Abstract
Seasonal frozen ground and snow cover are sensitive indicators of how our home planet is changing. In the meantime, new spaceborne SAR systems have been launched, such as the polarimetric PALSAR sensor on-board ALOS in January 2006. In this paper, the relevance of L-band polarimetric SAR data for extracting cryospheric information is presented over lowlands. It is first demonstrated that dry snowpack over frozen ground slightly affects the polarimetric signature. Given the fact that PALSAR data do not enable the use of a simplistic threshold-based method, a refined method for snow detection in PALSAR time series is outlined. A supervised Support Vector Machine is used showing fairly good results within the framework of a three-class classification (dry snow over frozen ground, wet snow and free of snow). Beyond these qualitative studies, a polarimetric EM backscattering model over snow-covered frozen fields brings out the possibility for quantitative assessments. The residual liquid water content in frozen ground over lowlands is estimated from PALSAR measurements.
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