Journal of Geo-information Science ›› 2020, Vol. 22 ›› Issue (6): 1240-1253.doi: 10.12082/dqxxkx.2020.190686

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Research on Travel Pattern and Network Characteristics of Inter-city Travel in China's Urban Agglomeration during the National Day Week based on Tencent Migration Data

LI Tao1,2, WANG Jiaoe2,3,*(), HUANG Jie2   

  1. 1. Northwest Land and Resource Research Center, Shaanxi Normal University, Xi'an 710119, China
    2. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-11-13 Revised:2020-04-26 Online:2020-06-25 Published:2020-08-25
  • Contact: WANG Jiaoe
  • Supported by:
    National Natural Science Foundation of China(41501120);National Natural Science Foundation of China(41722103);The Fundamental Research Funds for the Central Universities, SNNU(18SZYB01);Young Elite Scientists Sponsorship Program by CAS(2019QNRC001)


Intercity travel is a time-dependent behavior, which has different spatial characteristics with different time constraints or during different time periods. The patterns of intercity travel and geographical spatial connections revealed by intercity travel could be different with time. However, intercity travel with varying travel time has been studied little so far, in particular for holiday travel. With the booming of holiday tourism, analyzing intercity travel during holidays is of great significance to uncover the spatial movement rules and travel patterns among urban agglomerations. In the era of big data, real-time records of population movement provide a possibility to examine the characteristics of intercity travel in detail. Hence, this paper explores the characteristics, patterns, and structure of intercity travel in 19 urban agglomerations of China during the National Day holiday period (October 1-7) in 2016. The intercity travel data derived from the Tencent Location Big Data and network analysis methods are employed to evaluate intercity travel patterns between urban agglomerations. Using the community detection method, we identify 24 city communities during the National Day holiday, and the directions of intercity travel in urban agglomerations are explored. Results show that intercity travel during this golden week has an obvious timing feature, which is observed as leave period, return period, and journey period receptively. There have formed three intercity travel patterns, namely, hub-and-spoke, polycentric, and monocentric patterns. Meanwhile, the features of intercity travel in the leave period and return period are similar to the Spring Festival, which is characterized by space-time symmetry of population flow. Intercity travel in main urban agglomerations presents a typical long-holiday travel feature, which is characterized by short- and medium- distance travel between core cities and neighboring peripheral cities. While the intercity travel in urban agglomerations in the central and west of China has a typical tidal feature. Based on the population movement records from the Tencent Location Platform, this study has investigated intercity travel features and travel patterns during the National Day holiday in three time periods mentioned above. In addition, our results can provide useful support for intercity traffic management, road resource optimization, and allocation plan in long holidays in China.

Key words: intercity travel, travel pattern, network structure, time dependent, Tencent Migration, big data, National Day holiday, urban agglomeration