DG-ABC

Author:

Silva Elisabete A.1,Wu Ning1

Affiliation:

1. University of Cambridge, UK

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.

Publisher

IGI Global

Reference68 articles.

1. From Intentions to Actions: A Theory of Planned Behavior

2. Al-Kheder, S., Wang J., & Shan, J. (2007). Cellular automata urban growth model calibration with genetic algorithms. Urban Remote Sensing Joint Event, (11-13), 1-5.

3. Self-organizing map and cellular automata combined technique for advanced mesh generation in urban and architectural design.;C. C.Álvaro;International Journal of Information Technologies and Knowledge,2008

4. Generating Future Land-Use and Transportation Plans for High-Growth Cities Using a Genetic Algorithm

5. Barredo, J. I., Kasanko, M., Demicheli, L., McCormick, N., & Lavalle, C. (2002). Modelling the future of cities using cellular automata: The MOLAND methodology. Paper presented at Spatial Information and Social Processes: European and Greek experience in G.I.S. European Seminar, Thessaloniki.

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