A hybrid approach combining physics-based model with extreme value analysis for temporal probability of rainfall-triggered landslide
Author:
Funder
Ministry of the Interior and Safety, Korea
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10346-024-02366-x.pdf
Reference95 articles.
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2. Ajin RS, Nandakumar D, Rajaneesh A, Oommen T, Ali YP, Sajinkumar KS (2022) The tale of three landslides in the Western Ghats, India: lessons to be learnt. Geoenviron Disasters 9(1):1–8. https://doi.org/10.1186/S40677-022-00218-1/FIGURES/8
3. Al-Najjar HAH, Pradhan B (2021) Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks. Geosci Front 12(2):625–637. https://doi.org/10.1016/J.GSF.2020.09.002
4. Alonso EE (1976) Risk analysis of slopes and its application to slopes in Canadian sensitive clays. Géotechnique 26(3):453–472. https://doi.org/10.1680/GEOT.1976.26.3.453
5. Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65(1–2):15–31. https://doi.org/10.1016/J.GEOMORPH.2004.06.010
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