Articles | Volume 24, issue 3
https://doi.org/10.5194/nhess-24-947-2024
https://doi.org/10.5194/nhess-24-947-2024
Research article
 | 
20 Mar 2024
Research article |  | 20 Mar 2024

Automated Avalanche Terrain Exposure Scale (ATES) mapping – local validation and optimization in western Canada

John Sykes, Håvard Toft, Pascal Haegeli, and Grant Statham

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Preprint under review for NHESS
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Cited articles

Avalanche Canada: Avalanche Canada 2022 Annual Report, 38–39 pp., https://avalanche.ca/about/annual-reports (last access: 15 June 2023), 2022. 
Avalanche Canada: Trip Planner https://www.avalanche.ca/planning/trip-planner, last access: 11 May 2023. 
Bebi, P., Kulakowski, D., and Rixen, C.: Snow avalanche disturbances in forest ecosystems – State of research and implications for management, Forest Ecol. Manag., 257, 1883–1892, https://doi.org/10.1016/J.FORECO.2009.01.050, 2009. 
Bebi, P., Bast, A., Helzel, K., Schmucki, G., Brozova, N., and Bühler, Y.: Avalanche Protection Forest: From Process Knowledge to Interactive Maps, in: Protective forests as Ecosystem-based solution for Disaster Risk Reduction (ECO-DRR), IntechOpen, https://doi.org/10.5772/intechopen.99514, 2021. 
Brožová, N., Fischer, J. T., Bühler, Y., Bartelt, P., and Bebi, P.: Determining forest parameters for avalanche simulation using remote sensing data, Cold Reg. Sci. Technol., 172, 102976, https://doi.org/10.1016/j.coldregions.2019.102976, 2020. 
Short summary
The research validates and optimizes an automated approach for creating classified snow avalanche terrain maps using open-source geospatial modeling tools. Validation is based on avalanche-expert-based maps for two study areas. Our results show that automated maps have an overall accuracy equivalent to the average accuracy of three human maps. Automated mapping requires a fraction of the time and cost of traditional methods and opens the door for large-scale mapping of mountainous terrain.
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