IMPROVED SUBPIXEL MONITORING OF SEASONAL SNOW COVER: A CASE STUDY IN THE ALPS

The snow coverage area (SCA) is one of the most important parameters for cryospheric studies. The use of remote sens-ing imagery can complement field measurements by provid-ing means to derive SCA with a high temporal frequency and covering large areas. Images acquired by the Moderate Res-olution Imaging Spectroradiometer (MODIS) are perhaps the most widely used data to retrieve SCA maps. Some MODIS derived algorithms are available for subpixel SCA estimation, as MODSCAG and MODImLab. Both algorithms make use of spectral unmixing techniques using a fixed set of snow, rocks and other materials spectra (endmembers). We aim to improve the performance of a modified version of MODIm-Lab algorithm by exploring advanced spectral unmixing tech-niques. Furthermore, we make use of endmember induction algorithms to obtain the endmembers from the data itself in-stead of using a fixed spectral library. We validate the pro-posed approach on a case study in the mountainous region of the Alps. Index Terms — Snow coverage area, SCA, spectral un-mixing, MODIS, Alps