Understanding Spatial and Temporal Processes of Urban Growth: Cellular Automata Modelling
Environment and Planning, B: Planning and Design
Understanding the dynamic process of urban growth is a prerequisite to the prediction of land cover change and the support of urban development planning and sustainable growth management. The spatial and temporal complexity inherent in urban growth requires the occurrence of a new simulation approach, which should be process-oriented and have a stronger capacity of interpretation. This paper presents an innovative methodology to understand spatial processes and their temporal dynamics on two
... errelated scales (municipality and project), by a multi-stage framework and dynamic weighting concept. The multi-stage framework aims to model local spatial processes and global temporal dynamics by incorporating explicit decisionmaking processes. It is divided into four stages: project planning, site selection, local growth and temporal control. These four steps represent the interactions between top-down and bottom-up decision making involved in land development of large-scale projects. Project-based cellular automata modelling is developed for interpreting the spatial and temporal logic between various projects forming the whole urban growth. Dynamic weighting attempts to model local temporal dynamics at the project level as an extension of the local growth stage. As a non-linear function of temporal land development, dynamic weighting is able to link spatial processes and temporal patterns. The methodology is tested with reference to the urban growth of a fast growing city, Wuhan in the Peoples' Republic of China from 1993 to 2000. The findings from this research suggest that this methodology can facilitate the interpretation and visualisation of the dynamic process of urban growth more temporally and transparently, globally and locally.