Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops

Abstract Cultivation priority planning is a very important and vital step in suitable and sustainable revenue of agricultural land. The growth of urban areas and industrial intensification has contributed to a reduction in valuable agricultural lands and to various environmental impacts including climate change. This reduction in agricultural land severely impacts food production and food security. In order to effectively address this issue, spatial analytical and optimization methods based on evaluating multiple criteria decision are needed to evaluate the capability and suitability of available lands for current and future food production. The objective of this study is to implement the GIS and multi-criteria decision analysis (MCDA) techniques as an improved method of multi-criteria decision making for evaluating areas suitable for cultivation priority planning of maize, rape and soybean crops. For this purpose, 12,000 ha land which is located in Ardabil province, west-north of Iran was investigated by excavation of 167 soil profiles and 313 augers. After soil sampling and analysis, soils were classified in Aridisols. 24 soil series and 66 land units were identified and separated in study area. The several criteria had limitation for maize, rape and soybean cultivation in studying lands which the most limiting evaluation criteria including soil depth, slope, climate, pH, electrical conductivity, exchangeable sodium percentage, calcium carbonate and gypsum were selected for usage in prioritization models by principal component analysis and multi-dimensional scaling methods. Selected criteria were very important in growth of maize, rape and soybean. Simple additive weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy TOPSIS methods were used for cultivation priority planning of maize, rape and soybean crops in land units. Analytical Hierarchy Process (AHP) and Fuzzy AHP approaches were used to determine weight values of the criteria. Multivariate variance analysis proves significant difference among three methods at 0.05 probability level. With attention to allocated scores by prioritization models, crops cultivation priority was determined as maize, rape and soybean in land units, respectively and maize crop was preferred to other plants. The statistical analysis results with regard to mean comparison derived from least significant difference (LSD) test showed that Fuzzy TOPSIS method set cultivation priority planning of maize, rape and soybean crops for land units more accurately than the others, due to fuzzy TOPSIS method used appropriate values of criteria weights, twin comparing nature of alternative (crop) from positive and negative ideal, data standardization, mathematical equations and matrixes as well as fuzzy logic relations and principles for calculation of process performing. This study emphasizes the successful application of MCDA in dealing with complicated issues in the context of cultivation priority planning management. It is anticipated that, the integration of this developed framework in the planning policies of cultivation priority in developing countries as an effective tool for integrated regional land use planning can help in conducting better control over soil, land and environment losses.