A Review of Urban Growth Prediction Models

Human population continues to aggregate in urban centers, who inevitably increases the urban footprint with significant consequences for biodiversity, climate, and environmental resources. Urban growth prediction models have been extensively studied with the overarching goal to assist in sustainable management of urban centers. Despite the extensive research, these models are not frequently included in the decision making process. The survey found a strong recognition of the models’ potential in decision making, but limited agreement which these models actually reach enough potential in practice. This review aims are an overview of existing models, including advantages and limitations. Also, in general, it will be discussed to main reason for not applying these models in the decision making. Analysis of aggregated statistics indicates that cellular automata are the prevailing modeling technique, present in the majority of published works. Also, being unfamiliar decision-makers with models and thelack of popularity models to research are significant reasons for not using these models in the decision making.