Landslide susceptibility analysis using fuzzy analytical hierarchical process and GIS in Kasese district.

Abstract

The main purpose of this study was to investigate landslide susceptibility in Kasese District. Fuzzy analytical hierarchical process was adopted to model the susceptible regions while considering a number of factors like land use and degree of slope. A landslide inventory containing landslide occurrences from 1994 to date was retrieved from a number of sources like scientific publications and reports to validate the model. A pairwise comparison using analytical Hierarchical process was carried out and from the pairwise comparison weights were generated and slope generated the highest weight of 30 followed by land cover at 21.33 and lithology at 23.33. Other factors had their varying weight. Principle Eigen Values were applied to the weights and a consistency index was applied and a consistency ratio of 0.087171012 was got that indicated that results were consistent. Fuzzy logic was later applied to the AHP and it gave weights of 26,20,20,18,7,7,2 for slope, land cover, lithology, fault lines, streams, roads and aspect respectively. A landslide susceptibility map was plotted and showed areas that were very susceptible to landslides. From analysis of the results using Fuzzy Analytical Hierarchical Process, it showed that Slope has the biggest contribution to landslides followed by land cover, lithology, fault lines, streams, roads and aspect respectively. It was concluded that FAHP and GIS offer a robust and comprehensive approach to modelling land susceptibility mapping as it Caters for integration of various criteria, assigning appropriate weights, providing spatial visualization leading to improved decision making and effective management strategies for landslides. The Study recommended that Susceptibility analysis using FAHP and GIS provides valuable insights but it’s crucial to consider the specific context and local conditions when making decisions and implementing mitigation measures