The Spatial-temporal Evolution, Scale and Network Characteristics of Intercity Rail Transit in Worldwide Metropolitan Areas

  • 1. Depatrment of Geography, The University of Hong Kong, Hong Kong;
    2. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China

Received date: 2011-05-01

  Revised date: 2011-08-01

  Online published: 2012-02-25


Based on 255 worldwide intercity rail transit samples, this paper summarizes the spatial-temporal evolution and network characteristics of intercity rail transit, analyzes the correlation between intercity rail transit scale and metropolitan population, area and economic scale, and then constructs five regression models. Finally, it predicts the scale and layout of intercity rail transit in the Pearl River Delta of China by applying the models. The models indicate that that the scale of intercity rail is mostly related to regional economic scale, and less related to regional population and area scale. Meanwhile, there is exponential correlation between regional intercity rail scale per capita and regional GDP per capita as well as the population density. And the rail scale per capita is positively correlated to GDP per capita while negatively related to population density. According to the application of regression models, the planning scale of intercity rail transit in the Pearl River Delta is advanced comparing with the economic development while lagged comparing with the population development. In a short period of time, the intercity rail should connect the significant nodes in Guangzhou, Shenzhen, Foshan and Dongguan as well as the inner cities in other cities in the Pearl River Delta. In the long term, the rail line density should be increased in Guangzhou, Shenzhen, Foshan, Dongguan, Zhuhai and Zhongshan, and the nodes number should be increased in the periphery cities including Zhaoqing, Huizhou and Jiangmen.

Cite this article

LI Linna, CAO Xiaoshu, HUANG Xiaoyan . The Spatial-temporal Evolution, Scale and Network Characteristics of Intercity Rail Transit in Worldwide Metropolitan Areas[J]. PROGRESS IN GEOGRAPHY, 2012 , 31(2) : 221 -230 . DOI: 10.11820/dlkxjz.2012.02.011


[1] Henderson H. Light rail, heavy cost. Planning, 1994, 60 (5): 8-14.
[2] Priemus H, Konings R. Light rail in urban regions: What Dutch policymakers could learn from experiences in France, Germany and Japan. Journal of Transport Geography, 2001, 9(3): 187-198.
[3] Belzer D, Autler G. Transit oriented development: Moving from rhetoric to reality. 2002-06-15[2010-04-04].
[4] Givoni M, Rietveld P. The access journey to the railway station and its role in passengers' satisfaction with rail travel. Transport Policy, 2007, 14(5): 357-365.
[5] Givoni M, Banister D. Airline and railway integration. Transport Policy, 2006, 13(5): 386-397.
[6] Nijkamp P, Reggiani Aa, Tritapepe T. Modelling inter-urban transport flows in Italy: A comparison between neural network analysis and logit analysis. Transportation Research Part C: Emerging Technologies, 1996, 4(6): 323-328.
[7] Mandel B, Gaudry M, Rothengatter W. A disaggregate Box-Cox Logit mode choice model of intercity passenger travel in Germany and its implications for high-speed rail demand forecasts. The Annals of Regional Science, 1997, 31(2): 99-120.
[8] Martin J, Nombela G. Micro economic impacts of investments in high speed trains in Spain. The Annals of Regional Science, 2007, 41(3): 715-733.
[9] Sakanishi A. Commuting patterns in the Osaka Metropolitan area: A GIS-based analysis of commuter rail passengers. Review of Urban and Regional Development Studies, 2006, 18(1): 41-59.
[10] Senior M L. Impact on travel behavior of Great Manchester's light rail investment (Metrolink Phase 1): Evidence from household surveys and Census data. Journal of Transport Geography, 2009, 17(3): 187-197.
[11] Froidh O. Market effect of regional high-speed trains on the Svealand line. Journal of Transport Geography, 2005, 13(4): 352-361.
[12] Bollinger C R, Ihlanfeldt K R. The impact of rapid rail transit on economic development: The case of Atlanta's MARTA. Journal of Urban Economics, 1997, 42(2): 179-204.
[13] Zhu X, Liu S. Analysis of the impact of the MRT system on accessibility in Singapore using an integrated GIS tool. Journal of Transport Geography, 2004, 12(2): 89-101.
[14] Ryan S. The value of access to highways and light rail transit: evidence for industrial and office firms. Urban Studies, 2005, 42(4): 751-764.
[15] 袁家冬, 李少星. 日本三大都市圈快速轻轨交通网的形成与发展. 世界地理研究, 2005, 14(3): 1-6.
[16] 陆化普, 王建伟, 陈明. 城际快速轨道交通客流预测方法研究. 土木工程学报, 2003, 36(1): 41-45.
[17] 王海强, 马国忠, 刘开元. 基于重要度的城际轨道交通空间出行分布预测的研究. 交通标准化, 2005, 2(3): 93-96.
[18] 曹小曙, 刘望保. 城际轨道交通规划建设对珠江三角洲区域空间的影响. 现代城市研究, 2005(12): 43-46.
[19] 边经卫. 大城市空间发展与轨道交通. 北京: 中国建筑工业出版社, 2006.
[20] 颜琼. 城际轨道交通沿线土地集约利用对区域经济发展的作用. 都市快轨交通, 2006, 19(2): 6-12.
[21] Wikipedia. Light rail. 2012-01-29[2012-01-29]. http://en.
[22] Wikipedia. Commuter rail. 2012-01-18[2012-01-29]. http: //
[23] Wikipedia. High-speed rail. 2012-01-28[2012-01-29].
[24] Demographia. Demographic World Urban Areas & Population Projections. 5th ed. 2012-01-23[2012-01-29]
[25] Taplin M. The history of tramways and evolution of light rail. 2006-08-24[2010-04-04].
[26] Rodrigue J P, Comtois C, Slack B. The Geography of Transport Systems. New York: Routledge, 2009.
[27] 吕韬, 姚士谋, 曹有挥, 等. 中国城市群区域城际轨道交通布局模式. 地理科学进展, 2010, 29(2): 249-256.