Physically Based and Data-Driven Models for Landslide Susceptibility Assessment: Principles, Applications, and Challenges

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Detalles Bibliográficos
Publicado en:	Remote Sensing vol. 17, no. 13 (2025), p. 2280-2318
Autor principal:	Ye Chenzuo
Otros Autores:	Wu, Hao, Oguchi Takashi, Tang, Yuting, Pei Xiangjun, Wu, Yufeng
Publicado:	MDPI AG
Materias:	Deep learning Trends Susceptibility Landslides Remote sensing Mountainous areas Hydrology Hazard assessment Data integration Machine learning Mountain regions Stability analysis Geology Data analysis Hazard mitigation Spatial data Landslides & mudslides Failure analysis Predictions Neural networks Regions Geological hazards Earthquakes Disasters Physical properties Algorithms Real time Multisensor fusion
Acceso en línea:	Citation/Abstract Full Text + Graphics Full Text - PDF
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