Modelling organic farming suitability by spatial indicators of GIS integrated MCDA in Golestan Province, Iran

Abstract

Organic farming suitability can improve the health of environment, agroecosystems and humans, quality of products, and local economy. Organic agricultural system is not very much evolved in Iran. In this paper a model is proposed to identify the suitable zones in 14 counties of Golestan Province, northeast of Iran, for the development of organic farming using spatial indicators, spatial analysis and Multi-Criteria Decision Analysis (MCDA). In this model, some important criteria such as climatic variables, topographic factors, soil characteristics, ecological variables, environmental variables and developmental variables were evaluated and considered as spatial indicators. The thematic layers were classified based on agronomical requirements tables of organic farming and were overlaid based on Weighted Overlay Analysis (WOA) in ArcMap software. Final maps were separately generated and classified to five classes of suitability degree for spring and winter crops. According to the results of model, development of organic farming is possible for up to 14.72 and 17.76 percent of the current lands of Golestan Province in Iran for organic spring and winter cropping, respectively. In this research, we developed a land suitability model for organic farming based on the evaluation of spatial variables in Geographic Information System (GIS) and MCDA. Results provided useful information that can be used as decision support tools in the development of organic agriculture in Golestan Province, other similar regions in Iran and other countries in the world.