Map India 2003 Disaster Management Map India Conference 2003 © GISdevelopment.net, All rights reserved. Landslide susceptibility mapping using the fuzzy gamma operation in a GIS, Kakan catchment area, Iran Majid H. Tangestani Dept. of Earth Sciences, Faculty of Sciences, Shiraz University, 71454 Shiraz, Iran Tel: +98 711 2284572, Fax: +98 711 2280926 E-mail: tangestani@geology.susc.ac.ir Abstract Northwestern Fars province, Iran, is prone to landslides. In order to help the planners for selecting suitable locations to implement development projects a landslide susceptibility map was produced for the Kakan catchment area using the gamma 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. The factor maps were input into GIS and landslide hazard evaluation factor (LHEF) rating and fuzzy membership functions were assessed for each class of the factor maps. A weighting factor was then considered for each factor map and multiplied to fuzzy membership functions to justify the affect of each data layer on the output fuzzy membership functions due to the expert’s opinion. Three values for gamma were examined and output maps were evaluated using the known landslides. A gamma value of 0.94 yielded the most reliable susceptibility for landslides. Comparing the known landslides of the area with the output susceptibility map showed that the identified landslides were located in the high susceptibility zones. Introduction Landslide hazard and risk zoning and mapping for urban and rural areas is widely performed around the world (Siddle et al 1991, Lee et al 1991, Hutchinson and Chandler 1991, Hutchinson et al 1991, Morgan et al 1992, Carrara et al 1991, and 1992, Moon et al 1992). A landslide zonation map divides the land surface into zones of varying degrees of stability, based on an estimated significance of casuative factors in inducing instability. Engineers, earth scientists, and planners are interested in assessment of landslide susceptibility and hazard because of two purposes: (1) The landslide hazard maps identify and delineate unstable hazard-prone areas, so that environmental regeneration programs can be initiated adopting suitable mitigation measures; (2) These maps help planners to choose favourable locations for siting development schemes, such as building and road construction. Even if the hazardous areas can not be avoided altogether, their recognition in the initial stages of planning may help to adopt suitable precautionary measures. The main factors which influence landsliding are discussed in Varnes (1984) and Hutchinson (1995). Normally the most important factors are bedrock geology (lithology, structure, degree of weathering), geomorphology (slope gradient, aspect, relative relief), soil (depth, structure, permeability, porosity), land use and land cover, and hydrologic conditions. Soeters and van Westen (1996) and Leroi (1996) discuss the methods which can be used to assess probability of landsliding. Traditional methods of landslide hazard mapping have been based on extensive fieldwork by expert geologists in potentially dangerous areas. This is slow, expensive and very labor intensive operation, and as such can not be widely applied. With the increasing availability of high resolution spatial data sets, GIS, and computers with large and fast processing capacity, it is becoming possible to partially automate the landslide hazard and susceptibility mapping process and minimize fieldwork. Several studies have used GIS and statistics for landslide hazard and susceptibility mapping (Wadge 1988, Gupta and Joshi 1990, Wang Shu-Quiang and Unwin 1992, Pachauri and Pant 1992, Binaghi et al 1998, Guzzetti et al 1999, Skellariou and Ferentinou 2001, Gritzer et al 2001), but mapping studies using fuzzy approaches are limited (for example, Juang et al 1992, Davis and Keller 1997,