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

A. A. Harpold, Q. Guo, N. Molotch, P. D. Brooks, R. Bales, J. C. Fernandez-Diaz, K. N. Musselman, T. L. Swetnam, P. Kirchner, M. W. Meadows, J. Flanagan, R. Lucas

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

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 <30 cm compared to limited in situ snow depth observations.

Original languageEnglish (US)
Pages (from-to)2749-2755
Number of pages7
JournalWater Resources Research
Volume50
Issue number3
DOIs
StatePublished - Mar 2014

Keywords

  • airborne LIDAR
  • critical zone observatory
  • snow-vegetation interactions
  • snowpack

ASJC Scopus subject areas

  • Water Science and Technology

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