Landslide Susceptibility Mapping Considering Landslide Local-Global Features Based on CNN and Transformer

Landslide susceptibility mapping (LSM) is a crucial step in quantitatively assessing landslide risk, essential for geologic hazards prevention. With the rapid development of deep learning models, convolutional neural networks (CNNs), and transformer architectures have been applied to LSM. However, t...

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Autori principali:	Zeyang Zhao, Tao Chen, Jie Dou, Gang Liu, Antonio Plaza
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2024-01-01
Serie:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Soggetti:	Convolutional neural network (CNN) landslide local-global features landslide susceptibility mapping (LSM) transformer
Accesso online:	https://ieeexplore.ieee.org/document/10475385/
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