Identification of Industrial Clusters and Suitable Industrial Development Zones Using Multi- Criteria Decision Making Models in GIS (Case study: Gorgan, Gonbad- Kavus and Aq- Qala Townships in Golestan Province of Iran)

Nowadays, the urban community has been affected by population growth and migration, which collectively have led to unplanned construction and unrestrained urban expansion. In the meantime, the industrial sector is one of the most important factors that have a great impact on the concentration of population and activities, and thus accelerates the growth process and creates a plethora of changes in the landscape. The lack of proper attention to regional spatial planning often leads to unplanned expansion of industrial areas, and it can cause instability. The main objectives of this study are to identify industrial clusters and determine the optimal areas for industrial development. In this study, using statistical information and applying localization coefficient (LQ) analysis, cumulative and competitive effects of industrial clusters of Gorgan, Gonbad-Kavus and Aq-Qala Townships were identified. Then, using 16 indicators as factors and constraints for the Weighted Linear Combination (WLC) and Order Weighted Average (OWA) decision making models in GIS, the optimum locations of the industries were identified. According to the results, five industrial clusters including food and beverage industries, wood and wood products except sofa, paper and paper products production, production of refined petroleum products and manufacturing of materials and chemical products were identified in the study area. The research findings show that adjacent areas to urban settlements, due to geographical advantage, proximity to urban infrastructures and comfortable accessibility to human resources, are suitable areas for the establishment of industries. Furthermore, the cities of Gonbad-Kavus and Aq-Qala had the highest and the lowest areas of the suitable zones for industrial development, respectively.