Computational Land Use Simulation and Economic Value Forecasting in Waterfront Area Using Cellular Automata and Markov Chain Model

With the acceleration of urbanization, waterfront area has become an important economic development area because of its unique geographical location. In view of the unreasonable planning of waterfront development and the maximization of economic benefits. In this paper, the Cellular Automata and Markov (CA-Markov) model is used to evaluate and predict the economic development value of waterfront. By simulating the dynamic process of waterfront land use change, the economic development value of waterfront was evaluated and predicted. The transition probability matrix of land use type was calculated by Markov chain model, and the CA-Markov model was constructed by combining the spatial simulation ability of CA model. The CA-Markov model is used to predict the changes in Agricultural land, Land construction, Green land, Waters and Unused land, and is compared with other models. The results show that CA-Markov model has higher prediction accuracy.