The Application of Multi-Criteria Decision-Making Model in Land Suitability Assessment

IntroductionLand suitability analysis and land use mapping are one of the most practical applications of Geographic Information Systems in land resource management. Complexities in soil have briefly limited studies on how it functions (Karlen, 2008). There are many methods from different centers including food and agriculture organizations (FAO), to evaluate land suitability. These methods are based on the characteristics of the land and the needs of the plant. Soil quality indicators are a set of measurable soil characteristics that affect crop production or the environment and are sensitive to land use change, management or conservation operations. (Brejda, 2000; Aparico and Costa, 2007). As a result, there is a global need for environmental issues, improvement of soil quality assessment methods for sustainable agricultural development and recognition of the sustainability of soil management and land use systems. Until now, various methods have been used to collect data, measure and evaluate soil quality, and laboratory analysis is the most common method, which has the advantage of being easy to use and characterizing and the quantitative characteristics of the test on different soil quality indicators (and Wang, 1998 Gong). Criteria for soil quality indicators should be a set of physical, chemical, biological characteristics or a combination of them (Doran and Parkin, 1997).Materials and MethodsIn the present study, the qualitative assessment of land suitability was investigated using fuzzy and parametric hierarchical analysis process models for the irrigated wheat and alfalfa crops. Soil characteristics, climatic conditions, topography and accessibility were selected based on the Food and Agriculture Organization framework and expert opinions. The interpolation function was used to plot values to points in terms of quality/ terrain characteristics for the type of operation and the evaluation was performed based on parametric and fuzzy analytical hierarchy process models. The process of evaluation is based on the FAO qualitative land evaluation system (FAO 1976a, b, 1983, 1985), which compares climatic conditions and land qualities/characteristics including topography, erosion hazard, wetness, soil physical properties, soil fertility, and chemical properties, soil salinity and alkalinity with each specific crop requirements developed by Sys et al. (1991a, b, 1993). Based on morphological and physical/chemical properties of soil profiles some 10 land units were identified in the study area.Climate data related to different stages of wheat growth were taken from ten years of meteorological data of the region (2007-2017) and the climatic requirements of the crop were extracted from the Table developed by (Sys et al., 1993). An interpolation technique using the ArcGIS ver 10.3 helped in managing the spatial data and visualizing the land index results in both models for preparing the final land suitability evaluation maps. The FAHP method and (Chang, 1996) method, which is a very simple method for generalizing the hierarchical analysis process to the fuzzy space, was used in order to assign weight to the criteria through. This method is based on computational mean of the experts’ opinion and the time normalization method and the use of triangular fuzzy numbers. A pairwise comparison matrix has been made fuzzy based on the experts’ opinion and using the triangular fuzzy numb. After calculating the weights of the criteria in the present research through the FAHP method, the entire criteria maps were overlaid through the use of the GIS function and the suitability maps were prepared for the main criteria. The main suitability maps went through weight overlaying eventually and the final map of suitability for wheat and alfalfa cultivation was produced. Results and DiscussionThe results of this study showed that the FAHP was an efficient strategy to increase the accuracy of weight allocation to criteria that affect the analysis of ground fit. The inability of conventional decision-making methods to account for uncertainty paves the way for the use of fuzzy decision-making methods. One of the drawbacks of the AHP is its inability to account for the uncertainty of judgments in pairwise comparison matrices. This defect is compensated by the FAHP method. Instead of considering a specific number in a pairwise comparison, a range of values in the FAHP is used for uncertainty for decision makers. The present research method can be useful for prioritizing lands, improving exploitation, conserving resources, and creating sustainable management. The results of this study, considering the main criteria of cultivation in the study area and the opinion of domestic experts, can provide useful insights into choosing the appropriate cultivation pattern in the region. The use of different fuzzy AHP methods as well as comparing the results of different fuzzy AHP methods in future research is recommended.