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Lidar point cloud data products from Uncrewed Aircraft System (UAS) surveys of dryland sites 40 km south of Moab, Utah in May 2023
In support of U.S. Geological Survey (USGS) Southwest Biological Science Center researchers, and in coordination with the Bureau of Land Management (BLM) and National Ecological Observatory Network (NEON), the USGS National Uncrewed Systems Office (NUSO) conducted uncrewed aircraft systems (UAS) remote sensing flights over two BLM Assessment, Inventory, and Monitoring (AIM) plots at the NEON Moab site in Utah for multi-scale carbon sequestration research on public lands. The UAS data collected include natural color, multispectral, and hyperspectral imagery, and lidar to capture diverse information about vegetation and soils on drylands. The first site (“site 1”) features intact sagebrush and was mapped on May 3, 2023. The second site (“site 7”) is located on a grazed rangeland environment and was mapped on May 5, 2023. These UAS surveys were conducted in early May 2023 to coincide spatially and temporally with ground-based BLM AIM sampling and airplane-based remote sensing surveys by NEON.
This portion of the data release presents discrete lidar point clouds from low-altitude UAS flights at two dryland sites approximately 40 km south of Moab, Utah. A YellowScan Vx20-100 scanner (laser wavelength 905 nm) was flown at an altitude of 31 meters above ground level on a DJI Matrice 600 Pro UAS with approved government edition firmware. The lidar point clouds were post-processed kinematic (PPK) corrected to a concurrently operating Trimble R8s GNSS base station and each point was assigned Red, Gren, Blue (RGB) image values using corresponding natural color orthomosaics at each site. The point clouds were also point classified using a bare-ground classification scheme (0-Created, never classified; 2-Ground) and exported in .las format.
Complete Metadata
| @id | http://datainventory.doi.gov/id/dataset/32329aa71dd70200ed02a1f2a8486569 |
|---|---|
| bureauCode |
[ "010:12" ] |
| identifier | USGS:64ef6626d34e4b6d8ab72c45 |
| spatial | -109.4211,38.2062,-109.40298,38.29108 |
| theme |
[ "geospatial" ] |