Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment

Qianqian Wang, Dongchuan Wang, Yong Huang, Zhiheng Wang, Lihui Zhang, Qiaozhen Guo, Wei Chen, Wengang Chen and Mengqin Sang
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Qianqian Wang: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
Dongchuan Wang: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
Yong Huang: Appraisal Center for Environment & Engineering Ministry of Environmental Protection, No. 8 Beiyuan RD., Chaoyang District, Beijing 100012, China
Zhiheng Wang: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
Lihui Zhang: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
Qiaozhen Guo: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
Wei Chen: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
Wengang Chen: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
Mengqin Sang: School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China

Sustainability, 2015, vol. 7, issue 12, 1-17

Abstract: Landslides are usually initiated under complex geological conditions. It is of great significance to find out the optimal combination of predisposing factors and create an accurate landslide susceptibility map based on them. In this paper, the Information Value Model was modified to make the Modified Information Value (MIV) Model, and together with GIS (Geographical Information System) and AUC (Area Under Receiver Operating Characteristic Curve) test, 32 factor combinations were evaluated separately, and factor combination group with members Slope, Lithology, Drainage network, Annual precipitation, Faults, Road and Vegetation was selected as the optimal combination group with an accuracy of 95.0%. Based on this group, a landslide susceptibility zonation map was drawn, where the study area was reclassified into five classes, presenting an accurate description of different levels of landslide susceptibility, with 79.41% and 13.67% of the validating field survey landslides falling in the Very High and High zones, respectively, mainly distributed in the south and southeast of the catchment. It showed that MIV model can tackle the problem of “no data in subclass” well, generate the true information value and show real running trend, which performs well in showing the relationship between predisposing factors and landslide occurrence and can be used for preliminary landslide susceptibility assessment in the study area.

Keywords: predisposing factor combination; Modified Information Value model; ROC curve; Baoxing catchment; China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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