Articles | Volume 22, issue 6
https://doi.org/10.5194/nhess-22-2031-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-2031-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
14 Jun 2022
Research article | Highlight paper |
| 14 Jun 2022
| 14 Jun 2022
Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland
Cristina Pérez-Guillén
CORRESPONDING AUTHOR
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Frank Techel
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Martin Hendrick
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Michele Volpi
Swiss Data Science Center, ETH Zurich and EPFL, Zurich, Switzerland
Alec van Herwijnen
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Tasko Olevski
Swiss Data Science Center, ETH Zurich and EPFL, Zurich, Switzerland
Guillaume Obozinski
Swiss Data Science Center, ETH Zurich and EPFL, Zurich, Switzerland
Fernando Pérez-Cruz
Swiss Data Science Center, ETH Zurich and EPFL, Zurich, Switzerland
Department of Computer Science, ETH Zurich, Zurich, Switzerland
Jürg Schweizer
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
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Cited
16 citations as recorded by crossref.
- Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations S. Mayer et al. 10.5194/nhess-23-3445-2023
- Acoustic emission monitoring and analyses for avalanche release and slab fracturing events observed in Great Himalaya J. Kapil et al. 10.1080/10589759.2023.2208717
- Climate change impacts on snow avalanche activity and related risks N. Eckert et al. 10.1038/s43017-024-00540-2
- Combining modelled snowpack stability with machine learning to predict avalanche activity L. Viallon-Galinier et al. 10.5194/tc-17-2245-2023
- Automating avalanche detection in ground-based photographs with deep learning J. Fox et al. 10.1016/j.coldregions.2024.104179
- Development and evaluation of a method to identify potential release areas of snow avalanches based on watershed delineation C. Duvillier et al. 10.5194/nhess-23-1383-2023
- Application of Artificial Intelligence in the Assessment and Forecast of Avalanche Danger in the Ile Alatau Ridge V. Blagovechshenskiy et al. 10.3390/w15071438
- Automated prediction of wet-snow avalanche activity in the Swiss Alps M. Hendrick et al. 10.1017/jog.2023.24
- A neural network model for automated prediction of avalanche danger level V. Sharma et al. 10.5194/nhess-23-2523-2023
- SLABS: An improved probabilistic method to assess the avalanche risk on backcountry ski tours B. Degraeuwe et al. 10.1016/j.coldregions.2024.104169
- A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting A. Maissen et al. 10.5194/gmd-17-7569-2024
- Relating storm-snow avalanche instabilities to data collected from the Differential Emissivity Imaging Disdrometer (DEID) T. Morrison et al. 10.1016/j.coldregions.2023.103839
- 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
- Spatial heterogeneity and temporal tendency of channeled snow avalanche activity retrieved from Landsat images in the maritime snow climate of the Parlung Tsangpo catchment, southeastern Tibet H. Wen et al. 10.1016/j.coldregions.2024.104206
- On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger F. Techel et al. 10.5194/nhess-22-1911-2022
- Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland C. Pérez-Guillén et al. 10.5194/nhess-22-2031-2022
14 citations as recorded by crossref.
- Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations S. Mayer et al. 10.5194/nhess-23-3445-2023
- Acoustic emission monitoring and analyses for avalanche release and slab fracturing events observed in Great Himalaya J. Kapil et al. 10.1080/10589759.2023.2208717
- Climate change impacts on snow avalanche activity and related risks N. Eckert et al. 10.1038/s43017-024-00540-2
- Combining modelled snowpack stability with machine learning to predict avalanche activity L. Viallon-Galinier et al. 10.5194/tc-17-2245-2023
- Automating avalanche detection in ground-based photographs with deep learning J. Fox et al. 10.1016/j.coldregions.2024.104179
- Development and evaluation of a method to identify potential release areas of snow avalanches based on watershed delineation C. Duvillier et al. 10.5194/nhess-23-1383-2023
- Application of Artificial Intelligence in the Assessment and Forecast of Avalanche Danger in the Ile Alatau Ridge V. Blagovechshenskiy et al. 10.3390/w15071438
- Automated prediction of wet-snow avalanche activity in the Swiss Alps M. Hendrick et al. 10.1017/jog.2023.24
- A neural network model for automated prediction of avalanche danger level V. Sharma et al. 10.5194/nhess-23-2523-2023
- SLABS: An improved probabilistic method to assess the avalanche risk on backcountry ski tours B. Degraeuwe et al. 10.1016/j.coldregions.2024.104169
- A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting A. Maissen et al. 10.5194/gmd-17-7569-2024
- Relating storm-snow avalanche instabilities to data collected from the Differential Emissivity Imaging Disdrometer (DEID) T. Morrison et al. 10.1016/j.coldregions.2023.103839
- 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
- Spatial heterogeneity and temporal tendency of channeled snow avalanche activity retrieved from Landsat images in the maritime snow climate of the Parlung Tsangpo catchment, southeastern Tibet H. Wen et al. 10.1016/j.coldregions.2024.104206
2 citations as recorded by crossref.
- On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger F. Techel et al. 10.5194/nhess-22-1911-2022
- Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland C. Pérez-Guillén et al. 10.5194/nhess-22-2031-2022
Latest update: 23 Nov 2024
Executive editor
The paper could have a strong impact in the entire Alpine region, where avalanche forecasting is a critical issue to manage
The paper could have a strong impact in the entire Alpine region, where avalanche forecasting is...
Short summary
A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in...
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