Research on Regional Spatial Structure Based on the Spatiotemporal Correlation Analysis of Population Migration: A Case Study of Hubei, China

Population migration is an important indicator for measuring the interactions and connections between cities. Analyzing the spatiotemporal distribution pattern of the migration flows between cities is highly important to understanding urban development relationships and regional structures. From a spatiotemporal perspective, we conduct STFlowLISA (Space-Time Flow Local Indicator of Spatial Association) spatiotemporal autocorrelation analysis using population migration data from Hubei Province from 2018 to 2023 and, on this basis, calculate the spatiotemporal hub index and identify spatiotemporal clusters. The research aims to reveal the regional spatial structure shaped by migration flows and compare it with that of existing town system planning to evaluate deviations and provide a decision-making basis for the regional synergistic development of Hubei Province. The key findings include: (1) the population migration flows between Wuhan and its surrounding cities mostly exhibit a spatiotemporal distribution pattern of HH (high-value agglomeration), whereas the long-distance migration flows between eastern and western Hubei mostly follow a pattern of LL (low-value agglomeration), and these urban connections show improvement after the epidemic; (2) the spatiotemporal hubs of Hubei Province demonstrate a “core-periphery” structure with Wuhan as the absolute core, while Xiangyang’s role as a subcenter does not meet planning expectations; and (3) urban spatiotemporal clusters are dense in the east and sparse in the west, with Enshi and Shiyan showing disconnection from the main network, which deviates from the planned polycentric spatial pattern. By examining the spatiotemporal autocorrelation of migration flows, this study enriches the empirical understanding of regional spatial structure in Hubei Province within the framework of classical spatial theory and highlights the necessity of incorporating dynamic flow analysis into regional planning and policy-making.