Assessing temporal-spatial land use simulation effects with CLUE-S and Markov-CA models in Beijing.

In order to solve the problem of extensive land use in rural residential areas and promote the construction of a new socialist countryside and farmland protection, it is important to graspe the temporal and spatial evolution of rural settlements. In this study, with Beijing as an example, the efficiencies of CLUE-S and Markov-CA models in simulating spatial temporal evolution of rural residential areas are analyzed. With 14 driving factors chosen, the land uses in Beijing in 2000 and 2005 are simulated and predicted using the two models. Grid size of 220 m × 220 m is used. The accuracies and Kappa coefficients of the simulation and prediction results are analyzed and the following conclusions are made. The core part of CLUE-S model is logistic regression, which grants it obvious advantage in capturing the trends of land use changes with more discrete distributions. Meanwhile, Markov-CA model takes neighborhood into consideration, making it relatively more advantageous in simulating and predicting changes of land uses with the character of nearest-neighbor diffusion. However, among various land uses, only urban land use has this character, the correct prediction rates of the CLUE-S model in 2000 and 2005 were 60.99% and 81.35%, respectively, while the accuracy of the Markov-CA model prediction was 51.33% and 73.68%, and it is the main reason that CLUE-S model returns better simulation and prediction results of rural residential areas for both 2000 and 2005 than Markov-CA model.