A new framework for landslide susceptibility mapping in contiguous impoverished areas using machine learning and catastrophe theory

A new framework for landslide susceptibility mapping in contiguous impoverished areas using machine learning and catastrophe theory

Abstract Landslides are among the most frequent and dangerous geological disasters worldwide, making accurate landslide susceptibility mapping (LSM) crucial for effective disaster prevention. This study introduces a novel LSM framework by integrating random forest (RF), support vector machine (SVM),...

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Bibliographic Details
Main Authors: Wei Zhou, Yingzhi Zhou, Shuneng Liang, Chengnian Zhang, Hongzhou Dai, Xiaofei Sun
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Machine learning
Cusp catastrophe model
Spatial modeling
Landslide susceptibility
ROC curve
Online Access:https://doi.org/10.1038/s41598-025-88070-9
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https://doi.org/10.1038/s41598-025-88070-9

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