The combination of the Markov chain with Cellular Automata to provide a method for the spatial modeling of urban growth

today, in the countries of the world, the population in urban areas is increasing rapidly. In order to avoid adverse socio-economic and environmental impacts, rapid urban growth should be managed and planned in an appropriate manner. In order to plan and manage this phenomenon, spatial data related to the pattern and the growth rate is required. To achieve this, you can use various tools such as remote sensing and spatial information. In the present article, ASTER satellite images, cover changes and land use related to a part of Tehran city have been investigated. The review period is from 2001 to 2017. Then, in the next section, the CA-Markov integration model will be used to predict future urban growth.