Abstract
The complexity of LUCC (Land Use / Cover Change, LUCC) determines that it is important to conduct the study of LUCC using complex system theories, in particular by the establishment of a mathematical model for complex systems. In this paper, the LUCC model was built based on GIS technology, CA (cellular automata) and Agent technology. Firstly, Landsat TM data of 2000 and 2010 are used to obtain the land use map. Based on the maps, land use change patterns can be determined as references for the LUCC model. GIS is used to obtain the spatial variables. ANN (Artificial neural network) instead of complex transformation rules is used to obtain the parameters. This method significantly simplifies the structure of the CA model and the definition of transformation rules. Cellular interactions are entirely based on spatial proximity, which cannot move. However, ABM (Agent Based Modeling) has great advantages for complex “human-land relationship analog” and therefore, it is applied in this study. Land use change of each grid cell is determined and marked by CA model, and Agent makes the change of land use type according to the marks. The model is realized by Repast and Matlab. The LUCC model uses the land use type of 2002 initially to simulate land use type of 2010 and evaluates the accuracy of the simulation results by the Lee-Sallee index. After repeated debug processes and parameter adjustments, the optimal dynamic LUCC evolution model is determined. Based on initial land use of 2010, future land use types in 2020 of the Erhai region are predicted.
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