Australian Journal of Earth Sciences (2004) 51, 439–450 Landslide susceptibility mapping using the fuzzy gamma approach in a GIS, Kakan catchment area, southwest Iran M. H. TANGESTANI Department of Earth Sciences, Faculty of Sciences, Shiraz University, 71454 Shiraz, Iran (tangestani@susc.ac.ir). The northwestern Fars province of Iran is prone to landslides. In order to help the planners in the selection of suitable locations to implement development projects, a landslide susceptibility map has been produced for the Kakan catchment area using the gamma aggregation operation of the fuzzy approach. Lithology, slope angle, slope aspect, land cover, weathering depth, proximity to roads, topographical elevation, and soil depth were considered as landslide causal factors for the study area. Three values for gamma were examined and output maps were evaluated using the known landslides. Performing fuzzy gamma operation with 0.94 for gamma and classifying the area yielded an output susceptibility map with four zones: non-susceptible, moderate susceptibility, high suscepti- bility, and very high susceptibility. Gamma values <0.94 decreased the fuzzy membership functions to low susceptibility zones, and eliminated the high and very high classes. Gamma values >0.94 moved the output fuzzy membership function values to high and very high landslide susceptibilities and eliminated the moderate susceptible zones. Comparing the known landslides of the area with the output susceptibility map showed that 93.9% of the identified landslides were located in the high susceptible zone and 6.1% in very high susceptible zone. KEY WORDS: fuzzy logic, GIS, Iran, landslide susceptibility mapping, zonation. INTRODUCTION Landslide hazard and risk zoning and mapping for urban and rural areas is widely performed around the world (Carrara et al. 1991, 1992; Hutchinson & Chandler 1991; Hutchinson et al. 1991; Lee et al. 1991; Siddle et al. 1991; Moon et al. 1992; Morgan et al. 1992; van Westen et al. 2000; Parise 2001; Krejci et al. 2002). A landslide zonation map divides the land surface into zones of varying degrees of stability, based on estimated significance of causal factors in inducing instability. Engineers, earth scientists, and planners are interested in assessment of landslide susceptibility for two main purposes: (i) the landslide hazard maps identify and delineate potentially unstable areas, so that environmental regeneration programs can be initiated through the adoption of suitable mitigation measures; and (ii) these maps help planners to choose favourable locations for siting development schemes, such as building and road construction. Even if the hazardous areas cannot be avoided altogether, their recognition in the initial stages of planning may help the adoption of suitable precautionary measures. The main factors that influence landslides are dis- cussed in Varnes (1984) and Hutchinson (1995). Normally the most important factors are bedrock geology (lithology, structure, degree of weathering), geomorphology (slope gradient, aspect, and relative relief), soil (depth, structure, permeability, and porosity), land use and land cover, and hydrologic conditions. Soeters and van Westen (1996) and Leroi (1996) dis- cussed the methods that can be used to assess suscepti- bility to landslide. Traditional methods of landslide hazard mapping have been based on extensive fieldwork by expert geologists in landslide-prone areas. This is a slow, expensive, very labour-intensive, and also a low- accuracy and low-repeatability operation, and as such cannot be widely applied. With the increasing avail- ability of high-resolution spatial datasets, GIS, and computers with large and fast processing capacity, it is becoming possible to partially automate the landslide hazard and susceptibility mapping process and thus minimise fieldwork. Several studies have used GIS and statistics for landslide hazard and susceptibility mapping (Wadge 1988; Gupta & Joshi 1990; Pachauri & Pant 1992; Wang & Unwin 1992; Binaghi et al. 1998; Guzzetti et al. 1999; Gritzner et al. 2001; Sakellariou & Ferentinou 2001; Ohlmacher & Davis 2003), but mapping studies using fuzzy approaches are limited (Juang et al. 1992; Davis & Keller 1997; Binaghi et al. 1998; Ercanoglu & Gokceoglu 2002). The northwestern Fars province, Iran, is affected by landslides. The Kakan area, 51°42'30 to 51°51'30 and 30°32'30 to 30°43'00, (Figure 1) is mountainous, located in the Zagros Mountain Range, and is subject to heavy precipitation during the autumn and winter. A landslide susceptibility map was required as part of comprehensive detailed investigations for the development plans by local government. The objective of the present study was to generate the landslide susceptibility map of a landslide- prone area of 114 km 2 in the Kakan catchment area (Figure 1), based on a fuzzy approach. The study includes four main steps: (i) producing the causal factor maps through field studies and digital data processing; (ii) evaluating the fuzzy membership functions for evidence maps using a modified method initially discussed by Anabalgan (1992); (iii) the use of GIS to produce the