Does Intercity Transportation Accessibility Matter? Its Effects on Regional Network Centrality in South Korea DOI Creative Commons
Sangwan Lee,

Jeongbae Jeon,

Kuk Cho

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 873 - 873

Published: April 16, 2025

This study investigates the relationship between intercity transportation accessibility and network centrality across South Korea by integrating Global Positioning System (GPS)-based mobility data with graph-theoretic measures, including degree, PageRank, local clustering coefficient, harmonic, Katz, information centrality. Employing both statistical modeling machine learning techniques, this analysis uncovers key structural patterns interaction effects within national network. The findings yield several important insights. First, Seoul Metropolitan Area emerges as dominant hub, Busan, Daegu, Daejeon functioning secondary centers, reflecting a polycentric urban configuration. Second, intermediary transfer hubs—despite having lower direct connectivity—substantially enhance overall efficiency interregional mobility. Third, accessibility, particularly in relation to regional transit highway infrastructure, exhibits significant association measures strong feature importance, identifying these modes primary determinants of spatial connectivity. Fourth, impact on is characterized nonlinear relationships threshold effects. By elucidating complex interplay infrastructure dynamics, contributes more comprehensive understanding connectivity offers policy-relevant insights for future planning.

Language: Английский

Does Intercity Transportation Accessibility Matter? Its Effects on Regional Network Centrality in South Korea DOI Creative Commons
Sangwan Lee,

Jeongbae Jeon,

Kuk Cho

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 873 - 873

Published: April 16, 2025

This study investigates the relationship between intercity transportation accessibility and network centrality across South Korea by integrating Global Positioning System (GPS)-based mobility data with graph-theoretic measures, including degree, PageRank, local clustering coefficient, harmonic, Katz, information centrality. Employing both statistical modeling machine learning techniques, this analysis uncovers key structural patterns interaction effects within national network. The findings yield several important insights. First, Seoul Metropolitan Area emerges as dominant hub, Busan, Daegu, Daejeon functioning secondary centers, reflecting a polycentric urban configuration. Second, intermediary transfer hubs—despite having lower direct connectivity—substantially enhance overall efficiency interregional mobility. Third, accessibility, particularly in relation to regional transit highway infrastructure, exhibits significant association measures strong feature importance, identifying these modes primary determinants of spatial connectivity. Fourth, impact on is characterized nonlinear relationships threshold effects. By elucidating complex interplay infrastructure dynamics, contributes more comprehensive understanding connectivity offers policy-relevant insights for future planning.

Language: Английский

Citations

0