کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6345225 | 1621216 | 2016 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The Airborne Snow Observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo
ترجمه فارسی عنوان
رصدخانه برفی هوایی: ترکیب لیزر اسکن، طیف سنجی تصویربرداری و مدل سازی فیزیکی مبتنی بر نقشه برداری از معادله آب برف و آلبدو برفی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 184, October 2016, Pages 139-152
Journal: Remote Sensing of Environment - Volume 184, October 2016, Pages 139-152
نویسندگان
Thomas H. Painter, Daniel F. Berisford, Joseph W. Boardman, Kathryn J. Bormann, Jeffrey S. Deems, Frank Gehrke, Andrew Hedrick, Michael Joyce, Ross Laidlaw, Danny Marks, Chris Mattmann, Bruce McGurk, Paul Ramirez, Megan Richardson, S. McKenzie Skiles,