LiDAR geospatial data were collected on the 18,000 area Clarks River National Wildlife Refuge in late fall-winter 2011. The associated deliverables from the project are provided as geo-referenced in zipped folders. These datasets include 1-foot counter, bare earth DEM, Bare earth Hillshade, vare earth Terrain, control points, DSM, GT_report, Intensity, LAS, and Shapefiles. Associated Metadata may not be fully compliant.

LiDAR geospatial data were collected on approximately 60,000 acres of White River National Wildlife Refuge in late fall-winter 2016-17. The associated deliverables from the project are provided as geo-referenced in zipped folders. In some cases, data may extend beyond the refuge boundary and or include data associated with a larger LiDAR project which was not exclusively clipped to the boundaries of the refuge. Associated Metadata is fully compliant.

LiDAR geospatial data were collected on approximately 60,000 acres of White River National Wildlife Refuge in late fall-winter 2016-17. The associated deliverables from the project are provided as geo-referenced in zipped folders. In some cases, data may extend beyond the refuge boundary and or include data associated with a larger LiDAR project which was not exclusively clipped to the boundaries of the refuge. Associated Metadata is fully compliant.

LiDAR geospatial data were collected on hatchie National Wildlife Refuge in late fall-winter 2011-2012. The associated deliverables from the project are provided as geo-referenced in zipped folders. These datasets include 1-foot counter, bare earth DEM, Bare earth Hillshade, bare earth Terrain, control points, DSM, GT_report, Intensity, LAS, and Shapefiles. Associated Metadata may not be fully compliant.

LiDAR geospatial data were collected on hatchie National Wildlife Refuge in late fall-winter 2011-2012. The associated deliverables from the project are provided as geo-referenced in zipped folders. These datasets include 1-foot counter, bare earth DEM, Bare earth Hillshade, bare earth Terrain, control points, DSM, GT_report, Intensity, LAS, and Shapefiles. Associated Metadata may not be fully compliant.

This dataset includes, LiDAR point cloud, DEM, hydro-conditioned DEM, and other calibration files. All geospatial data is available through the FWS Geospatial FileShare (EDW). FWS stores this dataset on the FWS Enterprise Data Warehouse for use in internal projects. There are no restrictions on this data, but it is very large and managed on an internal server. It is available to anyone on request.

This dataset includes, LiDAR point cloud, DEM, hydro-conditioned DEM, and other calibration files. All geospatial data is available through the FWS Geospatial FileShare (EDW). FWS stores this dataset on the FWS Enterprise Data Warehouse for use in internal projects. There are no restrictions on this data, but it is very large and managed on an internal server. It is available to anyone on request.

The U.S. Geological Survey (USGS), in cooperation with the U.S. National Park Service (NPS), has compiled a Geographic Information System (GIS) dataset. The spatial data layer provided in this data release is derived from high-resolution lidar digital elevation models (DEM’s) for the Katahdin Woods and Waters National Monument in Penobscot County, Maine. The data provided in this release includes a stream network centerline polyline shapefile derived from hydro-enforcement that shows stream location within the Katahdin Woods and Waters National Monument boundary.

These data were compiled for Cabeza Prieta National Wildlife Refuge (CPNWR) in southern Arizona, to support managment efforts of water resources and wildlife conservation. Objective(s) of our study were to 1) measure water storage capacity at select stage heights in three tanks (also termed tinajas), 2) build a stage storage model to help CPNWR staff accurately estimate water volumes throughout the year, and 3) collect topographic data adjacent to the tanks as a means to help connect these survey data to past or future work. These data represent high-resolution (sub-meter) ground based lidar measurements used to meet these objectives and are provided as: processed lidar files (point clouds), rasters (digital elevation models), and vectors (shapefiles). These data were collected in Southern Arizona at Buckhorn, Eagle, and Senita tanks in the CPNWR from February 13-18, 2022. These data were collected by U.S. Geological Survey - Southwest Biological Science Center - Grand Canyon Monitoring and Research Center (GCMRC) staff for the CPNWR using a Riegl VZ 1000 ground-based lidar to produces ground elevation models georeferenced using control target coordinates collected by a Trimble real-time kinematic (RTK) rover and base station. These data which represent maximum water storage capacity at Buckhorn, Eagle and Senita tanks following sediment removal by CPNWR staff less than one month prior can be used to support management efforts for water resources at these tanks, and wildlife conservation in the CPNWR. Additionally, these data can be used as baseline conditions for evaluating changes in water storage and water storage capacity.

These data were compiled for Cabeza Prieta National Wildlife Refuge (CPNWR) in southern Arizona, to support managment efforts of water resources and wildlife conservation. Objective(s) of our study were to 1) measure water storage capacity at select stage heights in three tanks (also termed tinajas), 2) build a stage storage model to help CPNWR staff accurately estimate water volumes throughout the year, and 3) collect topographic data adjacent to the tanks as a means to help connect these survey data to past or future work. These data represent high-resolution (sub-meter) ground based lidar measurements used to meet these objectives and are provided as: processed lidar files (point clouds), rasters (digital elevation models), and vectors (shapefiles). These data were collected in Southern Arizona at Buckhorn, Eagle, and Senita tanks in the CPNWR from February 13-18, 2022. These data were collected by U.S. Geological Survey - Southwest Biological Science Center - Grand Canyon Monitoring and Research Center (GCMRC) staff for the CPNWR using a Riegl VZ 1000 ground-based lidar to produces ground elevation models georeferenced using control target coordinates collected by a Trimble real-time kinematic (RTK) rover and base station. These data which represent maximum water storage capacity at Buckhorn, Eagle and Senita tanks following sediment removal by CPNWR staff less than one month prior can be used to support management efforts for water resources at these tanks, and wildlife conservation in the CPNWR. Additionally, these data can be used as baseline conditions for evaluating changes in water storage and water storage capacity.