Articles | Volume 17, issue 7
https://doi.org/10.5194/tc-17-2779-2023
© Author(s) 2023. 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-17-2779-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jul 2023
Research article |
| 13 Jul 2023
| 13 Jul 2023
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data
César Deschamps-Berger
CORRESPONDING AUTHOR
Centre d'Etudes Spatiales de la Biosphère, CESBIO, Univ. Toulouse, CNES/CNRS/INRAE/IRD/UPS, Toulouse, France
Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
Simon Gascoin
Centre d'Etudes Spatiales de la Biosphère, CESBIO, Univ. Toulouse, CNES/CNRS/INRAE/IRD/UPS, Toulouse, France
David Shean
Dept. of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
Hannah Besso
Dept. of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
Ambroise Guiot
Centre d'Etudes Spatiales de la Biosphère, CESBIO, Univ. Toulouse, CNES/CNRS/INRAE/IRD/UPS, Toulouse, France
Juan Ignacio López-Moreno
Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
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Cited
15 citations as recorded by crossref.
- Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites Z. Hoppinen et al. 10.5194/tc-18-5407-2024
- Recent Advances in Snow Monitoring from Local to Global Scales J. Revuelto et al. 10.1007/s40641-025-00207-0
- Error-Reduced Digital Elevation Model of the Qinghai-Tibet Plateau using ICESat-2 and Fusion Model X. Zhang et al. 10.1038/s41597-024-03428-4
- Neural network-based snow depth retrieval from AMSR-2 brightness temperatures using ICESat-2 measurement as ground truth S. Sun-Mack et al. 10.3389/frsen.2025.1591276
- Learning to filter: snow data assimilation using a Long Short-Term Memory network G. Blandini et al. 10.5194/tc-19-4759-2025
- Snow monitoring at strategic locations improves water supply forecasting more than basin-wide mapping M. Raleigh et al. 10.1038/s43247-025-02660-z
- Remote sensing of mountain snow from space: status and recommendations S. Gascoin et al. 10.3389/feart.2024.1381323
- Retrieving snow depth distribution by downscaling ERA5 Reanalysis with ICESat-2 laser altimetry Z. Liu et al. 10.1016/j.coldregions.2025.104580
- Evaluation of high-resolution snowpack simulations from global datasets and comparison with Sentinel-1 snow depth retrievals in the Sierra Nevada, USA L. Sourp et al. 10.5194/hess-29-597-2025
- Spatio-temporal information propagation using sparse observations in hyper-resolution ensemble-based snow data assimilation E. Alonso-González et al. 10.5194/hess-27-4637-2023
- Spatio-temporal snow data assimilation with the ICESat-2 laser altimeter M. Mazzolini et al. 10.5194/tc-19-3831-2025
- Seasonal snow depth dataset over flat terrains in the Northern Hemisphere based on ICESat-2 data from 2018 to 2020 D. Feng et al. 10.1080/17538947.2025.2528632
- An improvement in ICESat-2 ATL03 snow depth estimation: a case study in the Tuolumne Basin, USA T. Chen et al. 10.1080/17538947.2025.2505628
- Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA T. Meehan et al. 10.5194/tc-18-3253-2024
- Mountain snow depth retrievals from customized processing of ICESat-2 satellite laser altimetry H. Besso et al. 10.1016/j.rse.2023.113843
15 citations as recorded by crossref.
- Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites Z. Hoppinen et al. 10.5194/tc-18-5407-2024
- Recent Advances in Snow Monitoring from Local to Global Scales J. Revuelto et al. 10.1007/s40641-025-00207-0
- Error-Reduced Digital Elevation Model of the Qinghai-Tibet Plateau using ICESat-2 and Fusion Model X. Zhang et al. 10.1038/s41597-024-03428-4
- Neural network-based snow depth retrieval from AMSR-2 brightness temperatures using ICESat-2 measurement as ground truth S. Sun-Mack et al. 10.3389/frsen.2025.1591276
- Learning to filter: snow data assimilation using a Long Short-Term Memory network G. Blandini et al. 10.5194/tc-19-4759-2025
- Snow monitoring at strategic locations improves water supply forecasting more than basin-wide mapping M. Raleigh et al. 10.1038/s43247-025-02660-z
- Remote sensing of mountain snow from space: status and recommendations S. Gascoin et al. 10.3389/feart.2024.1381323
- Retrieving snow depth distribution by downscaling ERA5 Reanalysis with ICESat-2 laser altimetry Z. Liu et al. 10.1016/j.coldregions.2025.104580
- Evaluation of high-resolution snowpack simulations from global datasets and comparison with Sentinel-1 snow depth retrievals in the Sierra Nevada, USA L. Sourp et al. 10.5194/hess-29-597-2025
- Spatio-temporal information propagation using sparse observations in hyper-resolution ensemble-based snow data assimilation E. Alonso-González et al. 10.5194/hess-27-4637-2023
- Spatio-temporal snow data assimilation with the ICESat-2 laser altimeter M. Mazzolini et al. 10.5194/tc-19-3831-2025
- Seasonal snow depth dataset over flat terrains in the Northern Hemisphere based on ICESat-2 data from 2018 to 2020 D. Feng et al. 10.1080/17538947.2025.2528632
- An improvement in ICESat-2 ATL03 snow depth estimation: a case study in the Tuolumne Basin, USA T. Chen et al. 10.1080/17538947.2025.2505628
- Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA T. Meehan et al. 10.5194/tc-18-3253-2024
- Mountain snow depth retrievals from customized processing of ICESat-2 satellite laser altimetry H. Besso et al. 10.1016/j.rse.2023.113843
Latest update: 30 Oct 2025
Short summary
The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.
The estimation of the snow depth in mountains is hard, despite the importance of the snowpack...
