Passenger and freight travel patterns: A cluster analysis based on urban networks

While research on population travel patterns and urban networks has been active, it has primarily focused on passenger travel, leaving freight travel relatively underexplored. This study addresses this gap by analyzing both passenger and freight travel patterns, network structures, and central areas. It uses origin-destination (OD) data, considering total travel volume by purpose and mode. The study applies regular equivalence and power centrality to examine differences in human and logistics flows across South Korea from an urban network theory perspective. The key findings are as follows. First, passenger travel, predominantly short-distance, exhibits lower density and intensity than freight travel. Freight travel, on the other hand, demonstrates strong density across short, medium, and long distances, with more travel routes concentrated around nodal regions. Second, passenger travel forms several polynucleated clusters, including short-distance movements. Conversely, freight travel forms a few extensive clusters that encompass medium and long-distance movements. Third, the spatial interaction of passenger travel is influenced by the OD distance, unlike freight travel. Interestingly, the distance between central areas of freight travel can be longer than that of passenger travel. This may stem from the strategic positioning of certain suburban areas as central areas to optimize logistics efficiency. This study emphasizes the importance of morphological and functional linkages between cities by identifying inter-regional differences in passenger and freight flows. It also proposes spatial planning strategies based on urban hierarchy.

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Publication Details

Journal
PLoS ONE
Published
2025-03-11
DOI
https://doi.org/10.1371/journal.pone.0318084
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Passenger and freight travel patterns: A cluster analysis based on urban networks

Soyeong Lee, Hee-Sun Joo
PLoS ONE
Human Mobility and Location-Based Analysis
article

Passenger and freight travel patterns: A cluster analysis based on urban networks

Soyeong Lee, Hee-Sun Joo
article en

Abstract

While research on population travel patterns and urban networks has been active, it has primarily focused on passenger travel, leaving freight travel relatively underexplored. This study addresses this gap by analyzing both passenger and freight travel patterns, network structures, and central areas. It uses origin-destination (OD) data, considering total travel volume by purpose and mode. The study applies regular equivalence and power centrality to examine differences in human and logistics flows across South Korea from an urban network theory perspective. The key findings are as follows. First, passenger travel, predominantly short-distance, exhibits lower density and intensity than freight travel. Freight travel, on the other hand, demonstrates strong density across short, medium, and long distances, with more travel routes concentrated around nodal regions. Second, passenger travel forms several polynucleated clusters, including short-distance movements. Conversely, freight travel forms a few extensive clusters that encompass medium and long-distance movements. Third, the spatial interaction of passenger travel is influenced by the OD distance, unlike freight travel. Interestingly, the distance between central areas of freight travel can be longer than that of passenger travel. This may stem from the strategic positioning of certain suburban areas as central areas to optimize logistics efficiency. This study emphasizes the importance of morphological and functional linkages between cities by identifying inter-regional differences in passenger and freight flows. It also proposes spatial planning strategies based on urban hierarchy.

PLoS ONEVol. 20(3)
Gyeongsang National University (KR)
National Research Foundation of Korea
Sustainable cities and communities
Openalex Percentile: Top 96%
Human Mobility and Location-Based Analysis
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