Predicting the thickness of shallow landslides in Switzerland using machine learning
<p>Landslide thickness is a key variable in various types of landslide susceptibility models. In this study, we developed a model providing improved predictions of potential shallow-landslide thickness for Switzerland. We tested three machine learning (ML) models based on random forest (RF) mo...
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| Main Authors: | C. Schaller, L. Dorren, M. Schwarz, C. Moos, A. C. Seijmonsbergen, E. E. van Loon |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-02-01
|
| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://nhess.copernicus.org/articles/25/467/2025/nhess-25-467-2025.pdf |
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