Articles | Volume 14, issue 9
https://doi.org/10.5194/tc-14-2925-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-2925-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
César Deschamps-Berger
CORRESPONDING AUTHOR
Centre d'Etudes Spatiales de la Biosphère, CESBIO, Univ.
Toulouse, CNES/CNRS/INRA/IRD/UPS, 31401 Toulouse, France
Université Grenoble Alpes, Université de Toulouse,
Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, 38000
Grenoble, France
Simon Gascoin
Centre d'Etudes Spatiales de la Biosphère, CESBIO, Univ.
Toulouse, CNES/CNRS/INRA/IRD/UPS, 31401 Toulouse, France
Etienne Berthier
Centre National de la Recherche Scientifique (CNRS-LEGOS), 31400
Toulouse, France
Jeffrey Deems
National Snow and Ice Data Center, Boulder, CO, USA
Ethan Gutmann
Research Applications Lab, National Center for Atmospheric Research
(NCAR), Boulder, CO, USA
Amaury Dehecq
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH
Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research
(WSL), Birmensdorf, Switzerland
David Shean
Dept. of Civil and Environmental
Engineering, University of Washington, Seattle, WA, USA
Marie Dumont
Université Grenoble Alpes, Université de Toulouse,
Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, 38000
Grenoble, France
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- Uncertainty of ICESat-2 ATL06- and ATL08-derived snow depths for glacierized and vegetated mountain regions E. Enderlin et al. 10.1016/j.rse.2022.113307
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- Mapping snow depth and spatial variability using SFM photogrammetry of UAV images over rugged mountainous regions of the Western Himalaya S. Dewali et al. 10.1080/10106049.2022.2127923
- Potential of the Bi-Static SAR Satellite Companion Mission Harmony for Land-Ice Observations A. Kääb et al. 10.3390/rs16162918
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- Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data C. Deschamps-Berger et al. 10.5194/tc-17-2779-2023
- Six Consecutive Seasons of High‐Resolution Mountain Snow Depth Maps From Satellite Stereo Imagery J. Hu et al. 10.1029/2023GL104871
- A scale-dependent model to represent changing aerodynamic roughness of ablating glacier ice based on repeat topographic surveys T. Smith et al. 10.1017/jog.2020.56
- Analyzing the sensitivity of a blowing snow model (SnowPappus) to precipitation forcing, blowing snow, and spatial resolution A. Haddjeri et al. 10.5194/tc-18-3081-2024
- On the Evaluation of the SAR-Based Copernicus Snow Products in the French Alps F. Karbou et al. 10.3390/geosciences12110420
- Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas L. Bührle et al. 10.5194/tc-17-3383-2023
- Annual to seasonal glacier mass balance in High Mountain Asia derived from Pléiades stereo images: examples from the Pamir and the Tibetan Plateau D. Falaschi et al. 10.5194/tc-17-5435-2023
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2 citations as recorded by crossref.
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Short summary
We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it with accurate airborne laser-scanning measurements in the Sierra Nevada, USA. We find that satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountains.
We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it...