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Remote Sens. 2018, 10(11), 1769; https://doi.org/10.3390/rs10111769

Canopy Effects on Snow Accumulation: Observations from Lidar, Canonical-View Photos, and Continuous Ground Measurements from Sensor Networks

1
Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720, USA
2
Sierra Nevada Research Institute, University of California, Merced, CA 95343, USA
3
Department of Civil and Environmental Engineering, University of Texas, Austin, TX 78712, USA
*
Author to whom correspondence should be addressed.
Received: 14 August 2018 / Revised: 18 October 2018 / Accepted: 30 October 2018 / Published: 8 November 2018
(This article belongs to the Special Issue Remote Sensing in Forest Hydrology)
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Abstract

A variety of canopy metrics were extracted from the snow-off airborne light detection and ranging (lidar) measurements over three study areas in the central and southern Sierra Nevada. Two of the sites, Providence and Wolverton, had wireless snow-depth sensors since 2008, with the third site, Pinecrest having sensors since 2014. At Wolverton and Pinecrest, images were captured and the sky-view factors were derived from hemispherical-view photos. We found the variation of snow accumulation across the landscape to be significantly related to canopy-cover conditions. Using a regularized regression model Elastic Net to model the normalized snow accumulation with canopy metrics as independent variables, we found that about 50 % of snow accumulation variability at each site can be explained by the canopy metrics from lidar. View Full-Text
Keywords: Sierra Nevada; wireless-sensor networks; snow; lidar Sierra Nevada; wireless-sensor networks; snow; lidar
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Zheng, Z.; Ma, Q.; Qian, K.; Bales, R.C. Canopy Effects on Snow Accumulation: Observations from Lidar, Canonical-View Photos, and Continuous Ground Measurements from Sensor Networks. Remote Sens. 2018, 10, 1769.

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