地理学报 ›› 2011, Vol. 66 ›› Issue (6): 761-770.doi: 10.11821/xb201106005

• 城市研究 • 上一篇    下一篇

基于交通、人口和经济的中国城市群识别

张倩1,2,3, 胡云锋1, 刘纪远1, 刘越1,2, 任旺兵4, 李军4   

  1. 1. 中国科学院地理科学与资源研究所, 北京 100101;
    2. 中国科学院研究生院, 北京 100049;
    3. 瑞典皇家理工学院城市规划与环境系, 斯德哥尔摩 10044;
    4. 国家发改委宏观经济研究院, 北京 100038
  • 收稿日期:2011-03-10 修回日期:2011-05-16 出版日期:2011-06-20 发布日期:2011-08-06
  • 通讯作者: 胡云锋(1974-), 男, 副研究员, 中国地理学会会员(S110008243M), 主要从事区域资源环境评价研究。E-mail: huyf@lreis.ac.cn E-mail:huyf@lreis.ac.cn
  • 作者简介:张倩(1981-), 女, 博士生, 主要从事城市土地利用变化探测与模拟研究。E-mail: zhangq@lreis.ac.cn
  • 基金资助:

    科技部973 计划(2010CB950904); 科技部科技支撑项目(2008BAH31B04); 瑞典科学研究基金项目(348-2006-6638)

Identification of Urban Clusters in China Based on Assessment of Transportation Accessibility and Socio-Economic Indicators

ZHANG Qian1,2,3, HU Yunfeng1, LIU Jiyuan1, LIU Yue1,2, RENWangbing4, LI Jun4   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Department of Urban Planning and Environment, Royal Institute of Technology-KTH, 10044 Stockholm, Sweden;
    4. Academy of Macroeconomic Research, National Development and Reform Commission, Beijing 100038, China
  • Received:2011-03-10 Revised:2011-05-16 Online:2011-06-20 Published:2011-08-06
  • Supported by:

    National Basic Rearch Program of China (973 Program), No.2010CB950904; National Key Technology Research & Devlopment Program, No.2008BAH31B04; Swedish Science Foundation, No.348-2006-6638

摘要: 城市群是一个国家工业化和城镇化进程发展到较高阶段的自然产物,是国家参与全球竞争与国际分工的新型地域单元。当前,研究人员对城市群的识别尚没有一个统一、快速的技术体系,国内外研究人员对于中国城市群的准确识别和区域界定也不统一。在综合前人研究的基础上,作者首先厘清了城市群的基本概念;继而提出了一套以地球信息技术为支撑的,综合了交通、人口和经济属性判断的城市群快速识别和区划的技术流程,即以空间通达性的定量测算为基础,初步识别出空间上集结的城市集群;然后以城市集群的经济和社会属性为判据开展进一步的遴选,得到城市群空间分布及其区划界线。作者使用基础地理数据、DEM数据、空间化的经济社会格网数据,应用ArcInfo Macro Language 编程技术对中国的城市群进行了识别,研究明确了2000 年中国9 大城市群的空间位置及其覆盖区域。与国内外既有认识的对比表明,本研究技术路线简单、清晰,所得的中国城市群区划成果准确,具有可参比性。

关键词: 空间分布, 中国, 城市群, 地理信息技术(GIS), 计算机识别

Abstract: Urban clusters are the expected products of high levels of industry and urbanization in a country, as well as being the basic units of participation in global competition. With respect to China, urban clusters are regarded as the dominant formation for boosting the China's urbanization process. However, to date, there is no coincident, efficient, and credible methodological system and set of techniques to identify Chinese urban clusters. This research investigates the potential of an computerized identification method supported by geographic information techniques to provide a better understanding of the distribution of China's urban clusters. The identification method is executed based on a geographic information database, a digital elevation model, and socio-economic data with the aid of ArcInfo Macro Language programming. In the method, preliminary boundaries are identified according to transportation accessibility, and final identifications are achieved from limiting city numbers, population, and GDP in a region with the aid of the rasterized socio-economic dataset. The results show that the method identifies nine Chinese urban clusters, i.e., Pearl River Delta, Lower Yangtze River Valley, Beijing-Tianjin-Hebei Region, Northeast China, Middle Yangtze River Valley, Central China Plains, Western Taiwan Strait, Guanzhong and Chengdu-Chongqing urban clusters. This research represents the first study involving the computerized identification of China's urban clusters. Moreover, compared to other related studies, the study's approach, which combines transportation accessibility and socio-economic characteristics, is shown to be a distinct, effective and reliable way of identifying urban clusters.

Key words: urban clusters, Geographic Information System (GIS), computerized identification, spatial distribution, China