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A key component of cellular automata (CA) models is the transition rules that determine the transformation of cells at each iteration. However, most previous studies use a single set of transition rules across the entire study region, and therefore do not fully account for spatial heterogeneity. In this research, a vector CA model has been implemented that calibrates transition rules by taking the entire study region and partitioned sub‐regions into consideration. The changes in residential areas were modelled for the city of Ipswich, Queensland, Australia, from 1999 to 2016. The results confirm that the spatially partitioned rules can generate more accurate and stable results compared to calibrated rules using the whole study area, with an increase of mean producer's spatial accuracy of 72.07 and 75.59% in two sub‐regions (2‐2 and 2‐3). The implementation of CA models with partitioned transition rules enables a better understanding of spatial heterogeneity in land use change. [ABSTRACT FROM AUTHOR]

Abstract: We describe an approach to modelling the spatio-temporal spread of foot and mouth disease through feral animal and unfenced livestock populations. We used a susceptible-infected-recovered model, implemented in a cellular automata framework, to assess the spread of FMD across two regions of Queensland, Australia. Following a sensitivity analysis on the infectious states, scenario analyses were conducted using feral pigs only as the susceptible population, and then with the addition of livestock, and initiated in the wet season and in the dry season. The results indicate that, depending on the season the outbreak is initiated, and without the implementation of control measures, an outbreak of Foot and Mouth Disease around Winton could continue unchecked, while an outbreak around Cape York may die out naturally. The approach explicitly incorporates the spatial relationships between the populations through which the disease spreads and provides a framework by which the spread of disease outbreaks can be explored through varying the model parameters. It highlights the emergence and importance of spatio-temporal patterns, something that previous modelling of FMD in feral animal and unfenced livestock populations has lacked. [Copyright &y& Elsevier]