Compensation of forest canopy effects in the estimation of snow covered area from SAR data

As spaceborne SAR is used for monitoring the snow cover during the spring melt period, temporal changes in backscattering properties of forest cover disturb the quantitative estimation of snow covered area (SCA). This paper introduces an algorithm that eliminates the related disturbances in SCA estimation. The algorithm is developed based on the Helsinki University of Technology (HUT) forest backscattering model. An extensive multitemporal ERS-2 C-band SAR data set from Northern Finland is used for validating the backscattering model and for testing the SCA estimation algorithm. Comparison of SCA estimation results with available ground truth data for SCA indicates a good performance and a significant improvement when compared with the estimates produced by commonly used linear interpolation algorithms