Simulating Urban Growth in Tehran Using the CA-Markov Model

The trend towards concentration of people in urban areas in developing countries has caused rapid urban expansions. This situation necessitates proper management and planning to avoid profound negative environmental and socioeconomic impacts. Urban planners require temporal and spatial information related to the pattern and extent of the urban growth for better understanding of its process and effects and to then set effective urban management and planning policies. Integration of Geographic Information Systems (GIS) and Remote Sensing (RS) technologies can provide efficient tools for collecting and analyzing the needed spatiotemporal informations. Tehran, the capital of Iran, has witnessed rapid growth since the last two decades. In this research, after investigating and modeling urban expansion in the last two decades, a model has been develop to understand the growth dynamics of this metropolis and to predict its expansion for the next two decades as a base to set urban management policies. In this research, a CA-Markov based urban growth simulation and predicting model has been applied and calibrated with historical data derived from a time series of Landsat satellite imagery captured at 1988, 2000 and 2006. Base on the land use/cover maps obtained from classification of satellite images, urban area has been increased 11% (about 56 km2) during 1988-2006. In order to simulate the urban growth in 2015 and 2025, the CA-Markov model has been utilized; and the result indicates that from 2006 to 2025, the urban areas would increase 3% (about 15 km2). The results of this research represent efficiency of integrated CA-Markov model in monitoring the urban growth process and its pattern in the last years and to predict urban growth for the future.Also, applying a multi-criteria decision making method to characterize urban growth and development parameters is another point of this research.