We present in this paper the development and application of a cellular automata model that uses irregular cells for simulating land-use change instead of the common regular cells based on the pixels of remote sensing images. The use of irregular cells combines urban form with reliable demographic, socioeconomic, and building data that are usually available for irregular census blocks. The calibration of the model is made through a procedure based on a particle swarm algorithm that optimises a measure of agreement derived from the kappa index for contingency matrices. The model was applied for simulating urban change in a small municipality in Portugal that registered high growth rates during the 1990s. Simulation results indicate the model's ability to capture land-use change in small urban areas.
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