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Measurement sampling and scaling for deep montane snow depth data
Author(s) -
Fassnacht S. R.,
Deems J. S.
Publication year - 2006
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.6119
Subject(s) - snow , sampling (signal processing) , resampling , rss , scale (ratio) , elevation (ballistics) , remote sensing , environmental science , scaling , digital elevation model , meteorology , geology , mathematics , statistics , geography , cartography , computer science , geometry , operating system , filter (signal processing) , computer vision
The resolution of snow depth measurements was scaled from a nominal horizontal resolution of approximately 1·5 m to 3, 5, 10, 20, and 30 m using averaging (AVG) and resampling with a uniform random stratified sampling (RSS) scheme. The raw snow depth values were computed from airborne light detection and ranging data by differencing summer elevation measurements from winter snow surface elevations. Three montane study sites from the NASA Cold Lands Processes Experiment, each covering an 1100 m × 1100 m area, were used. To examine scaling, log–log semi‐variograms with 50 log‐width bins were created for both of the different subsetting methods, i.e. RSS and AVG. From the raw data, a scale break, going from a structured to a nearly spatially random system, was observed in each of the log–log variograms. For each site, the scale break was still detectable at slightly greater than the resampling resolution for the RSS scheme, but at approximately twice the subsetting resolution for the AVG scheme. The resolution required to identify the scale break was still from 5 to 10 m, depending upon the location and sampling method. Copyright © 2006 John Wiley & Sons, Ltd.