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New method for landslide susceptibility mapping supported by spatial logistic regression and GeoDetector: A case study of Duwen Highway Basin, Sichuan Province, China
Yang, Jintao1,2; Song, Chao1,2,3; Yang, Yang1,2; Xu, Chengdong3; Guo, Fei4; Xie, Lei5
2019
Source PublicationGEOMORPHOLOGY
ISSN0169-555X
Volume324Pages:62-71
Corresponding AuthorYang, Yang(yacoco1981@126.com)
AbstractLandslides are destructive not only to property and infrastructure but also to people living in landslide-prone regions. Landslide susceptibility mapping (LSM) is critical for preventing and mitigating the negative impacts of land-slides. However, many previously proposed LSM modeling techniques included only the attribute information of spatial objects and ignored the spatial structural information of spatial objects, which led to suboptimal LSM. In addition, the selection of condition factors was not objective to such an extent that it may have reduced the reliability of LSM. To address these problems, a new method based on GeoDetector and a spatial logistic regression (SLR) model is proposed. GeoDetector is used to select condition factors based on the spatial distribution of landslides. The SLR model is used to make full use of the structural and attribute information of spatial objects simultaneously in LSM. The GeoDetector-SLR model is validated using data from the Duwen Highway Basin, which indudes the epicenter of the May 12, 2008 Wenchuan earthquake in southwestern China. Prediction accuracy of the GeoDetector-SLR model is found to be 86.1%, which is an 11.9% improvement over the traditional logistic regression model, indicating an improved and reliable solution for evaluating landslide susceptibility. (C) 2018 Published by Elsevier B.V.
KeywordLandslide susceptibility mapping GeoDetector Spatial logistic regression Spatial autocorrelation
DOI10.1016/j.geomorph.2018.09.019
WOS KeywordWENCHUAN EARTHQUAKE ; RISK ASSESSMENT ; AREA ; MODELS ; HAZARD ; REGION ; RATIO
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41701448] ; State Key Laboratory of Resources and Environmental Information System ; Young Scholars Development Fund of Southwest Petroleum University[201699010064] ; Open Fund of the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection[KLGSIT2016-03] ; Technology Project of the Sichuan Bureau of Surveying, Mapping and Geoinformation[J2017ZC05] ; Science and Technology Strategy School Cooperation Projects of the Nanchong City Science and Technology Bureau[NC17SY4016]
Funding OrganizationNational Natural Science Foundation of China ; State Key Laboratory of Resources and Environmental Information System ; Young Scholars Development Fund of Southwest Petroleum University ; Open Fund of the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection ; Technology Project of the Sichuan Bureau of Surveying, Mapping and Geoinformation ; Science and Technology Strategy School Cooperation Projects of the Nanchong City Science and Technology Bureau
WOS Research AreaPhysical Geography ; Geology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary
WOS IDWOS:000450378100006
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/51507
Collection中国科学院地理科学与资源研究所
Corresponding AuthorYang, Yang
Affiliation1.Southwest Petr Univ, Sch Geosci & Technol, Chengdu 610500, Sichuan, Peoples R China
2.Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Sichuan, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
4.China Three Gorges Univ, Natl Field Observat & Res Stn Landslides Three Go, Yichang 443002, Peoples R China
5.Natl Adm Surveying Mapping & Geoinformat, Topog Surveying Brigade 6, Chengdu 610500, Sichuan, Peoples R China
Recommended Citation
GB/T 7714
Yang, Jintao,Song, Chao,Yang, Yang,et al. New method for landslide susceptibility mapping supported by spatial logistic regression and GeoDetector: A case study of Duwen Highway Basin, Sichuan Province, China[J]. GEOMORPHOLOGY,2019,324:62-71.
APA Yang, Jintao,Song, Chao,Yang, Yang,Xu, Chengdong,Guo, Fei,&Xie, Lei.(2019).New method for landslide susceptibility mapping supported by spatial logistic regression and GeoDetector: A case study of Duwen Highway Basin, Sichuan Province, China.GEOMORPHOLOGY,324,62-71.
MLA Yang, Jintao,et al."New method for landslide susceptibility mapping supported by spatial logistic regression and GeoDetector: A case study of Duwen Highway Basin, Sichuan Province, China".GEOMORPHOLOGY 324(2019):62-71.
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