The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from the city's previous formal transformations. This was concluded after comparing the expected results with the data from the actual image. This study demonstrates the usefulness of cellular modelling and Markov's model in determining formal transformations in city structure. This paper contributes to identifying transformations and changes in urban structures because of the importance of this topic in the predictions of the future of cities to control and contain the negative trends of these transformations. The paper simulates spatial and temporal shifts by building a model that integrates mathematical and statistical analysis, and given the results of the Kappa index, the model's simulation capacity was excellent.
