Data file and availability statement.

The spatial patterns of population mobility serve as a critical indicator for urban network characterization, providing an essential foundation for resilience assessment. Based on the complex network theory, this study constructs urban networks using the Baidu Migration Big Data of the Jiangsu-Zhejiang-Shanghai region in 2023 to analyze the spatiotemporal dynamics of population flow. Through a research framework of “structure measurement-scenario simulation-resilience assessment,” the study systematically reveals the response mechanisms of urban networks. The static characteristics of network resilience in the normal scenario and the dynamic characteristics in the disruption scenario were analyzed. The results are as follows: (1) Population flow is dense in the central region and sparse in the north and south. Network clusters exhibit dual characteristics of “administrative boundary constraints” and “economic gravity dominance”, forming more easily among developed cities across provinces or adjacent cities within the same province. The overall connection intensity of the network during holidays is markedly higher than that in the daily period. However, daily contact between developed cities is more frequent than that during holidays, indicating strong intercity commuting and routine movement. (2) In the normal scenario, core cities possess prominent centrality, while the hierarchy of the network is less pronounced. The agglomeration among nodes is moderate but features evident asymmetric connections. The transmission efficiency is relatively high. (3) In the disruption scenario, both the network transmission efficiency and the path connectivity experience phased changes, and the impact of deliberate disturbances on resilience is more significant than that of random disturbances. A handful of cities with crucial influence constitute the core network. This research aims to reveal the resilience characteristics and response mechanisms of population flow networks, offering insights into regional spatial coordination and sustainable development.