Delineating urban agglomeration regions in China by network community scanning: Structures and policy implications

Document Type

Article

Publication Date

3-1-2025

Abstract

This study employs the network community scanning (NCS) method to analyze inter-city human flow network patterns using the most recent 2023 Baidu mobility data in China. Specifically, it uses the Community Multiresolution Overlap Scan (CMOS) technique to define regions comparable to the recently government designated urban agglomerations (UAs) and other administrative units (i.e., economic regions and provincial units) so that the delineated and targeted regions overlap most. The results reveal a larger spatial context for multiple UAs to interact as well as a centric structure to detect within each UA. By comparing designated UAs and the NCS-derived comparable regions, it largely validates the rationale of UAs. More in-depth examination reveals discrepancies on a finer scale. Based on community affiliation index (CAI) and PageRank centrality, the centric structure analysis of designated UAs identifies whether an UA is absent of any central city, led by a dominant center, or jointly anchored by multiple centers. The efficient network delineation algorithm supported by timely mining of big data enables policy makers to examine the hierarchical structure of cities in real time and make necessary adjustments.

Publication Source (Journal or Book title)

Cities

Number

683

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