Evaluating multiscale and multimodal transport inequalities in Chinese cities with massive open-source path data

JOURNAL OF GEOGRAPHICAL SYSTEMS(2023)

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摘要
Accessibility is an effective variable for identifying mobility needs and evaluating transport inequalities. In recent years, the construction of transport facilities has been often considered to have a significant effect on the accessibility of cities. This study focused on the regional inequalities of transport accessibility in China and the influence of transport mode disparity. A novel approach integrating intercity and intracity transport networks is modeled for detailed calculations of travel time using open-source massive path data. The proposed approach provides further improvement in the accuracy, and it can reflect realistic patterns of multiscale accessibility. Four indicators based on travel time estimation were employed to evaluate transport accessibility and inequality: weighted average travel time (WATT), potential value (PV), daily accessibility (DA), and coefficient of variation (CV). Results show that transport accessibility is the highest in the eastern region, followed by the midland, northeastern, and western regions; this trend is consistent with the level of urban development and transport facilities construction. The inequality of transport accessibility between cities is obvious, and the western region has a considerably greater inequality than other areas. With regard to transport facilities, the car driving mode has higher accessibility and lower discrepancy than the public transit mode at the national level; however, the construction of public transit infrastructure, especially the high-speed railway, should considerably improve the daily accessibility of cities. Several policy suggestions are provided for transport departments and decision makers that can effectively improve the level and equality of transport accessibility of cities in China.
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关键词
Inequality,Multiscale accessibility,Multimode transportation,Open-source massive path data,China
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