IMHE OpenIR  > 山地灾害与地表过程重点实验室
An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic
Zhu, A-Xing1,2; Wang, Rongxun2; Qiao, Jianping4; Qin, Cheng-Zhi3; Chen, Yongbo4; Liu, Jing2; Du, Fei2; Lin, Yang3; Zhu, Tongxin5
Corresponding AuthorZhu, A-Xing ; Qiao, Jianping
2014-06-01
Source PublicationGEOMORPHOLOGY
ISSN0169-555X
Volume214Pages:128-138
SubtypeArticle
AbstractThis paper presents an expert knowledge-based approach to landslide susceptibility mapping in an effort to overcome the deficiencies of data-driven approaches. The proposed approach consists of three generic steps: (1) extraction of knowledge on the relationship between landslide susceptibility and predisposing factors from domain experts, (2) characterization of predisposing factors using GIS techniques, and (3) prediction of landslide susceptibility under fuzzy logic. The approach was tested in two study areas in China - the Kaixian study area (about 250 km(2)) and the Three Gorges study area (about 4600 km(2)). The Kaixian study area was used to develop the approach and to evaluate its validity. The Three Gorges study area was used to test both the portability and the applicability of the developed approach for mapping landslide susceptibility over large study areas. Performance was evaluated by examining if the mean of the computed susceptibility values at landslide sites was statistically different from that of the entire study area. A z-score test was used to examine the statistical significance of the difference. The computed z for the Kaixian area was 3.70 and the corresponding p-value was less than 0.001. This suggests that the computed landslide susceptibility values are good indicators of landslide occurrences. In the Three Gorges study area, the computed z was 10.75 and the corresponding p-value was less than 0.001. In addition, we divided the susceptibility value into four levels: low (0.0-0.25), moderate (0.25-0.5), high (0.5-0.75) and very high (0.75-1.0). No landslides were found for areas of low susceptibility. Landslide density was about three times higher in areas of very high susceptibility than that in the moderate susceptibility areas, and more than twice as high as that in the high susceptibility areas. The results from the Three Gorge study area suggest that the extracted expert knowledge can be extrapolated to another study area and the developed approach can be used in large-scale projects. Results from these case studies suggest that the expert knowledge-based approach is effective in mapping landslide susceptibility and that its performance is maintained when it is moved to a new area from the model development area without changes to the knowledge base. (C) 2014 Elsevier B.V. All rights reserved.
KeywordLandslide Susceptibility Mapping Expert Knowledge-based Approach Fuzzy Logic Geographic Information System
WOS HeadingsScience & Technology ; Physical Sciences
DOI10.1016/j.geomorph.2014.02.003
WOS Subject ExtendedPhysical Geography ; Geology
Indexed BySCI
WOS Keyword3 GORGES AREA ; HAZARD ASSESSMENT ; ASTER IMAGERY ; LANTAU ISLAND ; YANGTZE-RIVER ; SOIL SURVEY ; HONG-KONG ; CHINA ; INFORMATION ; PREDICTION
Language英语
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary
WOS IDWOS:000336345700010
Funding OrganizationNatural Science Foundation of China(41023010 ; Ministry of Science and Technology of China(2010DFB24140 ; National High Technology Research and Development Program of China (863 Program)(2011AA120305) ; Vilas Associate Award ; Manasse Chair Professorship from the University of Wisconsin-Madison ; 40971236) ; 2011BAK12B01)
Citation statistics
Cited Times:93[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/9958
Collection山地灾害与地表过程重点实验室
人事教育处
Affiliation1.Nanjing Normal Univ, Sch Geog, Nanjing, Jiangsu, Peoples R China
2.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu, Peoples R China
5.Univ Minnesota, Dept Geog, Duluth, MN 55812 USA
Recommended Citation
GB/T 7714
Zhu, A-Xing,Wang, Rongxun,Qiao, Jianping,et al. An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic[J]. GEOMORPHOLOGY,2014,214:128-138.
APA Zhu, A-Xing.,Wang, Rongxun.,Qiao, Jianping.,Qin, Cheng-Zhi.,Chen, Yongbo.,...&Zhu, Tongxin.(2014).An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic.GEOMORPHOLOGY,214,128-138.
MLA Zhu, A-Xing,et al."An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic".GEOMORPHOLOGY 214(2014):128-138.
Files in This Item:
File Name/Size DocType Version Access License
An expert knowledge-(2425KB)期刊论文出版稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhu, A-Xing]'s Articles
[Wang, Rongxun]'s Articles
[Qiao, Jianping]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhu, A-Xing]'s Articles
[Wang, Rongxun]'s Articles
[Qiao, Jianping]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhu, A-Xing]'s Articles
[Wang, Rongxun]'s Articles
[Qiao, Jianping]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.