Waiting for the snow to melt…
This is a pseudo-3D hillshade visualization of a 9 meter resolution digital elevation model representing elevation above mean sea level in meters. Elevations are vertically referenced to the EGM96 geoid model and thus represent orthometric heights. The dataset is synthesized from 6 airborne laser scanning (LiDAR) datasets collected from August 2016 to August 2023. The data extent covers the declared forest boundary of the Grand Mesa, Uncompaghre, and Gunnison National Forests in western Colorado, USA. The elevation model was generated by functions in the LidR package for the R programming language (version 4.1, Roussel and Auty 2024). Original point cloud data delivered from the vendors to the Colorado Hazard Mapping Program was reprojected to a common coordinate system (WGS84 UTM Zone 13N, EPSG:32613). Points with the vendor-provided ground classification flag were interpolated using a TIN algorithm and gridded to a common 3 meter resolution grid system. Areas with significant holes in the original point cloud were filled with resampled vendor-provided gridded elevation data. These datasets were generated by Ian Breckheimer and Rachel Crafford at Rocky Mountain Biological Laboratory on behalf of the US Forest Service. References: Roussel J, Auty D, Coops NC, Tompalski P, Goodbody TR, Meador AS, Bourdon J, de Boissieu F, Achim A (2020). “lidR: An R package for analysis of Airborne Laser Scanning (ALS) data.” Remote Sensing of Environment, 251, 112061. ISSN 0034-4257, doi:10.1016/j.rse.2020.112061, https://www.sciencedirect.com/science/article/pii/S0034425720304314. Roussel J, Auty D (2024). Airborne LiDAR Data Manipulation and Visualization for Forestry Applications. R package version 4.1.2, https://cran.r-project.org/package=lidR.
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