Acta Geographica Sinica ›› 2011, Vol. 66 ›› Issue (8): 1033-1044.doi: 10.11821/xb201108003

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A Multi-agent Model for Urban Form, Transportation Energy Consumption and Environmental Impact Integrated Simulation

LONG Ying1,2, MAO Qizhi1, YANG Dongfeng3, WANG Jingwen4   

  1. 1. School of Architecture, Tsinghua University, Beijing 100084, China;
    2. Beijing Institute of City Planning, Beijing 100045, China;
    3. Department of Architecture, Dalian University of Technology, Dalian 116024, Liaoning, China;
    4. School of Landscape, Beijing Forestry University, Beijing 100083, China
  • Received:2010-04-27 Revised:2010-07-28 Online:2011-08-20 Published:2011-08-20
  • Supported by:

    National Natural Science Foundation of China, No.51078213

Abstract: Cities are consuming more energy with increasing urbanization process. The urban transportation energy is the primary part of urban energy consumption. Extensive researches found that it has strong relationship with the urban form, which fall into intra-cities level. However, little attention was paid to the relationship between urban form, transportation energy consumption, and environmental impact in the inner-city level. This paper aims to investigate the impact of urban form, namely land use pattern, development density distribution, on the residential commuting energy consumption (RCEC). We developed a multi-agent model for the urban form, transportation energy consumption and environment interaction simulation (FEE-MAS). Numerous urban forms with distinguished urban land use pattern and development density distribution are generated using the Monte Carlo approach in the hypothetical space. On one hand, the RCEC for each urban form is calculated using the proposed FEE-MAS. On the other hand, we select 14 indicators (e.g. Shape Index, Shannon's Diversity Index, Euclidean Nearest Neighbor Distance) to evaluate each generated urban form using FRAGSTATS, which is loosely coupled with the FEE-MAS model. Then, the quantitative relationship between the urban form and RCEC is identified based on 14 indicators and RCEC of each urban form. Several conclusions are drawn from simulations conducted in the hypothetical space. (1) RCEC may vary three times for the same space with various spatial layouts and density distribution. (2) Among selected 14 indicators for evaluating the urban form, the patch number of job parcels is the most significant variable influencing the RCEC. (3) The RCECs of all urban forms generated obey a normal distribution. (4) The shape of urban form also exerts influences on the RCEC. In addition, we evaluated several typical urban forms, e.g. compact/sprawl, single center/ multi-centers, traffic oriented development, green belt, in terms of the RCEC indicator using our proposed model to quantify those popular planning theories. The FEE-MAS model can also be applied for evaluating urban spatial alternatives in terms of energy consumption and environmental impact.

Key words: land use, development density, transportation energy consumption, environmental impact, multi-agent, Monte Carlo