Dry snow discrimination in alpine areas from multi-frequency and multi-temporal SAR data

A new method is presented to discriminate dry snow from bare earth in alpine regions. Because of the wide variety of alpine environments, the scene under study is first segmented into surface and forested area classes from L-band summer polarimetric SAR data. Dry snow is then discriminated over each class, using adaptive methods. A new polarimetric multi-temporal optimisation procedure, named polarimetic contrast variation enhancement (PCVE), is proposed to increase the slight polarimetric contrast because of the presence of snow over surfaces. Snow-covered forests are discriminated using performing polarimetric indicators resulting from a decomposition of incoherent matrix representations. The effectiveness of this method is demonstrated over two different alpine test sites, using SIR-C L- and C-bands polarimetric SAR data.