Constructing a time-varying network to observe the spatiotemporal evolution characteristics of intra-city migration

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Studying the long-term migration network within cities effectively reveals changes in urban spatial structures. This paper focuses on intra-city migration activities, introducing a method for dynamic network construction and analysis based on spatiotemporal data, offering a new perspective for examining the dynamic characteristics of residential migration within cities and their relationship to urban development. Migration behaviors are aggregated at the community level in the form of migration flows, and a time-varying network model of migration flows is constructed. Community detection and dynamic evolution analyses are conducted to uncover migration behavior characteristics. Using Shenzhen, a megacity in China, as a case study, a migration network spanning six consecutive years (2018–2023) was constructed using mobile phone signaling data. Our findings reveal that the gravitational pull of communities in the northern and eastern sub-center areas has increased. The dynamic evolution of community structures is closely related to the city's polycentric structure. Smaller network communities are more susceptible to changes, while strengthened regional connections have led to community mergers. The time-varying migration network proposed in this study provides an effective method for observing the development patterns of urban spatial structures from a mesoscopic perspective by tracking and analyzing migration flow patterns between different areas within a city.