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

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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Bibliographic Details
Main Authors: Jayanta Das, Pritam Saha, Rajib Mitra, Asraful Alam, Md Kamruzzaman
Format: Article
Language:English
Published: Elsevier 2023-05-01
Series:Heliyon
Subjects:
Landslide susceptibility mapping
Evidence belief function
Frequency ratio
Index of entropy
ROC-AUC
Sikkim himalayan region
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023033935

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http://www.sciencedirect.com/science/article/pii/S2405844023033935

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