Leveraging Artificial Neural Networks for Robust Landslide Susceptibility Mapping: A Geospatial Modeling Approach in the Ecologically Sensitive Nilgiri District, Tamil Nadu-Reference-Cited by-同舟云学术

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Leveraging Artificial Neural Networks for Robust Landslide Susceptibility Mapping: A Geospatial Modeling Approach in the Ecologically Sensitive Nilgiri District, Tamil Nadu

Published:2024-07 Issue: Volume: Page:
ISSN:2949-7418
Container-title:Geohazard Mechanics
language:en
Short-container-title:Geohazard Mechanics

Author:

Rahaman Aneesah,Dondapati Abhishek^ORCID,Gupta Stutee,Raj Raveena^ORCID

Publisher

Elsevier BV

Reference69 articles.

1. Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey);Akgun;Environmental monitoring and assessment,2012

2. Landslide hazard assessment: summary review and new perspectives;Aleotti;Bulletin of Engineering Geology and the environment,1999

3. GIS-based landslide susceptibility mapping using bivariate statistical methods in North-western Tunisia;Anis;Open Geosciences,2019

4. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan;Ayalew;Geomorphology,2005

5. Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications;Ayalew;Engineering geology,2005

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