CA-Based Urban Land Use Prediction Model: A Case Study on Orange County, Florida, U.S.

For a long time, interactions between land use and transportation have been one of the research hotspots in urban planning, which however, has not been investigated in much detail until recently. This paper started from spatial changes of regional land use, with an objective of understanding the relationship between trip generation and urban land use. Cellular automata and geographical information system techniques were used to store and update the spatial data dynamically. In addition, MATLAB software was adopted to conduct the logistic regression using land use/land cover data from Orange Country, Florida, U.S. (1990 and 2000). With fully utilizing the advantages of cellular automaton models, simulation results indicate the enhenced reliability of the model, which consequently assists to understand evolution of urban land uses.