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An agent-integrated irregular automata model of urban land-use dynamics

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Urban growth models are useful tools to understand the patterns and processes of urbanization. In recent years, the bottom-up approach of geo-computation, such as cellular automata and agent-based modeling, is commonly used to simulate urban land-use dynamics. This study has developed an integrated model of urban growth called agent-integrated irregular automata (AIIA) by using vector geographic information system environment (i.e. both the data model and operations). The model was tested for the city of San Marcos, Texas to simulate two scenarios of urban growth. Specifically, the study aimed to answer whether incorporating commercial, industrial and institutional agents in the model and using social theories (e.g. utility functions) improves the conventional urban growth modeling. By validating against empirical land-use data, the results suggest that a holistic framework such as AIIA performs better than the existing irregular-automata-based urban growth modeling.
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Keywords: agent-based modeling; cellular automata; geographic information system (GIS); urban growth; vector data model

Document Type: Research Article

Affiliations: Department of Geography, Texas Center for Geographic Information Science, Texas State University—San Marcos, San Marcos, TX, USA

Publication date: November 2, 2014

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