Applicability and calibration of an irregular cellular automata model for land use change

Cellular automata (CA) models of spatial change have been developed and applied in the context of large regional or metropolitan areas and usually use regular cells, with spatial interactions and transition rules operating within fixed-size neighbourhoods. Model calibration has also been an area of intensive research with many models still using expert-based input to ensure visual calibration of modelled land use maps. In this paper, we present an innovative CA model where irregular cells and variable neighbourhoods are used to better represent space and spatial interaction. Calibration is based on an optimisation procedure that uses particle swarm (PS) to determine the optimal set of parameters of the CA model. Hypothetical test instances are used to assess the CA model and its calibration to small urban areas. Our conclusion was that the use of PS ensures calibration results for the CA model that compare very well with results obtained through other approaches reported in the literature. •A cellular automata (CA) model is calibrated by a particle swarm (PS) algorithm using 20 hypothetical test instances•CA model uses irregular cells and variable neighbourhoods, including accessibility as a driver of land use change•PS has a simple formulation that is suitable for searching the very complex space of solutions of the CA model•PS ensures calibration results for the CA model that compare very well with results obtained through other approaches