Feasibility and Zoning Oive Prone Area using GIS and Genetic Algorithm in Lorestan Province



Prediction of the agricultural developmental problems has ever been one of the goals of proper agricultural development, to gain more productions from the minimum resources. The goal of this research is zoning prone area of olive cultivation with two methods: GIS and Genetic Algorithm. Also the results have been compared with the current olive cultivation areas in Lorestan province and the results compared the two methods with each other. Cultivation zoning were accomplished for 17 metrological stations inside and out of the province within 12 years common statistical period. AHP model used for weighting in GIS and Permutation model used for Genetic Algorithm method. Current olive cultivation according to Ministry of Agriculture statistics is in western, central and southern area in Lorestan province. Results represent 70.1 area percent subscription in first priority with GIS method and 68.5 area percent subscription in GA method with the current olive area cultivation in Lorestan. Also results show that comparison of two methods with each other represent 53.3 area percent subscriptions in first priority area of GIS method. Therefore, cultivation potential is in central and southern area in Lorestan and GIS and GA methods are able for zoning prone area.