Neighborhood Interaction in Urban Land-Use Changes Using Cellular Automata-Based Geo-Simulation

  • Yaolong Zhao
  • Bingliang Cui
  • Yuji Murayama


Cities can be understood as complex systems with intrinsic characteristics of emergence, self-organization, self-similarity, and non-linear behavior of land-use dynamics (Barredo et al. 2003; Batty 2005). Cities incessantly undergo a dynamic and complex process of urban land-use changes. This complex process has direct impacts on the urban environment (Jusuf et al. 2007; Pauleit et al. 2005), and may even profoundly disrupt the structure and function of ecosystems on a global scale (Lambin et al. 2001; Turner et al. 1990). Therefore, the complex spatial processes of urban land-use changes must be thoroughly understood in order to provide municipal and urban planners with a basis for assessing the ecological impacts of urban land-use changes, and to support spatial decision-making. For this purpose, various spatial dynamic models of urban land-use change, in particular cellular automata (CA), multi-agent systems (MAS), and geographical information system (GIS)-based urban geo-simulation models, have been constructed and successfully applied to many cities (Barredo and Demicheli 2003; Batty et al. 1999; Torrens 2006; White and Engelen 2000; Yeh and Li 2002). In such geo-simulation models, neighborhood interaction is an important component (Batty 1991; Wu 1998; Zhao and Murayama 2007). Neighborhood interaction means local spatial interactions between neighborhood land-use categories such as facilities, residential areas, and industries in urban areas. Here, “neighborhood” means “close to”, i.e., neighborhood land-use parcels may or may not be contiguous (touching). Such interaction has a great impact on the spatial processes of urban land-use changes (Batty 2005; Couclelis 1989). This type of factor is known as the neighborhood effect of urban land-use changes. The neighborhood effect plus exogenous factors (like spatial interactions between cities) and endogenous factors (like transportation networks in urban areas) determine the spatial process of urban land-use change (White and Engelen 2000). Furthermore, it is often cited as the main factor which decides urban land-use change patterns, since other factors are comparatively stable in the spatial process of urban land-use change during a set period.


Metropolitan Area Cellular Automaton Neighborhood Effect Public Land Residential Land 
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Copyright information

© Springer Japan 2012

Authors and Affiliations

  1. 1.School of GeographySouth China Normal UniversityGuangzhouPeople’s Republic of China
  2. 2.Division of Spatial Information Science, Graduate School of Life and Environmental SciencesUniversity of TsukubaTsukubaJapan

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