Characterizing intra-urban population migration networks: a case study of Shenzhen, China

Zhongyu Lai , Yueshan Li , Tao He , Xintao Liu

Computational Urban Science ›› 2025, Vol. 5 ›› Issue (1)

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Computational Urban Science ›› 2025, Vol. 5 ›› Issue (1) DOI: 10.1007/s43762-025-00207-8
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Characterizing intra-urban population migration networks: a case study of Shenzhen, China

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Abstract

Intra-urban migration plays a crucial role in shaping urban structure and socio-economic dynamics. Most existing studies rely on small-scale survey data or have a coarse spatial resolution, making it difficult to conduct detailed network analysis at the urban scale to fully understand the complexity and dynamics of migration patterns. To address the gap, this study conducted a subdistrict-level fine-grained network analysis, involving more than 800,000 relocation data with detailed demographic and housing information at subdistrict levels in Shenzhen in 2015, to explore the overall relocation patterns and the relocation differences among different groups. The findings reveal that short-distance relocations dominate, with major hubs serving as central points of population flow in the study area (e.g., Gongming and Shajing areas). The relocation patterns also indicate specific pathways guiding movement between city areas. Moreover, demographic factors such as marital status, education level, and age significantly influence relocation behaviour. For instance, elderly individuals move infrequently, but when they do, they often relocate over longer distances. Men tend to migrate to diverse areas, while women prefer similar ones. Highly educated individuals move longer distances, typically within economic core areas. Overall, our study provides new perspectives for understanding the complex mechanisms of intra-urban population migration.

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Intra-urban migration / Complex networks analysis / Relocation patterns / Demographic factors

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Zhongyu Lai,Yueshan Li,Tao He,Xintao Liu. Characterizing intra-urban population migration networks: a case study of Shenzhen, China. Computational Urban Science, 2025, 5(1): DOI:10.1007/s43762-025-00207-8

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Research Institute for Land and Space (RILS), The Hong Kong Polytechnic University(CDL1)

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