High-speed railway network structure and characteristics in three urban agglomerations in China

ZHAO Yinghui1 CHU Nanchen1,2 GUO Jingpeng1 JIANG Bo1 ZHU Liang1

(1.College of Resources and Environment, Northeast Agricultural University, Harbin, Heilongjiang, China 150030)
(2.Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, Jilin, China 130102)

【Abstract】The paper constructs the origin-destination matrix of intercity high-speed railway (HSR) operating frequency in the Yangtze River Delta, the Pearl River Delta and the Beijing-Tianjin-Hebei Region. HSR network structure and characteristics in three urban agglomerations in China are studied based on social network analysis. The results show that the overall relevance of HSR network of Beijing-Tianjin-Hebei Region is the closest followed by the Yangtze River Delta. The Pearl River Delta is the loosest. The intercity connection ability and network imbalance of HSR are the strongest in the Yangtze River Delta. HSR connection of the eastern part is closer than the western part in the Yangtze River Delta. HSR connection of the northern part is closer than the other parts in the Pearl River Delta. HSR flow frequent areas concentrate in Beijing and Tianjin in Beijing-Tianjin-Hebei Region. The order of provincial internal HSR closeness is: Jiangsu > Zhejiang > Guangdong > Hebei > Anhui. Shenzhen-Guangzhou, Shanghai-Nanjing, Shanghai-Suzhou, Nanjing-Suzhou, and Shanghai-Wuxi belong to intercity high density HSR connection. HSR network of three urban agglomerations all have significant characteristics of “small world” effect. And “small world” effect of the Beijing-Tianjin-Hebei Region and the Yangtze River Delta is stronger than the Pearl River Delta. Hefei-Suzhou-Zhenjiang-Nanjing-Wuxi-Lu’an is the HSR radiation clusters in the Yangtze River Delta. Guangzhou-Huizhou, Shenzhen-Dongguan, Tianjin-Cangzhou are the important HSR radiation pairs. Shanghai, Nanjing are the cores in the Yangtze River Delta HSR network. Guangzhou and Shenzhen are the centers in the Pearl River Delta HSR network. Beijing and Tianjin are the cores in the Beijing-Tianjin-Hebei HSR network.

【Keywords】 high-speed railway (HSR) ; social network analysis; operating frequency; urban agglomerations;


【Funds】 Humanities and Social Science Fund Project of the Ministry of Education (16YJCZH034) National Natural Science Foundation of China (41101153)

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(Translated by HE wenshan)


    [1] Scott N, Baggio R, Cooper C. Network Analysis and Tourism: From Theory to Practice. Bristol: Channel View Publication, 2008: 222.

    [2] Liu, J. Lectures on Whole Network Approach: a Practical Guide on UCINET (整体网分析讲义:UCINET软件使用指南). Shanghai: Gezhi Press, (2009).

    [3] Tindall D B, Wellman B. Canada as social structure: Social network analysis and Canadian sociology. Canadian Journal of Sociology, 2001, 26 (3): 265–308.

    [4] Stefan Krätke. Global pharmaceutical and biotechnology firms’ linkages in the world city network. Urban Studies, 2014, 51 (6): 1196–1213.

    [5] Taylor P J, Gatalano G, Walker D R F. Measurement of the world city network. Urban Studies, 2002, 39 (13): 2367–2376.

    [6] Ho Shin K, Timberlake A. World cities in Asia: Cliques, centrality and connectedness. Urban Studies, 2000, 37 (12): 2257–2285.

    [7] Matsumoto H. International urban systems and air passenger and cargo flows: Some calculations. Journal of Air Transport Management, 2004 (10): 239–247.

    [8] HAM Klemann, J Schenk. Competition in the Rhine delta: waterways, railways and ports, 1870–1913. The Economic History Review, 2013, 66 (3): 826–847.

    [9] Cai, L., Ma, X., Chen, W. et al. Economic Geography (经济地理), 33 (11): 52–57 (2013).

    [10] Zhu, T., Wu, D., Ma, J. et al. Economic Geography (经济地理), 31 (4): 561–565, 572 (2011).

    [11] Zhao, Y., Jiang, B., Guo, H. et al. Economic Geography (经济地理), 36 (2): 67–73 (2016).

    [12] Liu, Z., Liu, J., He, X. et al. Economic Geography (经济地理), 4 (7): 58–66 (2014).

    [13] Gao, X., Xiu, C., Wei, Y. et al. Human Geography (人文地理), 31 (1): 73–80 (2016).

    [14] Ye, L., Duan, X. & Ou, X. Scientia Geographica Sinica (地理科学), 35 (10): 1230–1237 (2015).

    [15] Liu, H., Shen, Y., Meng, D. et al. Economic Geography (经济地理), 33 (8): 37–45 (2013).

    [16] Jiang, B., Chu, N., Xiu, C. et al. Acta Geographica Sinica (地理学报), 71 (4): 591–604 (2016).

    [17] Feng, C., Feng, X. & Liu, S. Progress in Geography (地理科学进展), 32 (8): 1187–1194 (2013).

    [18] Zhong, Y., Huang, J. & Wen, Y. Geographical Sciences (地理科学), 35 (4): 387–395 (2015).

    [19] Jiang, H., Xu, J. & Qi, Y. Acta Geographica Sinica (地理学报), 65 (10): 1287–1298 (2010).

    [20] Jiang, B., Chu, N., Gong, Y. et al. Economic Geography (经济地理), 34 (11): 58–62, 68 (2014).

    [21] Wang, J. & Jiao, J. Tropical Geography (热带地理), 34 (3): 275–282 (2014).

    [22] Wang, J. & Ding, J. Urban Planning International (国际城市规划), 26 (6): 49–54 (2011).

    [23] Zhang, X. & Nie, Q. Modern Urban Research (现代城市研究), 25 (6): 7–10 (2010).

    [24] Wang, J., Jiao, J. & Jin, F. Acta Geographica Sinica (地理学报), 69 (12): 1833–1846 (2014).

    [25] Wang, J. & Lin, C. Urban Planning International (国际城市规划), 26 (1): 16–23 (2011).

    [26] Chen, J., Zheng, G. & Liu, Y. Economic Geography (经济地理), 34 (8): 54–60, 67 (2014).

This Article



Vol 37, No. 10, Pages 68-73

October 2017


Article Outline


  • 1 Research methods and data sources
  • 2 Results analysis
  • 3 Conclusions
  • References