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DG-ABC: An Integrated Multi-Agent and Cellular Automata Urban Growth Model

DG-ABC: An Integrated Multi-Agent and Cellular Automata Urban Growth Model
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Author(s): Elisabete A. Silva (University of Cambridge, UK)and Ning Wu (University of Cambridge, UK)
Copyright: 2017
Pages: 38
Source title: Natural Resources Management: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0803-8.ch025

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Abstract

Urban land change phenomena include spatial and a-spatial dynamics. As Holland (1995) suggests “a city's coherence is somehow imposed on a perpetual flux of people and structure.” However, it seems that most of the traditional economic and geographic studies have tried to separate the two entities associated with land use change (human decision-making and its spatial consequences), into two separate models (Sethuram et al., 2008). In order to explore the two fluxes (the spatial and a-spatial dynamics) this chapter presents an integrated model that incorporates ABM (Agent Base Model), CA (Cellular Automaton) and a Genetic Algorithm (GA) to include both spatial and a-spatial dynamics in an urban system in order to supply a new solution for urban studies. In the authors' model (DG-ABC stands for ‘Developing Genetic-Agent Based Cells'), the social economic behaviours of heterogeneous agents (resident, property developer and government) will be regulated by GA and the Theory of Planned Behaviour (TpB). With a pilot study conducted in order to test and calibrate the model this chapter analyzes how the macro level of the spatial pattern change (the emergence phenomena) is produced from the interactions of actors at the micro level (by the heterogeneous behaviours and interactions between agents, and the discrete spatial dynamics represented by CA). The simulation demonstrates that the integrated model can provide reasonable representations of the future evolution of cities.

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