Snow-Mantle Remote Sensing from Spaceborne Sar Interferometry Using a Model-Based Synergetic Retrieval Approach in Central Apennines.

Using Sentinel-1 satellite data, differential interferometric synthetic- aperture-radar (DInSAR) retrieval techniques at C band are presented to estimate snowpack depth, combined with SAR backscattered data for wet snow discrimination and a physically based snowpack model. Optical satellite data from satellite multispectral imagers are used for snow extent mapping. The processing chain is tested in central Apennines (Italy), using several validation sites where in-situ snow measurements are daily available during the winter 2018-19. The potential of using analytical and statistical inversion algorithms, trained by forward SAR and snowpack model simulations of the same area, is discussed. Results, in terms of error bias, standard deviation and correlation between estimated and in situ snow data, are illustrated pointing out critical issues due to coherence loss.