Mapping snow cover with repeat pass synthetic aperture radar

In hydrological investigations, modeling and forecasting of snow melt runoff requires information about snowpack properties and their spatial variability. This study demonstrates a technique to map snow cover with both the backscattering and coherence (with and without snow covered images) measurements. The authors found the coherence measurements provide a much easier way to map snow covered area. For validation of this method, they compared classification result with that derived from TM imagery. A accuracy of better than 86% can be achieved if one considers the classification result from TM imagery as the ground truth