Snow wetness estimation based on Pol-SAR decomposition technique

Snow wetness is a very important parameter for forecasting snow avalanche and for snow melt run off modeling in cragged areas specifically for Himalayan regions of India. In this paper, a new snow wetness estimation approach is used for fully polarimetric Synthetic Aperture Radar (SAR) data. In this new methodology, Freeman surface scattering and Cloude volume scattering components are introduced which account for all independent relative polarimetric phase parameters of the coherency matrix. Snow particle has been considered to be of spheroidal shape in volume scattering model. The estimated snow wetness is validated using the field data, which was collected, synchronized with the satellite pass. The results were also compared with the Shi and Dozier [1] inversion model based snow wetness estimation.