城市研究

中国城市空间关联网络结构的时空演变

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  • 1. 中国科学院地理科学与资源研究所, 北京100101;
    2. 中国科学院区域可持续发展分析与模拟重点实验室, 北京100101;
    3. 英国伦敦政治经济学院, 伦敦WC2A 2AE;
    4. 北京大学机器感知与智能教育部重点实验室, 北京100871;
    5. 国家开发银行信息科技局,北京1000379
武文杰, 男, 安徽淮北人, 博士研究生, 中国地理学会会员(S110007092A), 主要研究方向为城市和房地产。

收稿日期: 2010-07-09

  修回日期: 2010-12-08

  网络出版日期: 2011-04-20

基金资助

国家自然科学基金项目(40971077); 国家自然科学基金重点项目(40635026)

Spatio-temporal Evolution of the China's Inter-urban Organization Network Structure: Based on Aviation Data from 1983 to 2006

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  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing 100101, China;
    3. London School of Economics and Political Science, London WC2A 2AE, UK;
    4. Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing 100871, China;
    5. Bureau of Information and Technology, China Development Bank, Beijing, 100037

Received date: 2010-07-09

  Revised date: 2010-12-08

  Online published: 2011-04-20

Supported by

National Natural Science Foundation of China, No.40971077; Key National Natural Science Foundation of China, No.40635026

摘要

使用复杂网络的分析方法,研究了1983-2006 年中国城际航空网络的空间结构特征和格局变迁。主要结论有:① 城际航空网络作为典型的小世界网络,网络的稠密化趋势显著;②“轴—辐”空间组织模式已成为我国城际航空网络发展的基本模式。已形成以北京、上海、广州和深圳为轴心,以其他城市与轴心的空间联系为“辐网”的多轴心网络。同时,以乌鲁木齐和昆明为单轴心的两个相对独立的局部“轴—辐”网络日益完善;③ 城际航空网络演进效果具有明显的区域差异性,呈现出“鞍型”模式。东部比中西部地区航空的网络结构更加完善;④ 城际航空网络城市之间的空间关联表现出社群结构特征。枢纽性城市、地域邻近的城市以及城市职能相近的城市之间具有相似的空间关联特征;⑤ 随着城际航空网络的演进,35个大中城市在网络中的枢纽性地位表现出差异化趋势。此外,黄山、丽江等旅游城市、大连、青岛等沿海城市以及拉萨等西部城市航空联系的空间指向性特征明显。

本文引用格式

武文杰, 董正斌, 张文忠, 金凤君, 马修军, 谢昆青 . 中国城市空间关联网络结构的时空演变[J]. 地理学报, 2011 , 66(4) : 435 -445 . DOI: 10.11821/xb201104001

Abstract

Spatial-temporal distribution pattern of inter-urban organization network and its interaction process with aviation development has always been a hot issue in regional economy and transport geography. Civil aviation is the fastest growing travel mode in China. Nonetheless, research on this issue have been limited by the lack of systematic data-- especially spatial data--as well as other related data sources, and by the limitation of the quantitative methods in exploring the organization and efficiency of the inter-urban organization network in transitional China. This paper is a general process evaluation and actual description of the spatio-temporal structural characteristics of the Inter-urban Aviation Network in China (IANC) from 1983 to 2006 based on complex network methods. The conclusions can be drawn as follows. 1) The IANC exhibits the densification trends featured by a small-world network. 2) It follows the "hub-and-spoke" network organization model. Beijing, Shanghai, Guangzhou, and Shenzhen act as the multi-hubs, and the spatial connections among them act as the spokes. Urumqi and Kunming are particularly important local hubs; around them have formed two relatively independent local hub-and-spoke networks. 3) A "saddle-type" model has formed in the evolution of the IANC. Specifically, the structures of the eastern and western regions' aviation networks are better formed than that of the central region. 4) The cities in the IANC show a "community network" effect. To be more specific, hub cities, geographical neighboring cities, and cities with similar urban functions have similar urban spatial interaction characteristics. 5) The hub status of 35 important cities in the network varied with the development of the IANC. Moreover, there are great spatial disparities among tourist cities such as Huangshan and Lijiang, coastal cities such as Dalian and Qingdao, and western cities such as Lhasa.

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