A fine-grained characterization of polycentric structures is key to resolving the inconsistencies in performance evaluation. However, existing research is hampered by two major limitations: an overreliance on aggregate indicators and the absence of cross-scale modeling. To address this, we propose a “static structure-dynamic interaction-multiscale correlation” multifractal framework to fine-grainedly model the spatial organization of polycentric structures. Using Beijing as a case study and synthesizing POI and taxi trajectory data, we conduct a multiscale analysis of residential, employment, leisure, and shopping centers. The results show that: (1) Statically, various functional centers exhibit significant multifractal characteristics with distinct structural differentiation: residential centers (singularity exponent 1.71/fractal dimension 1.54) form an extensively distributed and balanced spatial substrate. Employment centers (1.56/1.41) and leisure centers (1.56/1.39) constitute an urban skeleton characterized by both agglomeration and hierarchy. While commercial centers (1.09/0.78) display hub features marked by high local concentration yet global sparsity. (2) Dynamically, the correlation dimensions for three travel purposes increase progressively (employment < shopping < leisure), which respectively reflect ordered, semi-elastic, and elastic flow patterns. (3) The coupling of static and dynamic features indicates that the functional urban polycentric structure is a self-organizing multifractal system. The multifractal approach provides analytical tools to transcend the binary “monocentric vs. polycentric” debate, enabling a fine-grained characterization of urban polycentric structures and thereby laying the groundwork for performance assessment and structural optimization.
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