This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model
consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to
improve the performance of the standard logistic regression model. Environmental and socio-economic
variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal
states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated
by means of relative operating characteristic values for different sets of variables. The approach was
calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes
represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve
the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming
years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach.
The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the
western border of the metropolis during the next decades.