Comparative landslide susceptibility assessment using information value and frequency ratio bivariate statistical methods: a case study from Northwestern Himalayas, Jammu and Kashmir, India
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12517-024-12022-2.pdf
Reference228 articles.
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2. Abraham MT, Satyam N, Pradhan B, Segoni S (2022) Proposing an easy-to-use tool for estimating landslide dimensions using a data-driven approach. All Earth 34(1):243–258
3. Achour Y, Boumezbeur A, Hadji R, Chouabbi A, Cavaleiro V, Bendaoud EA (2017) Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine. Algeria Arab J Geosci 10(8):194. https://doi.org/10.1007/s12517-017-2980-6
4. Aditian A, Kubota T, Shinohara Y (2018) Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia. Geomorphology 318:101–111. https://doi.org/10.1016/j.geomorph.2018.06.006
5. Akgün A, Bulut F (2007) GIS-based landslide susceptibility for ArsinYomra (Trabzon, North Turkey) region. Environ Geol 51(7):1377–1387. https://doi.org/10.1007/s00254-006-0435-6
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