Abstract Landscape pattern indexes are quantitative descriptions of the spatial composition and configuration of land use, which can influence a variety of ecological phenomena. In this paper, we propose a land use change simulation model based on landscape pattern indexes, Markov chain and cellular automata. In the model, Markov Chain is applied to predict the amount of land use change; transition potential maps generated from natural and socioeconomic indexes are used to control the spatial distribution of land use; landscape pattern indexes in the start year are used to differentiate the transition probabilities of land use classes within different sub-regions of the study area. First, the principles and implementation of the model were described. Then the model was successfully applied to the simulation of land use change in Changping, a district of Beijing. Based on land use maps in years 1988 and 1998, the land use map in year 2008 was simulated. By analyzing the simulation result, the effectiveness of the model for land use change simulation was demonstrated. By comparing results simulated by this model and the results simulated by Markov-CA model with the actual land use map, the advantage of this model in spatial accuracy was shown.