GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India

Predicting landslides is becoming a crucial global challenge for sustainable development in mountainous areas. This research compares the landslide susceptibility maps (LSMs) prepared from five GIS-based data-driven bivariate statistical models, namely, (a) Frequency Ratio (FR), (b) Index of Entropy...

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Detalles Bibliográficos
Autores principales: Das, Jayanta, Saha, Pritam, Mitra, Rajib, Alam, Asraful, Kamruzzaman, Md
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205644/
https://www.ncbi.nlm.nih.gov/pubmed/37234665
http://dx.doi.org/10.1016/j.heliyon.2023.e16186

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205644/
https://www.ncbi.nlm.nih.gov/pubmed/37234665
http://dx.doi.org/10.1016/j.heliyon.2023.e16186

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