Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
The Cryosphere, 10, 1361-1380, 2016
https://doi.org/10.5194/tc-10-1361-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
04 Jul 2016
Mapping snow depth in open alpine terrain from stereo satellite imagery
R. Marti1,2, S. Gascoin2, E. Berthier3, M. de Pinel4, T. Houet1, and D. Laffly1 1Géographie de l'Environnement (GEODE), UT2J/CNRS, Toulouse, France
2Centre d'Etudes Spatiales de la Biosphère (CESBIO), UPS/CNRS/IRD/CNES, Toulouse, France
3Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, (LEGOS), UPS/CNRS/IRD/CNES, Toulouse, France
4GeoFalco, Longages, France
Abstract. To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. Here, we examine the potential of very-high-resolution (VHR) optical stereo satellites to this purpose. Two triplets of 0.70 m resolution images were acquired by the Pléiades satellite over an open alpine catchment (14.5 km2) under snow-free and snow-covered conditions. The open-source software Ame's Stereo Pipeline (ASP) was used to match the stereo pairs without ground control points to generate raw photogrammetric clouds and to convert them into high-resolution digital elevation models (DEMs) at 1, 2, and 4 m resolutions. The DEM differences (dDEMs) were computed after 3-D coregistration, including a correction of a −0.48 m vertical bias. The bias-corrected dDEM maps were compared to 451 snow-probe measurements. The results show a decimetric accuracy and precision in the Pléiades-derived snow depths. The median of the residuals is −0.16 m, with a standard deviation (SD) of 0.58 m at a pixel size of 2 m. We compared the 2 m Pléiades dDEM to a 2 m dDEM that was based on a winged unmanned aircraft vehicle (UAV) photogrammetric survey that was performed on the same winter date over a portion of the catchment (3.1 km2). The UAV-derived snow depth map exhibits the same patterns as the Pléiades-derived snow map, with a median of −0.11 m and a SD of 0.62 m when compared to the snow-probe measurements. The Pléiades images benefit from a very broad radiometric range (12 bits), allowing a high correlation success rate over the snow-covered areas. This study demonstrates the value of VHR stereo satellite imagery to map snow depth in remote mountainous areas even when no field data are available.

Citation: Marti, R., Gascoin, S., Berthier, E., de Pinel, M., Houet, T., and Laffly, D.: Mapping snow depth in open alpine terrain from stereo satellite imagery, The Cryosphere, 10, 1361-1380, https://doi.org/10.5194/tc-10-1361-2016, 2016.
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Short summary
To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. We used very-high-resolution stereo satellites imagery (Pléiades) to generate a map of snow depth in a small Pyrenean catchment. The validation results are promising and open the possibility to retrieve the snow depth at a metric horizontal resolution in remote mountainous areas, even when no field data are available.
To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne...
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