Modern Social Science Research

Big data on population mobility provides a more precise basis for urban resource allocation. By dynamically monitoring migration patterns across different temporal and spatial scales, this approach reveals key indicators such as changes in permanent resident demographics, commuting patterns, and functional area activity levels, thereby identifying imbalances in resource distribution. Through multi-source data integration and analytical models, population trends can be aligned with demands for public service provision, industrial layout, and transportation capacity, enabling quantitative evaluation of resource optimization and regulatory pathways. This study establishes a data-driven framework for optimizing resource allocation, using population mobility as the core variable to provide scientific support for refined urban governance and policy optimization.

Population mobility big data; Urban resource allocation; Spatio-temporal analysis; Data-driven; Urban governance