Dynamic simulation of urban expansion through a CA-Markov model Case study: Hyrcanian region, Gilan, Iran

Abstract

Urban sprawl has become a remarkable feature in urban development, especially in developing countries, in the last decades. To face this phenomenon, it is required to first forecast auto-spreading orientation rural areas over time in order to avoid shapeless urban growth. Although GIS/RS and CA- Markov models are applied to study urban growth patterns the world over, very few studies have applied these methods to examine the urban growth of Iran. A major land use change is detected here from 1989 to 2013. In this study the future sprawl of this province is forecasted for target years of 2025 and 2037 through a simulation. The results predict an alarming increase in urban development for the target years of 2025 and 2037, with an expansion is predicted to develop of 11510 and 18320 ha, respectively. In sum, this model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable urban development providing decision-makers.