Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters. Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points. In this manner buildings and vegetation are removed from Bare Earth Model. This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernible in the LiDAR data.

Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters. Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points. In this manner buildings and vegetation are removed from Bare Earth Model. This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernable in the LiDAR data.

Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters. Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points. In this manner buildings and vegetation are removed from Bare Earth Model. This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernable in the LiDAR data.

Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters. Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points. In this manner buildings and vegetation are removed from Bare Earth Model. This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernable in the LiDAR data.

,Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters. Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points. In this manner buildings and vegetation are removed from Bare Earth Model. This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernable in the LiDAR data.,

,Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters. Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points. In this manner buildings and vegetation are removed from Bare Earth Model. This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernable in the LiDAR data.,

First Return Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of first return elevations in meters. LIDAR data provided by the Joint Precision Strike Demonstration Project Office of the US Army contained bare earth rasters. This raster contains elevations of all structures, tree canopies, and bare earth.

This dataset represents the Camas National Wildlife Refuge survey area in Jefferson and Clark County, ID. This bare earth digital elevation model (DEM) represent the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from LiDAR data using TIN processing of the ground point returns. The DEM grid cell size is 1 meter. The elevation units are in meters. Some elevation values have been interpolated across areas in the ground model where there is no elevation data (e.g. over water, over dense vegetation). Watershed Sciences, Inc. collected the LiDAR and created this data set for the US Fish and Wildlife Service.

This lidar data set includes unclassified swath LAS 1.4 files, classified LAS 1.4 files, breaklines, digital elevation models (DEMs), first return digital surface models (DSMs), and intensity imagery. Geographic Extent: Fourteen partial counties in Utah, covering approximately 7,005 total square kilometers; partial coverage of three counties covering approximately 182 square kilometers in the Minidoka QL1 AOI. This area is part of the Bear Lake / Cache Valley QL1 AOI. Dataset Description: The Utah 2016 Lidar project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011), UTM Zone 12, meters and vertical datum of NAVD88 (GEOID12B), meters. Lidar data was delivered as flightline-extent unclassified LAS swaths, as processed Classified LAS 1.4 files formatted to 215 individual 1,000 meter x 1,000 meter tiles; as tiled intensity imagery, as tiled bare earth DEMs, and as tiled first return DSMs all tiled a 2,000 meter x 2,000 meter schema (82 tiles). Continuous breaklines were produced in Esri shapefile format. Ground Conditions: Lidar was partially collected in fall of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. established a total of 28 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. An additional 5 independent accuracy checkpoints, 5 in Bare Earth and Urban landcovers (5 NVA points), 6 in the Shrubs and Tall Grass category (6 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

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