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

Abstract

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).

Model of Slum Area Management Based on Socio-Spatial Approach. The Case of Baubau City, Indonesia

“…If it is combined into a comprehensive socio-spatial database, it allows for spatial interventions directed to social needs that can be stratified according to scale [34]. Fuzzy Multi Criteria Decision Making (MCDM) is one application in geospatial information management [36], [37]. The integration of fuzzy logic into geospatial information systems has also been employed in various urban planning studies [38], [39], [40], [41], 42].…”

“…The next step in Fuzzy logic modelling was to create the degree of membership of each criterion of socio-spatial variables that had been pre-rasterized. The membership value, degree or function is the main characteristic of reasoning with the fuzzy logic [36], [38], [52], [53]. The membership degree of each criterion is 0-1 using the fuzzy membership extension in Arc GIS 10.3 software.…”

GIS-Based Land Suitability Classification for Wheat Cultivation Using Fuzzy Set Model

“…Fuzzy modeling is a suitable approach for defining continuous or uncertain structures (Burrough and Frank, 1996). Fuzzy logic-based land evaluation methods are widely used to determine agricultural land suitability (Garofalo, 2020;Zhang, 2015;Nurmiaty and Baja, 2014;Sicat et al, 2005;Baja, et al, 2002).…”

Land Suitability Evaluation for Cassava Production Using Integral Value Ranked Fuzzy AHP and GIS Techniques

“…Land evaluation is concerned with the process of determining the optimal use potential of land for a specific purpose based on its attributes [2]. As a core element of land use planning, land resource evaluation is central at all stages of planning and implementation [3] [4]. As it guides decision-makers in attempting to select appropriate types of land use, determining best spatial locations of planned agricultural activity, identifying opportunities for land use change and the outcomes of changing land use policies [3] [4] Land suitability evaluation is essential for production planning and the sustainable use of land over time [5].…”

“…As a core element of land use planning, land resource evaluation is central at all stages of planning and implementation [3] [4]. As it guides decision-makers in attempting to select appropriate types of land use, determining best spatial locations of planned agricultural activity, identifying opportunities for land use change and the outcomes of changing land use policies [3] [4] Land suitability evaluation is essential for production planning and the sustainable use of land over time [5]. Furthermore, it provides information on the potentials and constraints of land for a defined land use type for optimum crop performance [5].…”