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Publication Details

Title:
Digital surface, terrain, and canopy height models for Priest River Experimental Forest in 2011 Data publication contains GIS data
Author(s):
Bright, Benjamin C.; Hudak, Andrew T.; McCarley, T. Ryan
Publication Year:
2020
How to Cite:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:
Bright, Benjamin C.; Hudak, Andrew T.; McCarley, T. Ryan. 2020. Digital surface, terrain, and canopy height models for Priest River Experimental Forest in 2011. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2020-0043
Abstract:
This data publication contains three digital rasters with a spatial resolution of one meter: 1) a digital surface model (DSM), which represents the highest lidar return in each grid cell; 2) a digital terrain model (DTM), a representation of the ground surface with vegetation and other non-ground returns removed; and 3) a canopy height model (CHM), a representation of the height of vegetation above the ground surface. Digital rasters were derived from lidar data that were acquired over Priest River Experimental Forest, Idaho, USA in 2011.

Keywords:
biota; elevation; imageryBaseMapsEarthCover; Ecology, Ecosystems, & Environment; Inventory, Monitoring, & Analysis; Landscape ecology; Landscape management; Natural Resource Management & Use; canopy height model; digital surface model; digital terrain model; elevation data; forest; high-resolution; land cover; lidar; remote sensing; topography; vegetation; Priest River Experimental Forest; Idaho
Related publications:
  • Hudak, Andrew T.; Liebermann, Robert J.; Moreira, Eder P.; Gessler, Paul E.; Bright, Benjamin C; McCarley, T. Ryan. 2020. Digital surface, terrain, and canopy height models for Priest River Experimental Forest in 2002. 2nd Edition. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RDS-2013-0001-2
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Download count: 21
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