Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review
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 inte...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2024-10-01
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| Series: | Rock Mechanics Bulletin |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S277323042400043X |
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| author | Rongjie He Wengang Zhang Jie Dou Nan Jiang Huaixian Xiao Jiawen Zhou |
| author_facet | Rongjie He Wengang Zhang Jie Dou Nan Jiang Huaixian Xiao Jiawen Zhou |
| author_sort | Rongjie He |
| collection | DOAJ |
| description | 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 hyper-parameters 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. |
| format | Article |
| id | doaj-art-bd8bc226b0e94d3d8323b6d075ffc3cf |
| institution | OA Journals |
| issn | 2773-2304 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Rock Mechanics Bulletin |
| spelling | doaj-art-bd8bc226b0e94d3d8323b6d075ffc3cf2025-08-20T02:11:38ZengKeAi Communications Co., Ltd.Rock Mechanics Bulletin2773-23042024-10-013410014410.1016/j.rockmb.2024.100144Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive reviewRongjie He0Wengang Zhang1Jie Dou2Nan Jiang3Huaixian Xiao4Jiawen Zhou5State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610065, ChinaSchool of Civil Engineering, Chongqing University, Chongqing, 400044, ChinaBadong National Observation and Research Station of Geohazards, China University of Geosciences, Wuhan, 430074, ChinaCollege of Water Resources and Hydropower, Sichuan University, Chengdu, 610065, ChinaCollege of Water Resources and Hydropower, Sichuan University, Chengdu, 610065, ChinaState Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610065, China; Corresponding author.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 hyper-parameters 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.http://www.sciencedirect.com/science/article/pii/S277323042400043XLandslidesArtificial intelligenceMachine learningDetection and mappingLandslide susceptibilityPrediction and warning |
| spellingShingle | Rongjie He Wengang Zhang Jie Dou Nan Jiang Huaixian Xiao Jiawen Zhou Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review Rock Mechanics Bulletin Landslides Artificial intelligence Machine learning Detection and mapping Landslide susceptibility Prediction and warning |
| title | Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review |
| title_full | Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review |
| title_fullStr | Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review |
| title_full_unstemmed | Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review |
| title_short | Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review |
| title_sort | application of artificial intelligence in three aspects of landslide risk assessment a comprehensive review |
| topic | Landslides Artificial intelligence Machine learning Detection and mapping Landslide susceptibility Prediction and warning |
| url | http://www.sciencedirect.com/science/article/pii/S277323042400043X |
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