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Sustainability 2015, 7(12), 16653-16669; doi:10.3390/su71215839

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

1
School of Geology and Geomatics, Tianjin Chengjian University, No. 26 Jinjing RD., Xiqing District, Tianjin 300384, China
2
Appraisal Center for Environment & Engineering Ministry of Environmental Protection, No. 8 Beiyuan RD., Chaoyang District, Beijing 100012, China
*
Author to whom correspondence should be addressed.
Academic Editor: Eric Vaz
Received: 14 September 2015 / Revised: 10 December 2015 / Accepted: 11 December 2015 / Published: 17 December 2015
View Full-Text   |   Download PDF [3950 KB, uploaded 17 December 2015]   |  

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. View Full-Text
Keywords: predisposing factor combination; Modified Information Value model; ROC curve; Baoxing catchment; China predisposing factor combination; Modified Information Value model; ROC curve; Baoxing catchment; China
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, Q.; Wang, D.; Huang, Y.; Wang, Z.; Zhang, L.; Guo, Q.; Chen, W.; Chen, W.; Sang, M. Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment. Sustainability 2015, 7, 16653-16669.

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