A novel data-driven approach to pairwise comparisons in AHP using fuzzy relations and matrices for landslide susceptibility assessments

Over the last 2 decades, Analytical Hierarchy Process (AHP) has attracted great interest of the researchers in many fields like landslide susceptibility analyses. In addition to the classical AHP method, utilization of hybrid AHP methods, such as fuzzy AHP (F-AHP), has also increased in recent years. In this study, adhering to the general operating principles of AHP, except for the pairwise comparison concept, a new data-driven F-AHP method, called FR-AHP, which can be applied in landslide susceptibility mapping using fuzzy relations and fuzzy matrices concepts, is proposed. Fuzzy Geometric Mean (FGM) and Fuzzy Extent Analyses (FEA) methods were also applied to compare the proposed FR-AHP method in Seydikemer (Mugla) region, located in the southwestern part of Turkey. Ten parameters and 108 mapped landslides were taken into account for the landslide susceptibility analyses and 3 maps were produced and compared by Area Under Curve (AUC) approach. AUC values of FEA, FGM and FR-AHP maps were calculated as 0.813, 0.806 and 0.802, respectively. Considering the difficulties in evaluating the effects of some parameters according to expert opinion and the limitations in the studies conducted in large regions, it is of great importance in terms of using more objective data-driven methods in landslide susceptibility analyses. When considered from this point of view, it is thought that the proposed FR-AHP method in this study has the potential to be a feasible, objective and high-performance approach, supported by future studies in different regions.

Automated summary

A new data-driven fuzzy AHP method (FR-AHP) is proposed for landslide susceptibility mapping. The method is compared with FEA and FGM methods in a region in Turkey, and the AUC values are calculated. The results show that the FR-AHP method has the potential to be a feasible, objective, and high-performance approach.