Abstract. Information on snow depth and its spatial distribution is crucial for many applications in snow and avalanche research as well as in hydrology and ecology. Today snow depth distributions are usually estimated using point measurements performed by automated weather stations and observers in the field combined with interpolation algorithms. However, these methodologies are not able to capture the high spatial variability of the snow depth distribution present in alpine terrain. Continuous and accurate snow depth mapping has been done using laser scanning but this method can only cover limited areas and is expensive. We use the airborne ADS80 opto-electronic scanner with 0.25 m spatial resolution to derive digital surface models (DSMs) of winter and summer terrains in the neighborhood of Davos, Switzerland. The DSMs are generated using photogrammetric image correlation techniques based on the multispectral nadir and backward looking sensor data. We compare these products with the following independent datasets acquired simultaneously: (a) manually measured snow depth plots (b) differential Global Navigation Satellite System (dGNSS) points (c) Terrestrial Laser Scanning (TLS) and (d) Ground Penetrating Radar (GPR) datasets, to assess the accuracy of the photogrammetric products. The results of this investigation demonstrate the potential of optical scanners for wide-area, continuous and high spatial resolution snow-depth mapping over alpine catchments above tree line.
Yves BühlerMauro MartyLuca EgliJochen VeitingerTobias JonasP. TheeChristian Ginzler
Dongyue LiOliver WigmoreMichael DurandB. J. VanderjagtS. A. MargulisN. P. MolotchRoger C. Bales
Todd RedpathPascal SirgueyNicolas J. Cullen
Lucie EberhardPascal SirgueyAubrey MillerMauro MartyKonrad SchindlerAndreas StoffelYves Bühler