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),...

Deskribapen osoa

Xehetasun bibliografikoak

Egile Nagusiak:	Wei Zhou, Yingzhi Zhou, Shuneng Liang, Chengnian Zhang, Hongzhou Dai, Xiaofei Sun
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Nature Portfolio 2025-03-01
Saila:	Scientific Reports
Gaiak:	Machine learning Cusp catastrophe model Spatial modeling Landslide susceptibility ROC curve
Sarrera elektronikoa:	https://doi.org/10.1038/s41598-025-88070-9
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