Remote Sensing and GIS Applications in Environmental Sciences
Modeling Urban Physical Expansion with Cellular Automaton Method (Case Study: Tabriz City)
Document Type : Original Article
Authors
1 GIS
2 Professor, Department of Remote Sensing and Geographic Information Systems, University of Tabriz, Tabriz, Iran
Abstract
Urban expansion is one of the complex and challenging issues in urban planning. Cellular automata, as a powerful simulation method, is used to model and predict urban physical expansion. The aim of the present study is to use the cellular automata method to model and analyze the physical growth of Tabriz city. In this regard, the study aims to investigate the impact of various factors such as urban development and changes in urban structure density using the Markov chain model on the physical growth of Tabriz city. To achieve this goal, first, satellite images from 2017, 2019, 2021, and 2023 were analyzed and classified using the maximum likelihood classification method. After this stage, land use maps of Tabriz city were extracted. The results showed a significant expansion of residential areas and at the same time a significant decrease in wasteland and agricultural lands during this six-year period. The urban development trend forecast in 2033 has been carried out using the Markov chain model with a kappa index of 81.14. The results obtained from the analyses carried out using the models show that the city of Tabriz is progressing and expanding in a centralized and nuclear manner in different stages of its development and expansion. This progress is clearly visible in all directions and dimensions, especially from the east of the city. Therefore, emphasizing the use of more advanced models such as the Markov chain can significantly help improve the accuracy of predictions and analyses related to land use changes. The results of this research can be used in urban planning and urban resource management decisions.
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