| Landslide integrated characteristics and susceptibility assessment in Rongxian county of Guangxi, China | |
Liao Li-ping1,2,3 ; Zhu Ying-yan4; Zhao Yan-lin1; Wen Hai-tao5; Yang Yun-chuan1,2,3; Chen Li-hua1; Ma Shao-kun1; Xu Ying-zi1
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| Corresponding Author | Wen Hai-tao(wavewen500@163.com) |
| 2019-03-01 | |
| Source Publication | JOURNAL OF MOUNTAIN SCIENCE
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| ISSN | 1672-6316 |
| Volume | 16Issue:3Pages:657-676 |
| Abstract | Landslides distribute extensively in Rongxian county, the southeast of Guangxi province, China and pose great threats to this county. At present, hazard management strategy is facing an unprecedented challenge due to lack of a landslide susceptibility map. Therefore, the purpose of this paper was to construct a landslide susceptibility map by adopting three widely used models based on an integrated understanding of landslide's characteristics. These models include a semi-quantitative method (SQM), information value model (IVM) and logistical regression model (LRM).The primary results show that (1) the county is classified into four susceptive regions, named as very low, low, moderate and high, which covered an area of 13.43%, 32.40%, 31.19% and 22.99% in SQM, 0.86%, 26.82%, 44.11%, and 28.21% in IVM, 9.88%, 17.73%, 46.36% and 26.03% in LRM; (2) landslides are likely to occur within the areas characterized by following obvious aspects: high intensity of human activities, slope angles of 25 degrees similar to 35 degrees, the thickness of weathered soil is larger than 15 m; the lithology is granite, shale and mud rock; (3) the area under the curve of SQM, IVM and LRM is 0.7151, 0.7688 and 0.7362 respectively, and the corresponding success rate is 71.51%, 76.88% and 73.62%. It is concluded that these three models are acceptable because they have an effective capability of susceptibility assessment and can achieve an expected accuracy. In addition, the susceptibility outcome obtained from IVM provides a slightly higher quality than that from SQM, LRM. |
| Keyword | Landslide characteristic Susceptibility zonation Prevention regionalization Rongxian county |
| DOI | 10.1007/s11629-017-4804-2 |
| Indexed By | SCI |
| WOS Keyword | ANALYTIC HIERARCHY PROCESS ; WEIGHTED LINEAR COMBINATION ; LOGISTIC-REGRESSION MODELS ; ARTIFICIAL NEURAL-NETWORK ; INFORMATION VALUE METHOD ; HAZARD RISK-ASSESSMENT ; FREQUENCY RATIO ; STATISTICAL INDEX ; CERTAINTY FACTOR ; DECISION TREE |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[51609041] ; Natural Scientific Project of Guangxi Zhuang Autonomous Region[2018GXNSFAA138187] ; Project of the Education Department of Guangxi Zhuang Autonomous Region[2018KY0027] ; Project of Department of Land and Resources of Guangxi Zhuang Autonomous Region[GXZC2018-G3-19302-JGYZ] ; Project of Xi'an Geological survey center of China Geological survey[DD20189270] |
| WOS Research Area | Environmental Sciences & Ecology |
| WOS Subject | Environmental Sciences |
| WOS ID | WOS:000460754100013 |
| Funding Organization | National Natural Science Foundation of China ; Natural Scientific Project of Guangxi Zhuang Autonomous Region ; Project of the Education Department of Guangxi Zhuang Autonomous Region ; Project of Department of Land and Resources of Guangxi Zhuang Autonomous Region ; Project of Xi'an Geological survey center of China Geological survey |
| Publisher | SCIENCE PRESS |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imde.ac.cn/handle/131551/25310 |
| Collection | 山地灾害与地表过程重点实验室 |
| Corresponding Author | Wen Hai-tao |
| Affiliation | 1.Guangxi Univ, Coll Civil Engn & Architecture, Nanning 530004, Peoples R China 2.Guangxi Univ, Key Lab Disaster Prevent & Struct Safety, Minist Educ, Nanning 530004, Peoples R China 3.Guangxi Univ, Guangxi Key Lab Disaster Prevent & Engn Safety, Nanning 530004, Peoples R China 4.Chinese Acad Sci, Key Lab Mt Hazards & Surface Proc, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China 5.Guangxi Zhuang Autonomous Reg Geol Environm Monit, Guilin 541000, Peoples R China |
| Recommended Citation GB/T 7714 | Liao Li-ping,Zhu Ying-yan,Zhao Yan-lin,et al. Landslide integrated characteristics and susceptibility assessment in Rongxian county of Guangxi, China[J]. JOURNAL OF MOUNTAIN SCIENCE,2019,16(3):657-676. |
| APA | Liao Li-ping.,Zhu Ying-yan.,Zhao Yan-lin.,Wen Hai-tao.,Yang Yun-chuan.,...&Xu Ying-zi.(2019).Landslide integrated characteristics and susceptibility assessment in Rongxian county of Guangxi, China.JOURNAL OF MOUNTAIN SCIENCE,16(3),657-676. |
| MLA | Liao Li-ping,et al."Landslide integrated characteristics and susceptibility assessment in Rongxian county of Guangxi, China".JOURNAL OF MOUNTAIN SCIENCE 16.3(2019):657-676. |
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| Landslide integrated（4529KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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