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Machine Learning for Landslides Prevention: A Survey

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posted on 24.06.2020 by Zhengjing Ma, Gang Mei
Landslides are one of the most critical categories of natural disasters worldwide and induce severely destructive outcomes to human life and the overall economic system. To reduce its negative effects, landslides prevention has become an urgent task, which includes investigating landslide-related information and predicting potential landslides. Machine learning is a state-of-the-art analytics tool that has been widely used in landslides prevention. This paper presents a comprehensive survey of relevant research on machine learning applied in landslides prevention, mainly focusing on (1) landslides detection based on images, (2) landslides susceptibility assessment, and (3) the development of landslide warning systems. Moreover, this paper discusses the current challenges and potential opportunities in the application of machine learning algorithms for landslides prevention.

Funding

Research on geometric adaptive re-division method for hexahedral mesh of complex geological model

National Natural Science Foundation of China

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Email Address of Submitting Author

gang.mei@cugb.edu.cn

ORCID of Submitting Author

0000-0003-0026-5423

Submitting Author's Institution

China University of Geosciences (Beijing)

Submitting Author's Country

China

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