scholarly journals Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran

2012 ◽  
Vol 63 (2) ◽  
pp. 965-996 ◽  
Author(s):  
Hamid Reza Pourghasemi ◽  
Biswajeet Pradhan ◽  
Candan Gokceoglu
Keyword(s):  
Fuzzy Logic ◽  
Analytical Hierarchy Process ◽  
Landslide Susceptibility ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Hierarchy Process

scholarly journals Coupling Fuzzy logic and Analytical Hierarchy Process (FAHP) with GIS for Landslide Susceptibility Mapping (LSM) in Ziz upper watershed, SE Morocco

2021 ◽  
Author(s):  
Mohamed Manaouch ◽  
Sadiki Mohamed ◽  
Fenjiro Imad
Keyword(s):  
Fuzzy Logic ◽  
Analytical Hierarchy Process ◽  
Landslide Susceptibility ◽  
Susceptibility Mapping ◽  
Environmental Data ◽  
Landslide Susceptibility Mapping ◽  
Susceptibility Modeling ◽  
Significant Performance ◽  
Auc Value ◽  
Hierarchy Process

Abstract Landslides have become a destructive geo-hazard in many countries, which seriously cause damage to the human lives, infrastructure and properties. They result from the movement of soil on unstable slopes in mountainous areas. This caught attention to study the increasing incidences of landslides in many areas including Morocco. In this study, the fuzzy logic and analytical hierarchy process (FAHP) integrated with the geographic information system (GIS) are used to determinate the landslide susceptibility modeling in the Ziz upper watershed, southeast Morocco. The geo-environmental data that were used in the landslide susceptibility mapping (LSM) included: elevation, lithology, slope, land use/land cover (LULC), river, road, fault, and rainfall maps. FAHP model showed that 16.7% of the study area had high landslide susceptibility. However, the riskiest areas are situated in the upstream western parts. The resultant map of landslides hazards was validated using an inventory of 148 landslides events in the study area. The FAHP model showed a significant performance, the area under curve (AUC) value for this case study is 0.885.

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