Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review  

作　　者：Rongjie He Wengang Zhang Jie Dou Nan Jiang Huaixian Xiao Jiawen Zhou 

机构地区：[1]State Key Laboratory of Hydraulics and Mountain River Engineering,Sichuan University,Chengdu,610065,China [2]School of Civil Engineering,Chongqing University,Chongqing,400044,China [3]Badong National Observation and Research Station of Geohazards,China University of Geosciences,Wuhan,430074,China [4]College of Water Resources and Hydropower,Sichuan University,Chengdu,610065,China

出　　处：《Rock Mechanics Bulletin》2024年第4期15-33,共19页岩石力学通报（英文）

基　　金：supported by the National Natural Science Foundation of China(U2240221 and 52379105);the Sichuan Youth Science and Technology Innovation Research Team Project(2020JDTD0006)。

摘　　要：Landslides are one of the geological disasters with wide distribution,high impact and serious damage around the world.Landslide risk assessment can help us know the risk of landslides occurring,which is an effective way to prevent landslide disasters in advance.In recent decades,artificial intelligence(AI)has developed rapidly and has been used in a wide range of applications,especially for natural hazards.Based on the published literatures,this paper presents a detailed review of AI applications in landslide risk assessment.Three key areas where the application of AI is prominent are identified,including landslide detection,landslide susceptibility assessment,and prediction of landslide displacement.Machine learning(ML)containing deep learning(DL)has emerged as the primary technology which has been considered successfully due to its ability to quantify complex nonlinear relationships of soil structures and landslide predisposing factors.Among the algorithms,convolutional neural networks(CNNs)and recurrent neural networks(RNNs)are two models that are most widely used with satisfactory results in landslide risk assessment.The generalization ability,sampling training strategies,and hyperparameters optimization of these models are crucial and should be carefully considered.The challenges and opportunities of AI applications are also fully discussed to provide suggestions for future research in landslide risk assessment.

关 键 词：LANDSLIDES Artificial intelligence Machine learning Detection and mapping Landslide susceptibility Prediction and warning 

分 类 号：P642.22[天文地球—工程地质学]