Debris flow susceptibility zonation using statistical models in parts of Northwest Indian Himalayas—implementation, validation, and comparative evaluation-Reference-Cited by-同舟云学术

Debris flow susceptibility zonation using statistical models in parts of Northwest Indian Himalayas—implementation, validation, and comparative evaluation

Published:2022-01-15 Issue:2 Volume:111 Page:2011-2058
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Dash Rajesh Kumar^ORCID,Falae Philips Omowumi^ORCID,Kanungo Debi Prasanna^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

https://link.springer.com/content/pdf/10.1007/s11069-021-05128-3.pdf

Reference87 articles.

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2. Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44. https://doi.org/10.1007/s100640050066

3. Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31. https://doi.org/10.1016/j.geomorph.2004.06.010

4. Balamurugan G, Ramesh V, Touthang M (2016) Landslide susceptibility zonation mapping using frequency ratio and fuzzy gamma operator models in part of NH-39, Manipur, India. Nat Hazards 84:465–488. https://doi.org/10.1007/s11069-016-2434-6

5. Banerjee P, Ghose MK, Pradhan R (2018) Analytic hierarchy process and information value method-based landslide susceptibility mapping and vehicle vulnerability assessment along a highway in Sikkim Himalaya. Arab J Geosci 11:1–18. https://doi.org/10.1007/s12517-018-3488-4

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