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18 September 2009 Algorithm development for snow density estimation using polarimetric advanced SAR data
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Remote sensing of Radar Polarimety has great potential to determine the extent and properties of snow cover. Availability of spaceborne sensor dual polarimetric C-band data of ENVISAT-ASAR can enhance the accuracy in measurement of snow physical parameters as compared to single fixed polarization data measurement. This study shows that the capability of C-band SAR data for estimating dry snow density over snow coverer rugged terrain in Himalayan region. The study area lies in Beas, Chandra and Bhaga catchments of Himachal state (India). For this investigation, the main assumptions are that the snow is dry and at C-band, total backscattering coefficient comes from snowpack and snow ground interface. An algorithm for estimating snow density has been developed based on snow volume scattering and snow-ground scattering components. Snow density estimation algorithm requires HH and VV polarization combination data. The radar backscattering coefficients of both HH and VV polarization and incidence angle are given as input to the developed algorithm. Finally, the algorithm gives the snow dielectric constant which can further be related to snow density using Looyenga's semi empirical formula. Comparison was done between algorithm estimated snow density and field value of snow density in the study region. The mean absolute error between estimated and measured snow density was 21.3 kg/m3.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
G. Singh and G. Venkataraman "Algorithm development for snow density estimation using polarimetric advanced SAR data", Proc. SPIE 7472, Remote Sensing for Agriculture, Ecosystems, and Hydrology XI, 74720U (18 September 2009);

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