Investigating Intercity Rail Transit Scope with Social Economy Accessibility: Case Study of the Pearl River Delta Region in China

Xiaoshu Cao , Linna Li , Heng Wei

Urban Rail Transit ›› 2017, Vol. 3 ›› Issue (1) : 61 -71.

PDF
Urban Rail Transit ›› 2017, Vol. 3 ›› Issue (1) : 61 -71. DOI: 10.1007/s40864-017-0058-0
Original Research Papers

Investigating Intercity Rail Transit Scope with Social Economy Accessibility: Case Study of the Pearl River Delta Region in China

Author information +
History +
PDF

Abstract

In response to challenges caused by high gasoline prices, traffic congestion, and greenhouse gas emissions, smart internment on intercity rail transit infrastructures and service suggests a rekindling of many countries’ interest in offering a range of benefits over automobile travels. In order to check the suitability of the proposed intercity rail transit system with the local conditions in a region, models for relating the intercity rail transit scope and social economy factors have been developed with the datasets obtained in the Pearl River Delta (PRD) region in Guangdong Province, China. In this paper, the accessibility-based approach is presented to explore the impact of the intercity rail transit system planning on the regional development. The impact of three typical accessibility variables, transportation, population, and economic accessibilities, are considered in the approach. The global rail transit scope planning models are developed by using the regression technique to correlate the lengths of 254 regional intercity rail transit systems in different countries in the world with social economy factors. Those models are used for estimating the intercity rail transit size for the PRD region. The modeled transit scopes are examined with spatial distributions of the defined three accessibilities at each node (or centroid center of a town) in a Geographic Information System environment. The developed method has been proven helpful to understanding the gap between transport supply and potential travel demand and the suitability of each node to alignment of each rail transit route through the PRD region case study.

Keywords

Intercity rail transit / Population accessibility / Economy accessibility / Transportation accessibility / Social economic factors

Cite this article

Download citation ▾
Xiaoshu Cao, Linna Li, Heng Wei. Investigating Intercity Rail Transit Scope with Social Economy Accessibility: Case Study of the Pearl River Delta Region in China. Urban Rail Transit, 2017, 3(1): 61-71 DOI:10.1007/s40864-017-0058-0

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Renner M, Gardner G (2010). Global competitiveness in the rail and transit industry. Report for Apollo Transportation Manufacturing Initiative

[2]

The National Surface Transportation Policy and Revenue Study Commission (NSTPRSC) (2007) Transportation for tomorrow. Report of NSTPRSC

[3]

Quan H, Li SM (2011) Transport Infrastructure Development and Changing Spatial Accessibility in the Greater Pearl River Delta, China, 1990–2020. Working paper series

[4]

Gutiérrez J, González R, Gómez G. The European high-speed train network: predicted effects on accessibility patterns. J Transp Geogr, 1996, 4(4): 227-238

[5]

Jiang H, Xu J, Qi Y. The influence of Beijing–Shanghai high-speed railways on land accessibility of regional center cities. Acta Geogr Sin, 2010, 65(10): 1287-1298.

[6]

Murayama Y. The impact of railways on accessibility in the Japanese urban system. J Transp Geogr, 1994, 2(2): 87-100

[7]

Geurs KT, van Wee B. Accessibility evaluation of land-use and transport strategies: review and research directions. J Transp Geogr, 2004, 12: 127-140

[8]

Babalik-Sutcliffe E. Urban rail systems: analysis of the factors behind success. Transp Rev, 2002, 22(4): 415-447

[9]

Cao X, Lin Q. The evolution of worldwide metro systems: a study on their scales and network indexes. Acta Geogr Sin, 2008, 63(12): 1257-1267 (in Chinese)

[10]

Loo BPY, Cheng AHT. Are there useful yardsticks of population size and income level for building metro systems? Some worldwide evidence. J Transp Geogr, 2010, 27: 299-306.

[11]

Sachs J (2005) The end of poverty. How can we make it happen in our lifetime. Penguin Books, London

[12]

World Bank (2008) World development report. 2009, reshaping economic geography

[13]

Reggiani A. Accessibility, trade and location behavior, 1998, Aldershot: Ashgate

[14]

Castella JC, Manh PH, Kam SP, Villano L, Tronche NR. Analysis of village accessibility and its impact on land use dynamics in a mountainous province of northern Vietnam. Appl Geogr, 2005, 25: 308-326

[15]

Etter A, McAlpine C, Wilson K, Phinn S, Possingham H. Regional patterns of agricultural land use and deforestation in Colombia. Agr Ecosyst Environ, 2006, 114: 369-386

[16]

Hanson S. Dimensions of the urban transportation problem. Geographic perspectives on urban transportation, 1986, New York: Guilford Press 3-23.

[17]

Laurance WF, Albernaz AK, Schroth G, Fearnside PM, Bergen S, Venticinque EM Predictors of deforestation in the Brazilian Amazon. J Biogeogr, 2002, 29: 737-748

[18]

Nagendra H, Southworth J, Tucker C. Accessibility as a determinant of landscape transformation in western Honduras: linking pattern and process. Landsc Ecol, 2003, 18: 141-158

[19]

Verburg PH, Overmars KP, Witte N. Accessibility and land-use patterns at the forest fringe in the northeastern part of the Philippines. Geogr J, 2004, 170: 238-255

[20]

Guagliardo M (2004) Spatial accessibility of primary care: concepts, methods and challenges. Int J Health Geogr 3(1):3. doi:10.1186/1476-072X-3-3

[21]

Jalan J, Ravallion M. Geographic poverty traps? A micro model of consumption growth in rural China. J Appl Econom, 2002, 17: 329-346

[22]

Bryceson DF, Bradbury A, Bradbury T. Roads to poverty reduction? Exploring rural roads’ impact on mobility in Africa and Asia. Dev Policy Rev, 2008, 26: 459-482

[23]

Olsson J (2006) Responses to change in accessibility: socio-economic impacts of road investment: the distributive outcomes in two rural peripheral Philippine municipalities. Department of Human and Economic Geography, School of Business, Economics and Law, Göteborg University

[24]

The Guardian (2016) China’s Pearl River Delta overtakes Tokyo as world’s largest megacity. The article was drafted on 28 January 2015. Last modified on 15 June 2016. Accessible at https://www.theguardian.com/cities/2015/jan/28/china-pearl-river-delta-overtake-tokyo-world-largest-megacity-urban-area

[25]

Demographia Gross Domestic Product (GDP-PPP) Estimates for Metropolitan Regions in Western Europe, North America, Japan and Australasia, 2007, Belleville: Wendell Cox Consultancy

[26]

Demographia Demographia 2000–2008 metropolitan area population & migration, 2009, Belleville: Wendell Cox Consultancy

[27]

Demographia Demographia world urban areas: population projections, 2009, Belleville: Wendell Cox Consultancy

Funding

National Natural Science Foundation of China(#41171139)

AI Summary AI Mindmap
PDF

196

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/