GIS-Based Flood Vulnerability Assessment Using Integral Value of Inverse Function Ranked Fuzzy-AHP Technique. - Atijosan Abimbola; Isa Ibrahim (Covenant Journal of Informatics and Communication Technology, 2023)
Flooding is a common natural disaster which often causes extensive agricultural, infrastructural and socio-economic damages. In this study, a Geographic Information System (GIS) based flood vulnerability assessment using an improved integral value of inverse function ranked, Fuzzy Analytical Hierarchical Process (FAHP) technique for fast and accurate computation of flood vulnerability assessment across Oyo State, Southwest Nigeria is presented. The flood vulnerability assessment focuses on determining the spatial extent and flood vulnerability class of cultivated lands, settlements and road infrastructures across the study area for effective flood management. Based on the literature review, six prominent flood causative factors namely, elevation, slope, soil, rainfall, drainage density and land use/land cover were used as input criteria in this study. The improved integral value ranked FAHP technique uses both the left and right inverse function of a triangular membership function with an index of optimistic function to derive the weight for each input criterion. A flood vulnerability map for the study area was created using Geographic Information System (GIS) techniques based on the aggregation of the input causative criteria and their derived weights. Furthermore, maps showing the spatial extent and the flood vulnerability classes of cultivated lands, settlements and paved road infrastructures across the study area were made. The output vulnerability maps serve as an early warning system that would further assist policymakers and stakeholders in minimizing the effects of flooding on food security, road infrastructures, lives and properties across the study area.