Abstract
Cellular Automaton (CA) consists of a regular grid cells of which states change according to simple repetitive rules regulated by their contiguous and adjacent cells, which often expresses an unexpected complexity. Thus, CA is one of the major techniques to imitate and/or assess complex behaviors of natural systems. CA can be applied to physical and biological phenomena, such as turbulence in fluid, patterns of biological growth, and wildfire, and also some human-induced phenomena such as urban growth that is the main target of this review. In 1970s, cellular approach was initially adopted in geography, showing the clue to the urban growth application. To overcome the limitation or constraints the conventional standard cell-space models inherently include, alternative formulations were theoretically proposed in 1980s. And the pioneering work applied to realistic cities was conducted in 1990s. Subsequently, numerous models have been presented by relaxing original rules to express reality and by introducing some additional techniques such as geographical information system and system dynamics, thus far. This paper reviews 87 published cellular automata studies on urban growth simulations, urban land use change assessments, urban planning and related information from 18 countries, and examines the characteristics of each relaxation method. In addition, the scale problems are frequently discussed in the validation of the CA model is addressed.
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