Comparative analysis of frequency ratio, information value, and analytical hierarchy process statistical models for landslide susceptibility mapping in Kashmir Himalayas
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://link.springer.com/content/pdf/10.1007/s12517-023-11842-y.pdf
Reference94 articles.
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2. Abraham MT, Satyam N, Pradhan B, Segoni S (2022b) Proposing an easy-to-use tool for estimating landslide dimensions using a data-driven approach. All Earth 34(1):243–258
3. Afshar A, Hasanzadeh A, Besalatpour Y et al (2017) Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways. Theor Appl Climatol 129:683–699. https://doi.org/10.1007/s00704-016-1908-5
4. Anbalagan R, Chakraborty D, Kohli A (2008) Landslide hazard zonation (LHZ) mapping on meso-scale for systematic town planning in mountainous terrain. J Sci Ind Res 67:486–497
5. Anbalagan R, Kumar R, Lakshmanan K et al (2015) Landslide hazard zonation mapping using frequency ratio and fuzzy logic approach, a case study of Lachung Valley. Sikkim Geoenviron Disasters 2(1):1–17. https://doi.org/10.1186/s40677-014-0009-y
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1. Comparative Analysis of GIS-based Quantitative Approaches for Landslide Susceptibility Assessment along National Highway-1(NH-1), North Kashmir Himalaya, India;Indian Geotechnical Journal;2024-07-03
2. Geospatial assessment of landslide-prone areas in the southern part of Anambra State, Nigeria using classical statistical models;Environmental Earth Sciences;2024-03-30
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