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DOI10.1002/2017WR020799
An evaluation of terrain-based downscaling of fractional snow covered area data sets based on LiDAR-derived snow data and orthoimagery
Cristea, Nicoleta C.1; Breckheimer, Ian2; Raleigh, Mark S.3,4; HilleRisLambers, Janneke2; Lundquist, Jessica D.1
2017-08-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2017
卷号53期号:8
文章类型Article
语种英语
国家USA
英文摘要

Reliable maps of snow-covered areas at scales of meters to tens of meters, with daily temporal resolution, are essential to understanding snow heterogeneity, melt runoff, energy exchange, and ecological processes. Here we develop a parsimonious downscaling routine that can be applied to fractional snow covered area (fSCA) products from satellite platforms such as the Moderate Resolution Imaging Spectroradiometer (MODIS) that provide daily similar to 500 m data, to derive higher-resolution snow presence/absence grids. The method uses a composite index combining both the topographic position index (TPI) to represent accumulation effects and the diurnal anisotropic heat (DAH, sun exposure) index to represent ablation effects. The procedure is evaluated and calibrated using airborne-derived high-resolution data sets across the Tuolumne watershed, CA using 11 scenes in 2014 to downscale to 30 m resolution. The average matching F score was 0.83. We then tested our method's transferability in time and space by comparing against the Tuolumne watershed in water years 2013 and 2015, and over an entirely different site, Mt. Rainier, WA in 2009 and 2011, to assess applicability to other topographic and climatic conditions. For application to sites without validation data, we recommend equal weights for the TPI and DAH indices and close TPI neighborhoods (60 and 27 m for downscaling to 30 and 3 m, respectively), which worked well in both our study areas. The method is less effective in forested areas, which still requires site-specific treatment. We demonstrate that the procedure can even be applied to downscale to 3 m resolution, a very fine scale relevant to alpine ecohydrology research.


英文关键词downscaling snow cover remotely sensed snow cover LiDAR orthoimagery snow mapping snow satellite snow increase spatial resolution Mt Rainier Cascades Tuolumne Sierra Nevada
领域资源环境
收录类别SCI-E
WOS记录号WOS:000411202000026
WOS关键词SIERRA-NEVADA ; WATER EQUIVALENT ; ALPINE ; VEGETATION ; MODEL ; MELT ; PRECIPITATION ; ACCUMULATION ; VARIABILITY ; STREAMFLOW
WOS类目Environmental Sciences ; Limnology ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/21014
专题资源环境科学
作者单位1.Univ Washington, Civil & Environm Engn, Seattle, WA 98195 USA;
2.Univ Washington, Dept Biol, Seattle, WA 98195 USA;
3.Univ Colorado, CIRES, Boulder, CO 80309 USA;
4.Univ Colorado Boulder, NSIDC, Boulder, CO USA
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GB/T 7714
Cristea, Nicoleta C.,Breckheimer, Ian,Raleigh, Mark S.,et al. An evaluation of terrain-based downscaling of fractional snow covered area data sets based on LiDAR-derived snow data and orthoimagery[J]. WATER RESOURCES RESEARCH,2017,53(8).
APA Cristea, Nicoleta C.,Breckheimer, Ian,Raleigh, Mark S.,HilleRisLambers, Janneke,&Lundquist, Jessica D..(2017).An evaluation of terrain-based downscaling of fractional snow covered area data sets based on LiDAR-derived snow data and orthoimagery.WATER RESOURCES RESEARCH,53(8).
MLA Cristea, Nicoleta C.,et al."An evaluation of terrain-based downscaling of fractional snow covered area data sets based on LiDAR-derived snow data and orthoimagery".WATER RESOURCES RESEARCH 53.8(2017).
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