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Most existing studies on public transit network (PTN) rely on either small-scale passenger flow data or small PTN, and only traditional network parameters are used to calculate the correlation coefficient. In this work, the real smart card data (SCD) (when passenger tap in and tap out a station) of over eight million users is used as a proxy of passenger flow to dynamically explore and evaluate the structure of large-scale PTNs with tens of thousands of stations in Beijing, China. Three types of large-scale PTNs are generated, and the overall network structure of PTNs are examined and found to follow heavy-tailed distributions (mostly power law). Further, three traditional centrality measures (i.e. degree, betweenness and closeness) are adopted and modified to dynamically explore the relationship between PTNs and passenger flow. Our findings show that, the modified centrality measures outperform the traditional centrality measures in estimating passenger flow. [ABSTRACT FROM AUTHOR]

Urban agglomeration is an important strategy used to promote economic development and urbanization in China. Understanding the structure of urban agglomeration is therefore essential for policy‐makers and planners. In this study, the Beijing–Tianjin–Hebei urban agglomeration (BTHUG) is explored through a proposed spatial network analytical framework and a large mobile phone data set (over 20 million users). We first construct a weight‐directed spatial interaction network based on an origin–destination matrix derived from the data set. Several network metrics (i.e., degree, strength, the rich‐club coefficient, and the assortativity coefficient) and three selected community detection algorithms (i.e., Infomap, Louvain, and Regionalization) are applied and compared to reveal the structure of the BTHUG. A four‐level hierarchical structure is defined and observed: one global center, two local centers, major cities that have low mobility flow but strong linkages with the three centers, and peripheral cities that have low mobility flow and weak linkages with the three centers. In particular, the results imply that the spatial structure of the BTHUG is over‐dependent on the global center (i.e., Beijing and northern Langfang). Further, ignoring spatial interaction patterns in top‐down administrative planning for urban agglomeration may lead to ineffective integrated development. The implications for BTHUG planning are discussed. [ABSTRACT FROM AUTHOR]