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Land-use pattern scenario analysis using planner agents

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  • Ying Long
  • Yongping Zhang

Abstract

Land-use pattern is one of the key issues in the compilation of urban master plans. In China, government, planners, and residents, all with various requirements and preferences, are the main agents participating in this process. Among them, planners play a role in negotiating with related agents and then establishing land-use patterns. In this paper we propose a planner agent framework to support land-use pattern scenario analysis (LUPSA), based on existing planning support system (PSS) research. Planner agents are divided into three types: nonspatial planner agent (NPA), spatial planner agent (SPA), and chief planner agent (CPA). The NPA is responsible for formulating special plans (such as transport, municipal public facilities, or nature reserve plans) that correspond to available data (such as road network, public facilities, and nature reserve patterns) from LUPSA. The SPA is responsible for establishing land-use patterns. The SPA considers constraints of local development conditions and communicates and coordinates with the NPAs to confirm formulated special plans that can support the implementation of the established land-use pattern. The CPA is responsible for negotiating with the government agent to ensure the reasonability of comprehensive constraints, establishing the final land-use pattern based on an evaluation of established scenarios by several SPAs, then determining it after a public participation process involving local residents. We initially tested this framework in a hypothetical city, then did an experiment in Beijing. Results show that the proposed planner agent framework is suitable for LUPSA.

Suggested Citation

  • Ying Long & Yongping Zhang, 2015. "Land-use pattern scenario analysis using planner agents," Environment and Planning B, , vol. 42(4), pages 615-637, July.
    • Handle: RePEc:sae:envirb:v:42:y:2015:i:4:p:615-637
    DOI: 10.1068/b130012p
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    References listed on IDEAS

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    3. Nina Schwarz & Daniel Kahlenberg & Dagmar Haase & Ralf Seppelt, 2012. "ABMland - a Tool for Agent-Based Model Development on Urban Land Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-8.
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    1. Seyed Morsal Ghavami & Mohammad Taleai, 2017. "Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process," Journal of Geographical Systems, Springer, vol. 19(2), pages 109-132, April.

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