China is in a stage of rapid development of urbanization, socio-economic development leads to the rapid expansion of urban land, thus sharpens the contradiction between people and land resources. The scarcity of land resources per capita determines that we must allocate urban land scientifically and rationally, control urban scale, and achieve sustainable development of cities. As urban land expansion has open, nonlinear, uncertain and dynamic characteristics, the traditional methods can not accurately describe the actual number of urban land use and spatial changes. Cellular automata became a research focus in the area of expansion of urban land, because of its "bottom-up" dynamic evolution capabilities. The combination of Cellular Automata and GIS technologies can effectively simulate the process of spatial and temporal changes of urban land, make up the deficiency of traditional methods, and provide reference for urban planning.In this paper, the first part describes cellular automata and Markov model and its basic theory of urban land expansion. Then we use Land use dynamics, terrain distribution, transition matrix of land usage state analyze the characteristics of expansion of urban land usage and analyze the impact of the distribution of urban land caused by characteristics of terrain and transport factors. Based on the conclusion of the analysis above, we use several restriction to modify the cellular transformation rules generated by Markov model, improve cellular automata simulation accuracy. We use Wuhan City as the study area, use Erdas, Arcgis and Idrisi Andes process data, analyze and evaluate various factors, get urban land expansion characteristics, amend the cellular conversion based on those characteristics. Based on the real data, we test the rationality of cellular automaton mode, and amend the time calibration model parameters. We use Markov model to predict the number of urban land usage change and simulate the future expansion of the spatial distribution of urban land usage by using cellular automaton model.The results show that improving rules of transform, cellular automata model can accurately predict the number of changes and the spatial distribution in urban land expansion, it can be better to guide urban planning. |