| It is an important and effective methodto study land use/cover change (LUCC)bysimulatingmodels.Building LUCCmodel based on cellular automata (CA) is theimportant issues of LUCC simulation. A good model must integrate data andalgorithm well.However, the current CA-based LUCC modelsignore the relationshipbetween land use data with thestructure of CA model. Therefore, this paper proposedto improve CA model according to the land use data and influent factors of LUCC,and then established the theory and application LUCCmodel based on CA.First of all, theresearches of LUCC driving factorswere summarized, accordingto the structure characteristics of CA model, the driving factors were divided into twocategories: internal factors andexternal factors. Then based on this research, the CAmodel was improved.At thelayer of cellular space, the macro control factor was takenin, and for each cell, the internal factors were added. And then, thedynamicmechanism and characteristicswere analyzed.Then, the basic structures of extended CA were described by concepts of land tobuild LUCC-CA theory model.Combined with Markov Chain, ant colonyoptimization algorithm (ACO) and Agent,a LUCC-CA application model wasestabilished. The model adoptd the Markov Chain forecasting quantity of land usechanges, and took it as the macro control factorof extendedCA; usedACO miningspatial transformation rules;usesAgent and extended CA simulating land use dynamicchange process.Finally, case study was carried out in Changping, a district of Beijing.A land usemap of the experimental areawas simulated for2008using the modelbased on landuse maps from1988and1998. By analyzing the simulation results, we showed thatthe model is useful for land use change simulation.Compared with the other models,the model is more appropriate for predicting both the quantity and spatial distributionof land use changein the study area. Therefore the modelproposed in this paper iscapable of simulating land use change. |
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