Configuring the neighbourhood effect in irregular cellular automata based models

Abstract

Abstract:Cellular automata (CA) models have been widely employed to simulate urban growth and land use change. In order to represent urban space more realistically, new approaches to CA models have explored the use of vector data instead of traditional regular grids. However, the use of irregular CA-based models brings new challenges as well as opportunities. The most strongly affected factor when using an irregular space is neighbourhood. Although neighbourhood definition in an irregular environment has been reported in the literature, the question of how to model the neighbourhood effect remains largely unexplored.In order to shed light on this question, this paper proposed the use of spatial metrics to characterise and measure the neighbourhood effect in irregular CA-based models. These metrics, originally developed for raster environments, namely the enrichment factor and the neighbourhood index, were adapted and applied in the irregular space employed by the model. Using the results of these metrics, distance-decay functions were calculated to reproduce the push-and-pull effect between the simulated land uses. The outcomes of a total of 55 simulations (five sets of different distance functions and eleven different neighbourhood definition distances) were compared with observed changes in the study area during the calibration period. Our results demonstrate that the proposed methodology improves the outcomes of the urban growth simulation model tested and could be applied to other irregular CA-based models.

A Cellular Automata Model for Integrated Simulation of Land Use and Transport Interactions

“…These theoretical foundations boosted numerous variations and improvements to geographic CA models that are now widely used for simulating increasingly more complex problems [17][18][19][20][21][22]. The vast majority of these applications use regular cells derived from remotely sensed imagery, and even today, there is only a minority of studies that have considered irregular cellular fabrics [23,24,[25][26][27][28][29][30][31][32]33]. This is mainly due to the practicalities of operating raster images against the complexities of dealing with complex topologies in vector models.…”

Land use change simulation and analysis using a vector cellular automata (CA) model: A case study of Ipswich City, Queensland, Australia

“…A 5 × 5 Moore neighbourhood has been applied for the detection of neighbour cells in raster CA. Similarly, a buffer zone-based method has been adopted to define neighbourhood configuration of vector CA on the basis of research (Barreira-González and Barros, 2016; Moreno et al., 2009). Vector CA’s neighbourhood configuration has been identified as the intersection of the centre cell’s buffer zone and adjacent cells, which is proportional to the density of adjacent residential area.…”

Modelling the Impact of Transit Media on Information Spreading in an Urban Space Using Cellular Automata

“…With the help of these indicators, each cell has read access to any other cell in the cell field and the indicators can be changed from generation to generation, which causes the neighbourhood to be dynamic and differ from cell to cell. The neighbourhood problem becomes more complex in irregular spaces due to issues that are related to land use changes and the adaptation of urban spaces for other purposes [87][88][89][90][91]. Each cell selects one state from a finite set of states.…”