Retrieval of wet snow by means of multitemporal SAR data

An algorithm has been developed for mapping wet snow in mountainous terrain using repeat pass synthetic aperture radar (SAR) images. As a basis for algorithm development, backscattering properties of snow-free and snow-covered: alpine surfaces were investigated using ERS SAR data and field measurements at test sites in the Austrian Alps. The incidence angle dependence of backscattering derived from SAR data is compared with simulations for snow-free surfaces and for surfaces covered by dry snow and wet snow. Significant seasonal changes of backscattering are observed, which are mainly caused by variations of the snow liquid water content and of the surface roughness. The importance of surface roughness for backscattering of wet snow is demonstrated by a surface roughness experiment. The algorithm for mapping wet snow applies change detection using ratios of wet snow versus snow-free or dry snow surfaces. The main steps include coregistration, speckle reduction, thresholding of ratio images, geocoding, and, optionally, combination of crossing passes to reduce the loss of information due to layover. A threshold of -3 dB was found to be appropriate for both Radarsat and ERS SAR to separate wet snow from other surfaces. Postprocessing steps, based on historic snow maps or topographic information, are used to correct for dry snow areas at high elevations. Effects of imaging geometry are investigated by comparing ERS SAR images with a look angle of 19 degrees and Radarsat SAR Beam Mode S7 images with a look angle of 40 degrees. The comparison of snow maps from SAR and Landsat-5 Thematic Mapper images shows good agreement in areas of closed snow cover, whereas near the snow line/SAR tends to slightly underestimate the snow extent. Time series of SAR snow maps have been derived for several Alpine drainage basins as input for runoff models.