Estimation of snow hydrological parameters using single-parameter, multi-temporal SAR images

The objective of this study is to develop an algorithm for estimating snow parameter distributions using multi-temporal Synthetic Aperture Radar (SAR) data and a numerical scattering model. Simultaneous RADARSAT SAR observations were carried out during the two winter seasons. The study area is a part of the Hokuriku District of Japan that is well known for having wet snow from the beginning of the winter season. We compared the results of simulated backscattering coefficients with the ground-truth data and observed backscattering coefficients. Since the agreement was good, we demonstrated the possibility of estimating roughness distributions of soil surface using images acquired just before the snowfall with an assumption. Furthermore, we estimated the distributions of snow depth and roughness using images after a snowfall and estimated soil roughness distributions.