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

Abstract

In terms of food safety, it is important to use the lands correctly in agricultural production. In this study, potential crop suitability classes for wheat cultivation were created by using the fuzzy model and GIS together. Spatial and spectral factors considered as model inputs were separated four main groups, such as soil (drainage, depth, texture, CaCO3, stoniness, pH, organic matter, salinity, ESP), topography (slope), water availability (irrigation) and vegetation indices (NDVI). Criterion maps were standardized with the fuzzy membership model. Analytical Hierarchy Process was used to determine the weights of the factors. The vegetation change between years in the study area was determined by using NDVI values obtained from Landsat satellite images. In addition, the effect of temporal difference on land use and land suitability was evaluated. Land suitability index was created in GIS environment by weighted linear combination method and divided into four main suitability classes. The results with the Fuzzy method showed 9.7% (805 ha) of the study area as highly suitable for wheat, 46.5% (3868 ha) as medium suitable, 27.6% (2297 ha) as marginally suitable and 16.2% (1350 ha) as unsuitable. According to these classes, highly suitable and medium suitable classes are the areas that should be evaluated primarily in agricultural production. The Fuzzy model and GIS integration can be effectively used to identify priority areas for crop cultivation and sustainable land use management.