This paper discusses the methodology of Synthetic Aperture Radar (SAR) data analysis for studying various aspects of snow characteristics viz snow dielectric constant, snow wetness and snow density. ENVISAT- Advanced Synthetic Aperture Radar (ASAR), single look complex (SLC) data have been processed for backscattering coefficient image generation. ASAR Backscattering coefficient images have been calibrated and processed into terrain corrected images. Corrected backscattering images are despeckled using Frost filter technique. The estimation of snow pack characteristics is optimal at different incidence angles. The relation between snow characteristics like wetness, and snow density and radar backscatter has been studied and the importance of radar backscatter to infer various snow characteristics has been emphasized. This investigation shows the backscattering coefficient is inversely correlated to snow wetness and density. The correlation between the backscattering coefficients and snow wetness and snow density were observed as 0.8 and 0.92 respectively. 14.74 % and 13.31% part of the study area was found affected by layover and low or grazing local incidence respectively in ENVISAT-ASAR IS6 image. In this study, the wetness range was found to vary from 0.05% to 10.28% by volume and mean absolute error was found to be 0.64% by volume and snow density range varies from < 0.1 to 0.48 gm/cc and mean absolute error for density was found 0.032 gm/cc. At higher elevation to moderate elevation estimated snow wetness was observed to be 0.05 - 4% by volume, increasing to 4-10.28 % by volume at moderate to lower elevation.

Date Published: 27 September 2007
PDF: 12 pages
Proc. SPIE 6677, Earth Observing Systems XII, 667716 (27 September 2007); doi: 10.1117/12.732816

Published in SPIE Proceedings Vol. 6677:
Earth Observing Systems XII
James J. Butler; Jack Xiong, Editor(s)