The Airborne Snow Observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo

REMOTE SENSING OF ENVIRONMENT

卷:184

Article

Painter, Thomas H.¹  Berisford, Daniel F.¹  Boardman, Joseph W.²  Bormann, Kathryn J.¹  Deems, Jeffrey S.^3,4  Gehrke, Frank⁵  Hedrick, Andrew⁶  Joyce, Michael¹  Laidlaw, Ross¹  Marks, Danny⁶  Mattmann, Chris¹  McGurk, Bruce⁷  Ramirez, Paul¹  Richardson, Megan¹  Skiles, S. McKenzie¹  Seidel, Felix C.¹  Winstral, Adam⁶ 

[1] CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91125 USA

[2] Analyt Imaging & Geophys LLC, Boulder, CO USA

[3] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA

[4] Natl Snow & Ice Data Ctr, Boulder, CO USA

[5] Calif Dept Water Resources, Sacramento, CA USA

[6] USDA ARS, Northwest Watershed Res Ctr, Boise, ID 83712 USA

[7] McGurk Hydrol, Orinda, CA USA

关键词: Snow water equivalent;    Snow albedo;    Water resources;    Scanning lidar;    Imaging spectrometer;   

DOI  :  10.1016/j.rse.2016.06.018

来源: Elsevier

【 摘 要 】

Snow cover and its melt dominate regional climate and water resources in many of the world's mountainous regions. Snowmelt timing and magnitude in mountains are controlled predominantly by absorption of solar radiation and the distribution of snow water equivalent (SWE), and yet both of these are very poorly known even in the best-instrumented mountain regions of the globe. Here we describe and present results from the Airborne Snow Observatory (ASO), a coupled imaging spectrometer and scanning lidar, combined with distributed snow modeling, developed for the measurement of snow spectral albedo/broadband albedo and snow depth/SWE. Snow density is simulated over the domain to convert snow depth to SWE. The result presented in this paper is the first operational application of remotely sensed snow albedo and depth/SWE to quantify the volume of water stored in the seasonal snow cover. The weekly values of SWE volume provided by the ASO program represent a critical increase in the information available to hydrologic scientists and resource managers in mountain regions. (C) 2016 Elsevier Inc. All rights reserved.

【 授权许可】

Free