Analyzing rhythms of intercity mobility within and between mega-city regions: Evidence from China

Although a significant body of research on intercity mobility explores temporal dynamics, there are still gaps in our understanding of the rhythmic characteristics within and between mega-city regions (MCRs), partly due to challenges raised by the “curse of dimensionality” in time series big data. This paper attempts to unravel the rhythms of intercity mobility in terms of three interlocking characteristics: vibration, periodicity and predictability. China's daily intercity flows within and between MCRs over the course of one year are derived from Tencent big data. They are analyzed using time series methods, including permutation entropy and wavelet analysis. It is found that within a one-year timeframe, the flows within MCRs show weekly and monthly periodic patterns while the flows among MCRs have separated monthly periodic patterns in a part of the year. In addition, the flows within MCRs have a more predictable pattern than the flows between MCRs within a one-year timeframe. These results could provide valuable support for transportation and urban planning.