Accelerating urban growth and land use/cover changes places increasingly pressure on the natural environment and human welfare and have become a global concern. Iran, as a developing country, is also experiencing growth of its urban areas during the last decades by high rate of ruralurban migration along with rapid socio-economic and political changes that has resulted in degrading environmental quality in many parts of Iran, particularly in the metropolitan areas such as Isfahan. Therefore, developing methods for assessing different urban growth planning scenarios and simulating urban expansion is critically important. The main goal of this study was simulating future urban expansion of Isfahan Metropolitan area from 2010 to 2050, by making use of cellular automata methodology in the SLEUTH modelling. The model was calibrated using historical data extracted from a time series of satellite images. The input data required by the model including Slope, Land use, Exclusion, Urban extent, Transportation and Hillshade were obtained from satellite images based on supervised classification. This research used the four images of Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) acquired 1976, 1990, 2001, and 2010. Two scenarios were planned to simulate the spatial pattern of urban growth. The first scenario was historical urban growth, which permitted urban development maintenance of the historical trend and the second scenario was a more compact growth as an answer to hypothetical policies and the lack of land to decrease urban spreading. Calibration of the SLEUTH model for Isfahan metropolitan area showed a high spread coefficient, which means that the predicted mode of growth in Isfahan is "organic" or edge growth. In Isfahan metropolitan area, topography was also shown to have an enormous effect in controlling the urban development. The results of this study invites many opportunities for further studies in many other regions which are experiencing growth of their urban areas and can be useful for planners, and policy makers to implement preventative or controlling factors in advance and make more informed strategic decisions.

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