A comparative assessment of information value, frequency ratio and analytical hierarchy process models for landslide susceptibility mapping of a Himalayan watershed, India

2018 ◽  
Vol 78 (4) ◽  
pp. 2431-2448 ◽  
Author(s):  
Swati Sharma ◽  
A. K. Mahajan
Keyword(s):  
Analytical Hierarchy Process ◽  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Comparative Assessment ◽  
Susceptibility Mapping ◽  
Information Value ◽  
Process Models ◽  
Landslide Susceptibility Mapping ◽  
Hierarchy Process

scholarly journals GIS-based earthquake-triggered-landslide susceptibility mapping with an integrated weighted index model in Jiuzhaigou region of Sichuan Province, China

2019 ◽  
Vol 19 (9) ◽  
pp. 1973-1988 ◽  
Author(s):  
Yaning Yi ◽  
Zhijie Zhang ◽  
Wanchang Zhang ◽  
Qi Xu ◽  
Cai Deng ◽  
...  
Keyword(s):  
Analytical Hierarchy Process ◽  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Sichuan Province ◽  
Controlling Factors ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Index Model ◽  
Weighted Index ◽  
Hierarchy Process

Abstract. A Mw=6.5 earthquake struck the Jiuzhaigou region of Sichuan Province, China, at 21:19 LT on Tuesday, 8 August 2017, and triggered a large number of landslides. For mitigating the damages of earthquake-triggered landslides to individuals and infrastructures of the earthquake-affected region, a comprehensive landslide susceptibility mapping was attempted with an integrated weighted index model by combining the frequency ratio and the analytical hierarchy process approaches under a GIS-based environment in the heavily earthquake-affected Zhangzha town of the Jiuzhaigou region. For this purpose, a total number of 842 earthquake-triggered landslides were visually interpreted and located from Sentinel-2A images acquired before and after the earthquake at first, and then the recognized landslides were randomly split into two groups to establish the earthquake-triggered landslide inventory, among which 80 % of the landslides were used for training the integrated model and the remaining 20 % for validation. Nine landslide controlling factors were considered including slope, aspect, elevation, lithology, distance from faults, distance from rivers, land use–land cover, normalized difference vegetation index and peak ground acceleration. The frequency ratio was utilized to evaluate the contribution of each landslide controlling factor to landslide occurrence, and the analytical hierarchy process was used to analyse the mutual relationship between landslide controlling factors. Finally, the landslide susceptibility map was produced by using weighted overlay analysis. Furthermore, an area under the curve approach was adopted to comprehensively evaluate the performance of the integrated weighted index model, including the degree of model fit and model predictive capability. The results demonstrated the reliability and feasibility of the integrated weighted index model in earthquake-triggered landslide susceptibility mapping at a regional scale. The generated map can help engineers and decision makers assess and mitigate hazards of the earthquake-triggered landslides to individuals and infrastructures of the earthquake-affected region.

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