A Spatio-Temporal Urban Growth Modelling. Case Study: Tehran Metropolis

Different models have been attempted for modelling urban expansion. Models are tools for detecting changes and considering the relationship between land use and land use change factors. In this paper, the authors used the Logistic Regression method for modelling the urban expansion pattern in Tehran Metropolis during 1988-2010, and employing landsat imageries acquired in 1988, 1999 and 2010. The effective parameters employed in this study include distance to principle roads, distance to developed region, distance to faults, distance to green space, elevation, slope and the number of urban pixels in a 3*3 neighbourhood. Percent Correct Match, Kappa statistics and Figure of Merit have been used for evaluating the accuracy of the model. The authors concluded that the distance to the residential area greatly influences the urban development of Tehran as compared to other factors. On the other hand, the number of urban pixels in a 3*3 neighbourhood had the lowest impact on urban development for this megacity in this period of time.