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Publication Details

Title:
Digital surface, terrain, and canopy height models for Moscow Mountain in 2009 Data publication contains GIS data
Author(s):
Bright, Benjamin C.; Hudak, Andrew T.; McCarley, T. Ryan
Publication Year:
2019
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. 2019. Digital surface, terrain, and canopy height models for Moscow Mountain in 2009. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2019-0045
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 Moscow Mountain, Idaho, USA in 2009. Lidar data were also acquired across a small area in the northeast in 2007 – this area is also included in this data publication.

Keywords:
biota; imageryBaseMapsEarthCover; elevation; Ecology, Ecosystems, & Environment; Landscape ecology; Natural Resource Management & Use; Landscape management; Inventory, Monitoring, & Analysis; digital surface model; digital terrain model; canopy height model; remote sensing; lidar; elevation data; topography; land cover; high-resolution; forest; vegetation; Idaho; Moscow Mountain
Related publications:
  • Watershed Sciences, Inc. 2009. LiDAR: Airborne data acquisition and processing: Moscow Mountain, ID. (Available through data publication download: \Supplements\MoscowMt_LiDAR_Report.pdf.).
Metrics:
Visit count : 326
Access count: 1
Download count: 36
More details
Data Access:
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