Calibration of an urban cellular automaton model by using statistical techniques and a genetic algorithm. Application to a small urban settlement of NW Spain

摘要: Cellular automata CA stand out among the most commonly used urban models for simulation and analysis of growth because their ability to reproduce complex dynamics, similar those found in real cities, from simple rules. However, still have overcome some shortcomings related flexibility difficult calibration. This study combines various techniques calibrate an that is based on one widely models. First, number calibration parameters reduced by using statistical techniques, and, second, procedure automated through a genetic algorithm. The resulting model has been assessed simulating Ribadeo, small village NW Spain, characterized low, slow growth, which makes identification dynamics consequently more difficult. Simulation results shown that, automating procedure, can be easily applied adapted areas with different characteristics dynamics. In addition, simulations obtained proposed show better values cell-to-cell correspondence between simulated maps, spatial metrics are closer ones.