Integrated fuzzy, AHP and GIS techniques for land suitability assessment in semi-arid regions for wheat and maize farming

Abstract

Abstract The accurate evaluation of land suitability for special agriculture production plays an important role to decrease the negative environmental impacts. The current study aimed to apply fuzzy set, AHP and GIS techniques for analyzing land suitability to wheat and maize production in 5474.27 ha of saline and calcareous soils located in semi-arid regions, east of Iran. The conditioned Latin hypercube sampling approach was applied to take 72 point-samples from the agricultural land use. For evaluating the land suitability climate data, soil and topography information was transformed to a fuzzy set data. After that, an accurate assessment model of land suitability for wheat and maize farming was developed by integrating AHP (analytic hierarchy process) and fuzzy set approaches in ArcGIS environment. The results indicated that the highest specific weight was obtained for soil texture (0.221) and the lowest was found for exchangeable sodium percentage (0.012). Specifically, 14.68% (803.75 ha), 78.23% (4282.53 ha) and 7.08% (387.99 ha) of the studied area were highly, moderately and marginally suitable for wheat production, respectively. Moreover, 2.75% (150.52 ha), 61.51% (3366.99 ha) and 35.74% (1956.76 ha) of this region were highly, moderately and marginally suitable for maize production, respectively. It was concluded that integrating fuzzy set, AHP and GIS techniques could be an accurate and effective method for better land use planning and management for agriculture productions.