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\begin{document}

\title{Machine Learning for Landslides Prevention: A Survey}



\author[1]{Zhengjing Ma }%
\author[2]{Gang Mei }%
\affil[1]{Affiliation not available}%
\affil[2]{China University of Geosciences (Beijing)}%


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  \date{May 28, 2024}


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\begin{abstract}
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.%
\end{abstract}%



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