DocumentCode :
1408284
Title :
Estimation of snow water equivalence using SIR-C/X-SAR. II. Inferring snow depth and particle size
Author :
Shi, Jiancheng ; Dozier, Jeff
Author_Institution :
Inst. for Comput. Earth Syst. Sci., California Univ., Santa Barbara, CA, USA
Volume :
38
Issue :
6
fYear :
2000
fDate :
11/1/2000 12:00:00 AM
Firstpage :
2475
Lastpage :
2488
Abstract :
For pt.I see ibid., vol.38, no.6, p.2465-74 (2000). The relationship between snow water equivalence (SWE) and SAR backscattering coefficients at C- and X-band (5.5 and 9.6 GHz) can be either positive or negative. Therefore, discovery of the relationship with an empirical approach is unrealistic. Instead, the authors estimate snow depth and particle size using SIR-C/X-SAR imagery from a physically-based first order backscattering model through analyses of the importance of each scattering term and its sensitivity to snow properties. Using numerically simulated backscattering values, the authors develop semi-empirical models for characterizing the snow-ground interaction terms, the relationships between the ground surface backscattering components, and the snowpack extinction properties at C-band and X-band. With these relationships, snow depth and optical equivalent grain size can be estimated from SIR-C/X-SAR measurements. Validation using three SIR-C/X-SAR images shows that the algorithm performs usefully for incidence angles greater than 300, with root mean square errors (RMSEs) of 34 cm and 0.27 mm for estimating snow depth and ice optical equivalent particle radius, respectively.
Keywords :
backscatter; hydrological techniques; radar cross-sections; radar theory; remote sensing by radar; snow; spaceborne radar; synthetic aperture radar; 5.5 GHz; 9.6 GHz; C-band; SAR; SHF; SIR-C; X-SAR; X-band; backscattering coefficient; first order backscattering model; hydrology; incidence angle; particle size; radar remote sensing; snow cover; snow depth; snow water equivalence; snowcover; snowpack; spaceborne radar; synthetic aperture radar; water content; Backscatter; Grain size; Image analysis; Numerical simulation; Optical scattering; Optical sensors; Particle scattering; Root mean square; Size measurement; Snow;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/36.885196
Filename :
885196
Link To Document :
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