Spatiotemporal patterns and influencing factors in intercity travel within urban agglomerations

The investigation of spatiotemporal characteristics and patterns in intercity travel within urban agglomerations constitutes a pivotal component of urban transportation planning. However, the vast spatial expanse of urban agglomerations and the high costs associated with traditional surveys pose challenges in gathering comprehensive data that reflect intercity travel dynamics accurately. This study harnesses mobile signaling data and applies an enhanced Nonnegative Matrix Factorization (NMF) technique to uncover spatiotemporal travel patterns within the Yangtze River Delta urban agglomeration. The analysis identifies three distinct spatiotemporal travel patterns: leisure and business dual-driven travel (LBT), outbound tourism and family visits (OTV), and return trips related to tourism and family visits (RTV). In addition, the Quadratic Assignment Procedure (QAP) model traditionally utilized in social network analysis is employed to examine the factors influencing these travel patterns. The findings indicate that macroeconomic factors, spatial proximity and travel convenience uniformly influence all of the identified patterns, whereas factors related to Work-life balance and tourism and leisure exhibit varying degrees of significance across the patterns. The results further demonstrate that the critical influencing factors are aligned closely with the spatiotemporal distribution characteristics of each pattern, corroborating the efficacy of the proposed methodology in mining and analyzing spatiotemporal travel patterns.