A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network

A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network

Landslide susceptibility mapping (LSM) plays a crucial role in assessing geological risks. The current LSM techniques face a significant challenge in achieving accurate results due to uncertainties associated with regional-scale geotechnical parameters. To explore rainfall-induced LSM, this study pr...

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Bibliographic Details
Main Authors: Hong-Zhi Cui, Bin Tong, Tao Wang, Jie Dou, Jian Ji
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Journal of Rock Mechanics and Geotechnical Engineering
Subjects:
Rainfall landslides
Landslide susceptibility mapping
Hybrid model
Physically-based model
Convolution neural network (CNN)
Probability of failure (POF)
Online Access:http://www.sciencedirect.com/science/article/pii/S167477552400355X
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