The dataset also includes soil water content measured with a TDR system. The package provides also polygons of different vegetation communities, which were used as reference data for mapping plant community distributions. The spatial polygons are based on plant locations acquired during the field campaign of June-July 2017 using an RTK DGPS system. The reference dataset is composed by 11 vegetation classes, namely, deciduous forest, evergreen forest, riparian shrubland, sagebrush, shrubland, potentilla, frasera, lupine meadow, veratrum, bunchgrass meadow, and forb, as well as four non-vegetation classes, such as water-river, water-lake, man-made, bare area, and shadow. The vegetation classes are determined based on distinct spectral and/or structural signatures of dominant species. The package includes products derived by these datasets, such as: a) a plant height map, computed by subtracting the DTM from the DSM, and b) a plant community distribution map, obtained by using a data-fusion machine-learning-based framework that exploit the WV-2 image and plant height information.

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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.

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

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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.

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.

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.