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Recently, spatial data on land resources have become more available, detailed, and sophisticated. Accordingly, it requires a method that could deal with those complex and detailed data in an effective way. A fuzzy set method with the semantic import model (SIM) was utilized within a raster GIS (geographic information systems) to analyze the area of Maros Regency on a reconnaissance scale basis. In this study, land attribute values were converted into continuous values (ranging from 0 to 1.0), according to the class limit determined based on field experiences, results of experiments, or fixed conventional standards. The evaluation criteria were based on land attributes which are divided into two main components: soil profile and topography. Each of land attributes within each component was valued from 0 (minimum) to 1.0 (maximum) according to the suitability of maize. Those values were represented as membership values, also ranging from 0 to 1.0. The result from land suitability analysis in Maros Regency for maize cultivation indicates that around 25% of land areas have a land suitability index (LSI) value of above 0.70 (suitable and very suitable), about 11% fall between 0.50 and 0.70 (moderately suitable), and 63% under 0.5 (not suitable). The main limiting factor for maize cultivation in this region is topography, especially slope gradient (s).

Using Fuzzy Set Approaches in a Raster GIS for Land Suitability Assessment at a Regional Scale: Case Study in Maros Region, Indonesia