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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Detalhes bibliográficos

Principais autores:	Wei Zhou, Yingzhi Zhou, Shuneng Liang, Chengnian Zhang, Hongzhou Dai, Xiaofei Sun
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-03-01
coleção:	Scientific Reports
Assuntos:	Machine learning Cusp catastrophe model Spatial modeling Landslide susceptibility ROC curve
Acesso em linha:	https://doi.org/10.1038/s41598-025-88070-9
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