A cellular automata model of land cover change to integrate urban growth with open space conservation

▶ This research develops a cellular automata model of urban growth with two scenarios: a baseline scenario that represents a continuation of current trends and an open space conservation scenario that builds upon the principles of smart growth and green infrastructure concepts. ▶ The modeling approach applies cellular automata, Markov probabilities and multi-criteria evaluation to simulate five land cover classes simultaneously. ▶ The transition rules for the CA_MARKOV module are set in the form of suitability maps based on MCE allowing for consideration of various factors that are commonly used in land use planning and decision. ▶ The approach construes a basis for meaningful examination of the landscape dynamics under different scenarios, thus providing a useful planning and decision-making tool.