地理科学 ›› 2020, Vol. 40 ›› Issue (10): 1671-1678.doi: 10.13249/j.cnki.sgs.2020.10.011

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1998—2016年中国省际网络联系结构特征

赵映慧1(), 朱亮1,2, 马百通1, 许月2, 姜博1   

  1. 1. 东北农业大学公共管理与法学院,黑龙江 哈尔滨 150030
    2. 东北农业大学资源与环境学院,黑龙江 哈尔滨 150030
  • 收稿日期:2019-03-03 出版日期:2020-10-10 发布日期:2020-12-05
  • 作者简介:赵映慧(1976−),男,四川广元人,副教授,博士,主要从事城市地理与区域发展研究。E-mail: zhaoyhneau@163.com
  • 基金资助:
    国家自然科学基金项目 (41471141)、教育部人文社会科学研究项目 (16YJCZH034)资助

Characteristics of Inter-provincial Network Connection Based on Railway Freight Flow in China, 1998-2016

Zhao Yinghui1(), Zhu Liang1,2, Ma Baitong1, Xu Yue2, Jiang Bo1   

  1. 1. College of Public Administration and Law, Northeast Agricultural University, Harbin 150030, Heilongjiang, China
    2. College of Resource and Environment, Northeast Agricultural University, Harbin 150030, Heilongjiang, China
  • Received:2019-03-03 Online:2020-10-10 Published:2020-12-05
  • Supported by:
    National Natural Sciences Foundation of China (41471141), Humanities and Social Science Foundation of the Ministry of Education of China (16YJCZH034)

摘要:

基于中国省级行政区之间铁路货流数据(不含港澳台),采用社会网络分析及GIS空间分析等对1998—2016年中国省际网络联系结构特征进行分析。结果表明:① 1998—2016年中国铁路货流网络密度呈先增长后下降的趋势;② 中部地区和环渤海经济圈的省份在铁路货流网络中货运量处于领先地位,沿海省份之间铁路货运联系减弱;③ 山西和内蒙古在铁路货流网络中占有重要地位,而海南、西藏则在铁路货流网络中处于边缘地位;④ 广东密切联系华中地区和西南地区,西北省份相互联系及对外联系都较弱;⑤ 铁路货流网络中地域邻近性与经济联系很大程度上决定了凝聚子群的构成,随着中国经济发展和铁路货运的不断变化,铁路货流网络的凝聚子群增多,规模变小。

关键词: 铁路货流, 省际网络, 网络联系, 凝聚子群

Abstract:

Based on the data of railway freight flow among provincial administrative regions of China (excluding Hong Kong, Macau and Taiwan), this article analyzes the characteristics of inter-provincial network by social network analysis and GIS in China from 1998 to 2016. The results show that: 1) The density of China’s railway freight network has been increased from 1998 to 2011 and it has been decreased from 2012 to 2016. In 2011, the density of China’s railway freight network reached its maximum, and it began to decline slightly in 2012. The density declined in 2016 and it is roughly the same as that in 2006. It shows that the contribution of railway freight to economic development has increased from 1998 to 2011, and the connection among provincial administrative regions has become closer. From 2012 to 2016, the demand for railway freight flow in economic development has decreased; 2) The provinces in the eastern China and in the Bohai economic rim are in the leading position in the railway freight network, and the railway freight connections among the provinces in the eastern China are decreasing; 3) There is a huge amount of coal in Shanxi Province; it has the largest connection with other provincial administrative regions. Therefore, Shanxi Province plays a very important role in China’s railway freight network. Inner Mongolia autonomous region also has a huge amount of coal, which is sent to North China and Northeast China by the railway. So it also plays a very important role in China’s railway freight network. Hainan province and Tibet autonomous region are marginalized in China’s railway freight network because of limitations of geographical location, a short history of railway operation and its low economic development level; 4) Guangdong in the southern coastal regions is a developed province and its economy development is prospering. And there is a very important Guangzhou port in Guangdong Province. A lot of freight is flowing between Guangdong Province and the provinces in Central China and Southwest China, so there are lots of close connections between them. Most provinces (autonomous regions) in the Northwest China are developing provinces (autonomous regions) and their density of the traffic network is low. Therefore, the northwestern provinces (autonomous regions) are weakly connected to each other and to the provinces in the other regions. 5) In the railway freight network, geographical proximity and economic connections largely determine the composition of the cohesive subgroup. With the economy development and the continuous changes of railway freight transportation, the cohesive subgroups of railway freight network increase, and their scales become smaller. For example, in China’s railway freight network, there are 4 cohesive subgroups in 1998; and the number of cohesive subgroups increases from 6 cohesive subgroups in 2011 to 7 cohesive subgroups in 2016. The members of cohesive subgroups have decreased from 4-10 members in 1998 to 3-5 members in 2016.

Key words: railway freight flow, inter-provincial network, network connection, cohesive subgroup

中图分类号: 

  • F291