| Urban growth is a dynamic spatial process that is commonly modelled with complex systems theory and the cellular automata (CA) approach. The majority of CA models use the raster data structure to represent space and are often implemented as custom-built or geographic information systems (GIS)-coupled software. However, the regular grid presents a number of problems when used with high-resolution land use data composed of irregularly sized and shaped cadastral parcels. The objective of this study is to develop a CA model of urban growth using a high-resolution irregular spatial data structure with high temporal resolution. A GIS-embedded modelling tool named iCity was developed within a common desktop GIS to enable urban planners and stakeholders to visualize how different subdivision designs, population growth rates, and buyer preferences will influence urban development. This study contributes to the advancement of CA models and spatial decision support systems for use in urban planning. |
