Machine Learning for Landslides Prevention: A Survey
preprintposted on 24.06.2020, 04:58 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.
Read the peer-reviewed publication
Research on geometric adaptive re-division method for hexahedral mesh of complex geological model
National Natural Science Foundation of ChinaFind out more...