A Multisource Statistical Method to Downscale Snow Cover Fraction in Mountain Regions

The monitoring of the snow cover area (SCA) from optical sensors on board of satellites is affected by the trade-off between spatial and temporal resolution provided by the current operational missions. This limits the possibility to exploit satellite SCA for hydrological purposes. In this paper, we propose a novel downscaling approach driven by the low resolution (LR) information that takes advantage of i) all the high resolution (HR) images acquired in the past over a catchment; and ii) the geomorphometric features that drive the snow redistribution process. Possible applications of the proposed method are time-series gap-filling and snow pattern detection. The downscaled scenes have been validated across existing HR scenes showing an accuracy of about 90%.