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中国城市群分布及范围的定量评价(英文)
引用本文:张倩,胡云锋,刘纪远,刘越,任旺兵,李军.中国城市群分布及范围的定量评价(英文)[J].地理学报(英文版),2012,22(1):137-151.
作者姓名:张倩  胡云锋  刘纪远  刘越  任旺兵  李军
作者单位:Institute of Geographic Sciences and Natural Resources Research, CAS;Graduate University of Chinese Academy of Sciences;Department of Urban Planning and Environment, Royal Institute of Technology-KTH;Academy of Macroeconomic Research, National Development and Reform Commission
基金项目:National Basic Research Program of China,No.2010CB950904,National Key Technology Research & Development Program:No.2008BAH31B04,Swedish Science Foundation
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.

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

A quantitative assessment of the distribution and extent of urban clusters in China
Qian Zhang,Yunfeng Hu,Jiyuan Liu,Yue Liu,Wangbing Ren,Jun Li.A quantitative assessment of the distribution and extent of urban clusters in China[J].Journal of Geographical Sciences,2012,22(1):137-151.
Authors:Qian Zhang  Yunfeng Hu  Jiyuan Liu  Yue Liu  Wangbing Ren  Jun Li
Institution: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, Stockholm 10044, Sweden; 4. Academy of Macroeconomic Research, National Development and Reform Commission, Beijing 100038, China
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 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 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 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.
Keywords:urban clusters  Geographic Information System (GIS)  computerized identification  spatial distribution  China
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