Presenter/Author Information

G. L. Ciampaglia
B. Tirozzi

Keywords

urban growth impact, multi-agent system, cellular automaton, rome, model integration

Start Date

1-7-2008 12:00 AM

Description

In this paper we present a model of urban growth and its preliminary application to acase study of the phenomena of residential development in the setting of the eastern periphery ofRome, Italy’s capital city. The modeling approach we use synthesises the two typical paradigmswidespread in the community of quantitative urban planning: the traditional one, based on cellularautomata (CA), and the (relatively) new one, which is agent-based. In particular, our multi-agentsystem (MAS) is in-between a reactive MAS, with agents carrying out a two-staged decision processin a complex environment, and a model of statistical physics, since we use populations ofagents in order to reduce the number of degrees of freedom of the system. While we explicitlymodel the consumption of agricultural and undeveloped land due to urban growth, our modelmay be easily integrated as a socio-economic part into a wider decision support system for environmentalplanning, e.g. our simulations can produce indicators of environmental impact of thegrowth of the city: electricity consumption, waste production, etc.

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Jul 1st, 12:00 AM

Go East: A Residential Land Use Model for the Periphery of Rome

In this paper we present a model of urban growth and its preliminary application to acase study of the phenomena of residential development in the setting of the eastern periphery ofRome, Italy’s capital city. The modeling approach we use synthesises the two typical paradigmswidespread in the community of quantitative urban planning: the traditional one, based on cellularautomata (CA), and the (relatively) new one, which is agent-based. In particular, our multi-agentsystem (MAS) is in-between a reactive MAS, with agents carrying out a two-staged decision processin a complex environment, and a model of statistical physics, since we use populations ofagents in order to reduce the number of degrees of freedom of the system. While we explicitlymodel the consumption of agricultural and undeveloped land due to urban growth, our modelmay be easily integrated as a socio-economic part into a wider decision support system for environmentalplanning, e.g. our simulations can produce indicators of environmental impact of thegrowth of the city: electricity consumption, waste production, etc.