Debris flow susceptibility mapping in mountainous area based on multi-source data fusion and CNN model – taking Nujiang Prefecture, China as an example

Debris flow susceptibility mapping in mountainous area based on multi-source data fusion and CNN model – taking Nujiang Prefecture, China as an example

Efforts to evaluate the susceptibility of debris flows in large areas, especially in mountainous regions, are often hampered by the alpine and canyon terrain. This paper proposes a convolution neural network (CNN) model named dense residual shuffle net (DRSNet). It is successfully applied to Nujiang...

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Bibliographic Details
Main Authors: Fanshu Xu, Baoyun Wang
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:International Journal of Digital Earth
Subjects:
debris flow
disaster prediction
convolutional neural networks
mountainous valleys
Online Access:http://dx.doi.org/10.1080/17538947.2022.2142304

Internet

http://dx.doi.org/10.1080/17538947.2022.2142304

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