In recent decades, along with urbanization, various models have been used to urban growth prediction. In this regard, Urban models based on the automata technique have emerged under the paradigm of a self-organizing system, with cellular automata (CA) being the simplest
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In recent decades, along with urbanization, various models have been used to urban growth prediction. In this regard, Urban models based on the automata technique have emerged under the paradigm of a self-organizing system, with cellular automata (CA) being the simplest but most popular in action What happens to each grid cell is defined by a transition rule or transition rules.If the transition rule requires that the state of a grid cell is only dependent on its state at a previous time step, such a model is called a Markov model, and is not considered a CA model. Cellular automata models have one additional feature: the transition rules operate on cells based on the local neighborhood of those cells. In this research, the spatial expansion of Maragheh city was simulated using Cellular automata- Markov chain hybrid model. Satellite images (Landsat) were used for land cover mapping, urban growth monitoring, and modeling land cover changes. Results represent high efficiency of Cellular automata- Markov chain in the urban spatial growth simulation. In the past three decades,development trend of Maragheh city has been more towards barren lands.According to the output of the model,this trend will continue over the next 17 years. So that, the city will be expended due to the transition of barren lands cells state to urban cells state,and 774 hectares from surrounding barren lands will be converted to urban lands. However, with continue of the previous trend, nearly 417 hectares of good agricultural lands will also change to urban lands.
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