地理研究

地理研究 ›› 2018, Vol. 37 ›› Issue (11): 2193-2205.doi: 10.11821/dlyj201811006

• 研究论文 • 上一篇    下一篇

基于日高铁流量视角的中国高速铁路网络空间特征

初楠臣1,2(), 张平宇1(), 姜博3   

  1. 1. 中国科学院东北地理与农业生态研究所,长春 130102
    2. 中国科学院大学,北京 100049
    3. 东北农业大学资源与环境学院,哈尔滨 150030
  • 收稿日期:2018-06-14 修回日期:2018-09-01 出版日期:2018-11-20 发布日期:2018-11-23
  • 作者简介:

    作者简介：初楠臣（1992- ）,男,黑龙江佳木斯人,博士研究生,主要从事城市地理与区域发展研究。E-mail: chunanchen_1992@163.com

  • 基金资助:
    国家科技基础资源调查专项课题（2017FY101303-1）;国家自然科学基金项目（41571152）;黑龙江省自然科学基金项目（G2018003）

Spatial characteristics of Chinese high-speed railway network from the perspective of daily flow

Nanchen CHU1,2(), Pingyu ZHANG1(), Bo JIANG3   

  1. 1. Northeast Institute of Geography and Agroecology, CAS, Changchun 130102, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. College of Resource and Environment, Northeast Agricultural University, Harbin 150030, China
  • Received:2018-06-14 Revised:2018-09-01 Online:2018-11-20 Published:2018-11-23
  • About author:

    Author: Shi Zhenqin (1988-), PhD, specialized in regional development and land space management in mountain areas. E-mail: kevinszq@163.com

    *Corresponding author: Deng Wei (1957-), Professor, specialized in mountain environment and regional development.

    E-mail: dengwei@imde.ac.cn

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摘要：

构建中国180×180的O-D城市日高铁流量矩阵,基于社会网络分析研究其高铁网络结构特征,结果表明：① 中国高铁网络松散,东、中部网络密度大于东北与西部,以长三角为核心的东南与其他区域不均衡特征凸显,东、中、西、东北包含不同的高铁区系与核心。② 日高铁流量表现为沿京沪高铁“廊道型”向东西两侧递减弱化的“非对称性”格局,形成京沪、京广、杭福深相串联的高铁大三角主骨架;高铁中心要素也呈现沿京沪、京广、沪昆、杭福深等向线路两侧不规则递减格局,“廊道效应”显著。③ 胡焕庸线东南侧城市对高铁要素掌控能力大于西北侧,省会或区域中心城市多为高铁通达服务“中介”,一线城市高铁空间溢出效应有向二、三线城市过渡态势。

关键词: 高铁网络, 日高铁流量, 社会网络分析, 结构特征, 空间格局, 中国

Abstract:

This paper studied the spatial structure, pattern, and characteristics of China's high-speed railway (HSR) network. The paper first built a daily origin-destination (O-D) HSR flow matrix consisting of 180*180 cities to evaluate the daily HSR flow of China. Then by analyzing the network density, four kinds of centralities, core/periphery structure and cohesive subgroups using the network analysis software, i.e., University of California at Irvine Network (UCINET), this paper displayed the structure and characteristics of China's HSR network. Finally, the global trend analysis and spatial interpolation function of geographic information system (GIS) were used to simulate the pattern of the daily HSR flow and four kinds of centralities in China and to reveal the characteristics and the differentiation of their spatial distribution. The results are as follows. First, spatially, the HSR network of China is loosely organized. The HSR network density of different regions differs greatly as such: eastern China> central China> northeastern China> western China. Particularly, the HSR network density of the Yangtze River Delta is higher than that of other region in China. This phenomenon shows the imbalanced and uncoordinated development of China's current HSR network. The HSR cliques and cores of eastern China, central China, northeastern China and western China are different. Second, by analyzing the daily HSR flow, we find that the flow of Beijing-Shanghai HSR line which has developed into the main "corridor" of China's HSR flow is much higher than that of the rest lines. However, its west and east sides have shown an asymmetric reduction trend. Beijing-Shanghai HSR line, Beijing-Guangzhou HSR line and Hangzhou-Fuzhou-Shenzhen HSR line are the nation's HSR center-lines, as they have the highest daily HSR flow. These three lines have developed into a triangle pattern, which is the basis of China's HSR spatial structure. The spatial pattern of the flows of the key urban elements, such as the population and industries, has been affected by the HSR network. These key elements of both sides of the Beijing-Shanghai HSR, Beijing-Guangzhou HSR, Shanghai-Kunming HSR, Hangzhou-Fuzhou-Shenzhen HSR lines have an asymmetric reduction trend, which shows the strong influence of the "corridor". Third, key elements related to HSR such as population and industries of the cities located to the southeast of the Hu Huanyong Line are higher than those of the cities to the northwest of the line in China. Beijing, Guangzhou, Chengdu, Chongqing, Shenzhen, Zhengzhou, Shijiazhuang, Nanjing and Shanghai are the national important HSR accessibility intermediary cities. These cities, together with other provincial capitals and regional central cities, have spatially developed into multiple service centers of China. Besides, the spatial spillover effects based on the HSR accessibility have been spilled from the first-tier developed cities to the second-tier or third-tier cities. The HSR development and its accessibility have brought potential agglomeration chances to second-tier or third-tier cities.

Key words: HSR network, daily HSR flow, social network analysis, structure and characteristics, spatial pattern, China