地理学报 ›› 2013, Vol. 68 ›› Issue (10): 1389-1400.doi: 10.11821/dlxb201310008

• 时空格局与生态环境 • 上一篇    下一篇

基于多智能体的就业与居住空间演化多情景模拟——快速工业化区域研究

李少英1, 黎夏2, 刘小平2, 吴志峰1, 艾彬3, 陈明辉4, 黎海波4, 刘萌伟5   

  1. 1. 广州大学地理科学学院, 广州 510006;
    2. 中山大学地理科学与规划学院广东省城市化与地理环境空间模拟重点实验室, 广州 510275;
    3. 中山大学海洋学院, 广州 510275;
    4. 东莞市地理信息与规划编制研究中心, 东莞 523129;
    5. 广州市房地产测绘院, 广州 510030
  • 收稿日期:2012-08-14 修回日期:2013-01-16 出版日期:2013-10-20 发布日期:2013-11-20
  • 作者简介:李少英(1987-), 女, 广东汕头人, 博士研究生。E-mail: lsy_0130@163.com
  • 基金资助:
    国家重点基础研究发展项目(973 计划) (2011CB707103);国家自然科学基金项目(41171308);广州市科技和信息化局国际科技交流与合作专项项目(2012J5100044)

Multi-scenario simulations on the interactions of jobs-housing based on agent-based model

LI Shaoying1, LI Xia2, LIU Xiaoping2, WU Zhifeng1, AI Bin3, CHEN Minghui4, LI Haibo4, LIU Mengwei5   

  1. 1. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China;
    2. School of Geography and Planning, Sun Yat-sen University, Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China;
    3. School of marine sciences, Sun Yat-sen University, Guangzhou 510275, China;
    4. Research Center of Geographic Information System & Planning of Dongguan, Dongguan 523129, Guangdong, China;
    5. Real Estate Surveying and Mapping Institute, Guangzhou 510030, China
  • Received:2012-08-14 Revised:2013-01-16 Online:2013-10-20 Published:2013-11-20
  • Contact: 黎夏(1962-), 男, 广西梧州人, 教授, 中国地理学会会员(S110001500M)。E-mail: lixia@mail.sysu.edu.cn E-mail:lixia@mail.sysu.edu.cn
  • Supported by:
    National Basic Research Program of China (973 Program), No.2011CB707103; National Natural Science Foundation of China, No.41171308; Intenational Collaborative Program of Science and Technology of Guangzhou Municipal Bureau of Science and Information Technology, No.2012J5100044

摘要: 就业与居住空间关系是城市规划与管理研究的热点问题。已有研究主要基于传统宏观模型对就业—居住空间结构进行现状分析或对城市理论进行实证研究,在微观尺度的机制探讨与过程模拟方面较为缺乏。本文基于多智能体自下而上的建模思想,提出基于就业市场的人口居住区位选择模型(Labor Market Based Model of Residential Location-LMBMRL)。以典型的快速工业化地区—东莞市主城区为实验区,通过多情景模拟对就业与居住空间的互动关系进行机制探讨与过程分析。模拟结果充分反映了就业选择对人口居住区位决策的影响,定量评估了住房与交通对职住空间均衡性与职住分离的影响规律。当住房成本提高时,城市职住均衡性降低;当交通可达性提高时,城市空间结构可能出现较为显著的职住分离现象。最后通过多情景模拟揭示不同行业劳动人口群体的就业—居住空间特征与组织模式。研究结果有助于深刻理解城市就业—居住空间互动关系及其内部因果,能够为城市规划与管理提供决策参考。

关键词: 居住区位选择, 就业—居住空间关系, 多智能体, 就业市场

Abstract: Jobs and housing are two major elements in urban spatial structure. The relationship between jobs and housing affects urban planning and management, and has become one of the hot topics in urban study. Most of the current researches focus on the analyses of urban spatial structure and the empirical study of urban theory based on macro-models. These models, which are traditional "top-down" approaches, have limitations in reflecting the individual behaviors. In fact, the spatial relationship of jobs-housing is the outcome of population individual behaviors including jobs selecting and residential decisions. Hence, the spatial organization of jobs-housing is difficult to simulate with those macro-models. Studies indicated that agent-based models which are "bottom-up" approaches, can offer a way to simulate the complex problems that involve individual behaviors. This paper proposes an agent-based model (Labor Market Based Model of Residential Location-LMBMRL) to simulate the interactions between jobs and housing. In this model, labor economics theory is incorporated to define the influence of labor market on job searching behaviors of population individuals. An agent-based approach is used to simulate the job searching behaviors and the residential location decisions of individuals. The proposed model is applied to the center region of Dongguan, an emerging and renowned manufacturing metropolis in the Pearl River Delta region, China. The simulated results reflect the effect of labor market on residential decisions. Quantitative analysis is carried out to assess the influence of housing cost and commuting cost on jobs-housing balance. It is found that as the housing cost rises, the relationship of jobs-housing will become less balanced. When the commuting cost is reduced, the relationship of jobs-housing will be much more imbalanced. Moreover, it has revealed the jobs-housing characteristics of population in different economic sectors through multi-scenario simulations. The study results are significant for understandings of jobs-housing organization, which can provide important guidance for urban planning and management.

Key words: Jobs-housing relationship, residential location decisions, labor market, agent-based model, job searching behaviors