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Jing Guo   Dr.  Graduate Student or Post Graduate 
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Jing Guo published an article in June 2015.
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Qiang Li

3 shared publications

College of Resources Sciences & Technology, Beijing Normal University, No. 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China

Xuemin Liu

3 shared publications

College of Resources Sciences & Technology, Beijing Normal University, No. 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China

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CONFERENCE-ARTICLE 1 Read 0 Citations Urban Density, Accessibility and Energy Consumption in the Transport Sector: Analysis of 30 Cities in China Jing Guo, Jing Zhang, Qiang Li, Xuemin Liu Published: 08 June 2015
8th Conference of the International Forum on Urbanism (IFoU), doi: 10.3390/ifou-E002
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The growth and diversification of transport demand accompanied with social and economic development led to increasing energy consumption in transport sector. In order to find a way that can not only contribute to reducing transportation energy consumption but also fully meet the transport demand, the research firstly formulated three indicators. Urban density implies population size and intensity of social and economic activities that is related to transport demand. Accessibility is defined by per capita road area and average bus numbers of ten thousand people and reflects transport conditions of private and public traffic. Per capita energy consumption in transport sector was used to characterize environmental effects. The data of urban density and accessibility was collected from the National Statistical Yearbook, while the data of transport energy consumption was obtained by conversion of DMSP/OLS (Defense Meteorological Satellite Program/Operational Lines-can System) night lighting data which is a sign of human activity. Secondly, considering the different levels of transport infrastructure and economic development in different regions of China, only 30 provincial capital cities were selected to analyze the relationships of the three indicators mentioned above. Based on relationship analysis, 30 cities were divided into three patterns. It was founded that the first pattern would be optimal because of a good match of transport demand and supply coupled with low energy consumption. The second pattern is non-ideal, since it is at high level of energy consumption and less balanced between transport demand and supply. The third pattern should improve accessibility and reduce energy consumption. Finally, some suggestions about urban transport development that are suitable to local conditions were proposed for different urban patterns.