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ZHOU Suhong, DENG Lifang, HUANG Meiyu. Spatial Analysis of Commuting Mode Choice in Guangzhou, China[J]. Chinese Geographical Science, 2013, 23(3): 353-364. doi: 10.1007/s11769-012-0569-2
Citation: ZHOU Suhong, DENG Lifang, HUANG Meiyu. Spatial Analysis of Commuting Mode Choice in Guangzhou, China[J]. Chinese Geographical Science, 2013, 23(3): 353-364. doi: 10.1007/s11769-012-0569-2
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Spatial Analysis of Commuting Mode Choice in Guangzhou, China

doi: 10.1007/s11769-012-0569-2
  • 1.

    School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;

  • 2.

    Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China;

  • 3.

    Guangzhou Panyu Urban Planning & Design Institute, Guangzhou 511400, China;

  • 4.

    Bartlett School of Planning, University College London, London WC1E 6BT, United Kingdom

Funds:  Under the auspices of National Natural Science Foundation of China (No. 40971098), National High Technology Research and Development Program of China (No. 2012AA121402)
More Information
  • Corresponding author: ZHOU Suhong. E-mail: eeszsh@mail.sysu.edu.cn
  • Received Date: 2011-12-08
  • Rev Recd Date: 2012-03-22
  • Publish Date: 2013-05-29
  • Metropolitan cities in China are commonly confronted with unresolved traffic congestion issues, primarily due to rapidly increasing traffic demand. Group disparity between commuting mode choice and its spatial distribution on road networks has enabled us to examine the factors that give rise to the discrepancies and the fundamental spatial causes of traffic congestion. In recent years, micro-perspective, individual, and behavior-based spatial analysis have mushroomed and been facilitated with effective tools such as temporal geographic information systems (T-GIS). It is difficult to study the interrelations between transport and space on the basis of commuting mode choice since the mode choice data are invisible in a specific space such as a particular road network. Therefore, in the field of transport, the classical origin destination (OD) four-stage model (FSM) is usually employed to calculate data when studying commuting mode choice. Based on the relative principles of T-GIS and the platform of ArcGIS, this paper considers Guangzhou as a case study and develops a spatio-temporal tool to examine the daily activities of residents. Meanwhile, the traffic volume distribution in rush hours, which was analyzed according to commuting modes and how they were reflected in the road network, was scrutinized with data extracted from travel diaries. Moreover, efforts were made to explain the relationship between traffic demand and urban spatial structure. Based on the investigation, this research indicates that traffic volumes in divergent groups and on the road networks is driven by: 1) the socio-economic characteristics of travelers; 2) a jobs-housing imbalance under suburbanization; 3) differences in the spatial supply of transport modes; 4) the remains of the Danwei (work unit) system and market development in China; and 5) the transition of urban spatial structure and other factors.
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Spatial Analysis of Commuting Mode Choice in Guangzhou, China

doi: 10.1007/s11769-012-0569-2
  • 1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;
  • 2. Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China;
  • 3. Guangzhou Panyu Urban Planning & Design Institute, Guangzhou 511400, China;
  • 4. Bartlett School of Planning, University College London, London WC1E 6BT, United Kingdom
Funds:  Under the auspices of National Natural Science Foundation of China (No. 40971098), National High Technology Research and Development Program of China (No. 2012AA121402)
    Corresponding author: ZHOU Suhong. E-mail: eeszsh@mail.sysu.edu.cn
  • Received Date: 2011-12-08
  • Rev Recd Date: 2012-03-22
  • Publish Date: 2013-05-29

Abstract: Metropolitan cities in China are commonly confronted with unresolved traffic congestion issues, primarily due to rapidly increasing traffic demand. Group disparity between commuting mode choice and its spatial distribution on road networks has enabled us to examine the factors that give rise to the discrepancies and the fundamental spatial causes of traffic congestion. In recent years, micro-perspective, individual, and behavior-based spatial analysis have mushroomed and been facilitated with effective tools such as temporal geographic information systems (T-GIS). It is difficult to study the interrelations between transport and space on the basis of commuting mode choice since the mode choice data are invisible in a specific space such as a particular road network. Therefore, in the field of transport, the classical origin destination (OD) four-stage model (FSM) is usually employed to calculate data when studying commuting mode choice. Based on the relative principles of T-GIS and the platform of ArcGIS, this paper considers Guangzhou as a case study and develops a spatio-temporal tool to examine the daily activities of residents. Meanwhile, the traffic volume distribution in rush hours, which was analyzed according to commuting modes and how they were reflected in the road network, was scrutinized with data extracted from travel diaries. Moreover, efforts were made to explain the relationship between traffic demand and urban spatial structure. Based on the investigation, this research indicates that traffic volumes in divergent groups and on the road networks is driven by: 1) the socio-economic characteristics of travelers; 2) a jobs-housing imbalance under suburbanization; 3) differences in the spatial supply of transport modes; 4) the remains of the Danwei (work unit) system and market development in China; and 5) the transition of urban spatial structure and other factors.

ZHOU Suhong, DENG Lifang, HUANG Meiyu. Spatial Analysis of Commuting Mode Choice in Guangzhou, China[J]. Chinese Geographical Science, 2013, 23(3): 353-364. doi: 10.1007/s11769-012-0569-2
Citation: ZHOU Suhong, DENG Lifang, HUANG Meiyu. Spatial Analysis of Commuting Mode Choice in Guangzhou, China[J]. Chinese Geographical Science, 2013, 23(3): 353-364. doi: 10.1007/s11769-012-0569-2
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