Articles | Volume 18, issue 12
https://doi.org/10.5194/nhess-18-3235-2018
© Author(s) 2018. 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-18-3235-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Dec 2018
Research article |
| 10 Dec 2018
| 10 Dec 2018
Automated snow avalanche release area delineation – validation of existing algorithms and proposition of a new object-based approach for large-scale hazard indication mapping
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
Daniel von Rickenbach
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
Department of Geography, University of Zürich, Zürich, 8057,
Switzerland
Andreas Stoffel
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
Stefan Margreth
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
Lukas Stoffel
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
Marc Christen
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
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- An online platform for spatial and iterative modelling with Bayesian Networks A. Stritih et al. 10.1016/j.envsoft.2020.104658
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- Potential and challenges of depth-resolved three-dimensional MPM simulations: a case study of the 2019 ‘Salezer’ snow avalanche in Davos M. Kyburz et al. 10.1017/aog.2024.14
- Light and Shadow in Mapping Alpine Snowpack With Unmanned Aerial Vehicles in the Absence of Ground Control Points J. Revuelto et al. 10.1029/2020WR028980
- A machine learning framework for multi-hazards modeling and mapping in a mountainous area S. Yousefi et al. 10.1038/s41598-020-69233-2
- GIS-Based Spatial Modeling of Snow Avalanches Using Analytic Hierarchy Process. A Case Study of the Šar Mountains, Serbia U. Durlević et al. 10.3390/atmos13081229
- Coğrafi Bilgi Sistemi (CBS) ve Parametre Puanlama Yöntemi İle Hakkâri İli Çığ Tehlike Haritasının Oluşturulması S. MUTLU et al. 10.56130/tucbis.1177536
- Bayesian Inference in Snow Avalanche Simulation with r.avaflow J. Fischer et al. 10.3390/geosciences10050191
- The impact of terrain model source and resolution on snow avalanche modeling A. Miller et al. 10.5194/nhess-22-2673-2022
- 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
- Towards an Ensemble Machine Learning Model of Random Subspace Based Functional Tree Classifier for Snow Avalanche Susceptibility Mapping A. Mosavi et al. 10.1109/ACCESS.2020.3014816
- Determining forest parameters for avalanche simulation using remote sensing data N. Brožová et al. 10.1016/j.coldregions.2019.102976
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- Automated avalanche hazard indication mapping on a statewide scale Y. Bühler et al. 10.5194/nhess-22-1825-2022
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- Geomorphometry today I. Florinsky 10.35595/2414-9179-2021-2-27-394-448
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Latest update: 14 Dec 2024
Short summary
Coping with avalanche hazard has a long tradition in alpine countries. Hazard mapping has proven to be one of the most effective methods. In this paper we develop a new approach to automatically delineate avalanche release areas and connect them to state-of-the-art numerical avalanche simulations. This enables computer-based hazard indication mapping over large areas such as entire countries. This is of particular interest where hazard maps do not yet exist, such as in developing countries.
Coping with avalanche hazard has a long tradition in alpine countries. Hazard mapping has proven...
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