LiDAR‐derived snowpack data sets from mixed conifer forests across the Western United States. Issue 3 (14th March 2014)

• Record Type: Journal Article
• Authors: Harpold, A. A.; Guo, Q.; Molotch, N.; Brooks, P. D.; Bales, R.; Fernandez‐Diaz, J. C.; Musselman, K. N.; Swetnam, T. L.; Kirchner, P.; Meadows, M. W.; Flanagan, J.; Lucas, R.
• Is Part Of: Water resources research. Volume 50:Issue 3(2014:Mar.)
• Page Start: 2749
• Page End: 2755
• Publication Date: 2014-03-14
• Subjects: Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2013WR013935
• Languages: English
• ISSNs: 0043-1397

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>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 &lt;30 cm compared to limited in situ snow depth observations.</p> </abstract>