The aim of this EUFAR project is to measure the hyperspectral (HS) signature of snow surface in the Mont-Blanc Massif in order to estimate the spatial variability of snow surface properties (albedo, grain size and impurities content). These properties display a strong spatio-temporal variability and constrain the energy budget of the snowpack. The data retrieved during the experiment will be compared to ground measurements and satellite observations. They will provide a unique dataset to better investigate and model the surface radiative and mass balance of snow surfaces. The second objective is to obtain accurate high-resolution characterizations of glacier surface (glacier margins, glacier surface area covered by debris, limit between snow and ice). HS data will provide relevant information to quantify spatio-temporal changes in albedo (a key variable of the surface energy balance governing the ablation processes at the glacier surface) at the moment of the year (late summer) when the snow cover on the glacier surface is minimal. In addition, airborne LiDAR will allow for the elaboration of a fine-grained digital elevation model. Combining HS and LiDAR data will also enable improved modeling and understanding of glacier mass balance through investigation of the effects of small-scale topography on surface radiation and energy balances. Finally, HS imagery has direct applications for questions in alpine plant ecology. Our overall objective is to obtain a fine-grained classification of the land cover, together with spatially distributed parameters of plant canopies (physical and biochemical).