Description: We report on the development of novel Earth Observation tools and algorithms for generation of snow products optimized for scientific and operational applications in mountain areas. The work is carried out in the AlpSnow project, a science activity within ESA's Alpine Regional Initiative. The main products refer to extent, wetness, and mass of the seasonal snow cover. Regarding snow extent, we developed a multispectral unmixing approach that accounts for variations in illumination across mountainous terrain and offers flexibility regarding the optimum use of spectral sensor capabilities. The algorithm provides consistent snow extent estimates from satellite data of different spatial resolution and spectral channels, e.g. for sensors of the Copernicus Sentinel-2 and Sentinel-3 missions. Another special feature is the provision of pixel-by-pixel uncertainty estimates by error propagation. The snow wetness product is derived from time series of Sentinel-1 radar image (SAR) data that are sensitive to wet snow. A change detection algorithm is applied, identifying also fractional snow and providing uncertainty estimates. The synergy of SAR-based and optical snow extent is used for obtaining dense time series during the snowmelt period. The project deals also with tools for retrieving snow mass (SWE) in mountain areas. SAR interferometry procedures for spatially detailed mapping of SWE are tested and evaluated, showing good performance for long wavelength SAR (L-band). AlpSAR activities are based on occasional repeat L-band SAR acquisitions of the ALOS-2 PALSAR and SAOCOM missions. Regular acquisitions, for operational applications, are expected for upcoming L-Band SAR mission, e.g. the European Copernicus Mission ROSE-L.