Abstract
The study investigates the modeling process for simulating the land use changes in a port city, Dalian, China. Using remote sensing data, an integrated approach coupling with logistic regression, Markov Chain, and cellular automata is designed. Aimed at port city, both natural and socio-economic determinants involved, especially port related factors are imported to strengthen pertinence and particularity in research. Three different spatial growth scenarios are simulated based upon various land-use expectations. The results verify the reliability of the proposed approach and illustrate different simulation outcomes. This research can provide scenario-based decision-making support to port city to achieve land-use sustainable development.
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