Snow wetness mapping using advanced synthetic aperture radar data

Gulab Singh; Gopalan Venkataraman

doi:10.1117/1.2768622

1 July 2007 Snow wetness mapping using advanced synthetic aperture radar data

Gulab Singh, Gopalan Venkataraman

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 1, Issue 1, 013521 (July 2007). https://doi.org/10.1117/1.2768622

Abstract

The main objective of the study is to estimate snow wetness using advanced synthetic aperture radar alternative polarization single look complex data. A software has been developed for backscattering coefficient image generation and advanced synthetic aperture radar, single look complex data have been processed for backscattering coefficient image generation for dual (HH and VV) polarization data. Incidence angle image was extracted from the advanced synthetic aperture radar header data using interpolation method. These mages were multi-looked 5 times in azimuth and 1 time in range direction. Multi-looked backscattering image was despeckled using Frost filter technique. Advanced synthetic aperture radar backscattering coefficient image has been calibrated and processed into terrain corrected image in Universal Transverse Mercator (UTM), zone 43 north and WGS-84 datum map projection using ERDAS imagine software. In this study, we have used an integral equation method based inversion model for snow wetness estimation. The combined correlation coefficient between measured and estimated snow wetness was observed to be 0.89 at 95% confidence interval at Dhundi observatory and individual correlation coefficient between both measurements were observed as 0.78, 0.68,0.6 and 0.66 for 24th Feb., 27th Feb., 4th March, and 7th March, 2006 respectively at 95% confidence interval and average absolute error 2.52%. The snow wetness range varies from 0-15% by volume.

Citation Download Citation

Gulab Singh and Gopalan Venkataraman "Snow wetness mapping using advanced synthetic aperture radar data," Journal of Applied Remote Sensing 1(1), 013521 (1 July 2007). https://doi.org/10.1117/1.2768622

Published: 1 July 2007

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