A quantitative assessment of the distribution and extent of urban clusters in China  

作　　者：ZHANG Qian HU Yunfeng LIU Jiyuan LIU Yue REN Wangbing LI Jun 

机构地区：[1]Institute of Geographic Sciences and Natural Resources Research, CAS [2]Graduate University of Chinese Academy of Sciences [3]Department of Urban Planning and Environment, Royal Institute of Technology-KTH [4]Academy of Macroeconomic Research, National Development and Reform Commission

出　　处：《Journal of Geographical Sciences》2012年第1期137-151,共15页地理学报（英文版）

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

摘　　要：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 Chinese 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 a computerized identification method supported by geographic information techniques to provide a better understanding of the distribution of Chinese 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 accord-ing 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 Plain, 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 Chinese 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.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 Chinese 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 a computerized identification method supported by geographic information techniques to provide a better understanding of the distribution of Chinese 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 accord-ing 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 Plain, 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 Chinese 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.

关 键 词：urban clusters Geographic Information System （GIS） computerized identification spatial distribu-tion China 

分 类 号：P208[天文地球—地图制图学与地理信息工程] TU984[天文地球—测绘科学与技术]