A Comprehensive Vector Dataset of Bus Networks Across China for the Year 2024

Urban public transportation systems facilitate traffic flow and promote sustainable urban development by offering convenient, economical, and environmentally friendly transit services. However, existing research often lacks large-scale bus network data, limiting the potential for comprehensive and in-depth analyses of urban transit systems' complexity and scope. Consequently, large-scale vector data on urban bus networks hold immense value. We designed a set of high-precision algorithms for generating bus network vector data based on electronic map APIs, which include steps such as coordinate transformation, network simplification, station projection, and topology generation. After cross-validation, a vector dataset containing bus stops, routes, and topology for 299 cities in China was generated and stored in Shapefile format (a widely used GIS file). The dataset offers valuable insights for studying network patterns in China's bus systems, supporting international comparative analyses of public transportation systems. Given that China operates the largest bus system globally, this dataset carries substantial academic and practical significance, providing data-driven insights for optimizing network structures, enhancing transportation efficiency, and informing policy-making.

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Publication Details

Journal
Scientific Data
Published
2025-03-28
DOI
https://doi.org/10.1038/s41597-025-04894-0
Citations
3
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
6.53
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article

A Comprehensive Vector Dataset of Bus Networks Across China for the Year 2024

Heng Ding, Shiguang Wang, Zeyang Cheng, Rui Ma et al.
3 citations
Scientific Data
Human Mobility and Location-Based Analysis
6.53
article

A Comprehensive Vector Dataset of Bus Networks Across China for the Year 2024

Heng Ding, Shiguang Wang, Zeyang Cheng, Rui Ma, Jinyu He
article en
3 citations

Abstract

Urban public transportation systems facilitate traffic flow and promote sustainable urban development by offering convenient, economical, and environmentally friendly transit services. However, existing research often lacks large-scale bus network data, limiting the potential for comprehensive and in-depth analyses of urban transit systems' complexity and scope. Consequently, large-scale vector data on urban bus networks hold immense value. We designed a set of high-precision algorithms for generating bus network vector data based on electronic map APIs, which include steps such as coordinate transformation, network simplification, station projection, and topology generation. After cross-validation, a vector dataset containing bus stops, routes, and topology for 299 cities in China was generated and stored in Shapefile format (a widely used GIS file). The dataset offers valuable insights for studying network patterns in China's bus systems, supporting international comparative analyses of public transportation systems. Given that China operates the largest bus system globally, this dataset carries substantial academic and practical significance, providing data-driven insights for optimizing network structures, enhancing transportation efficiency, and informing policy-making.

Scientific DataVol. 12(1)
Hefei University of Technology (CN)
Openalex Percentile: Top 5%
Human Mobility and Location-Based Analysis
6.53
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