LiDAR-derived snowpack data sets from mixed conifer forests across the Western United States

Autor:	Harpold, AA, Guo, Q, Molotch, N, Brooks, PD, Bales, R, Fernandez-Diaz, JC, Musselman, KN, Swetnam, TL, Kirchner, P, Meadows, MW, Flanagan, J, Lucas, R
Rok vydání:	2014
Předmět:	critical zone observatory Environmental Engineering snowpack Applied Economics airborne LIDAR snow-vegetation interactions Civil Engineering Physical Geography and Environmental Geoscience
Zdroj:	Water Resources Research, vol 50, iss 3 Harpold, AA; Guo, Q; Molotch, N; Brooks, PD; Bales, R; Fernandez-Diaz, JC; et al.(2014). LiDAR-derived snowpack data sets from mixed conifer forests across the Western United States. Water Resources Research, 50(3), 2749-2755. doi: 10.1002/2013WR013935. UC Merced: Retrieved from: http://www.escholarship.org/uc/item/6vd756kd
DOI:	10.1002/2013WR013935.
Popis:	Airborne-based Light Detection and Ranging (LiDAR) offers the potential to measure snow depth and vegetation structure at high spatial resolution over large extents and thereby increase our ability to quantify snow water resources. Here we present airborne LiDAR data products at four Critical Zone Observatories (CZO) in the Western United States: Jemez River Basin, NM, Boulder Creek Watershed, CO, Kings River Experimental Watershed, CA, and Wolverton Basin, CA. We make publicly available snow depth data products (1 m2 resolution) derived from LiDAR with an estimated accuracy of
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::10c2ae6ae2b02375f4ca9db0845a1d42 https://escholarship.org/uc/item/6vd756kd Zobrazit plný text záznamu