Spatial pattern of population mobility among cities in China: Case study of the National Day plus Mid-Autumn Festival based on Tencent migration data

Abstract

Population migration, social check-in, vehicle navigation, and other spatial behavior big data have become vital carriers characterizing users' spatial behavior. “Tencent Migration” big data can real-timely, dynamically, completely and systematically record population flow routs using LBS device. Through gathering residents daily mobility among 299 cities in China during the period of “National Day–Mid-Autumn Festival” (NDMAF) vacation (from September 30 to October 8) in 2017 in “Tencent Migration” and defining three periods with “travel period, journey period, return period”, this paper is designed to analyze and explore the characteristics and spatial patterns of daily flow mobility cities from the perspective of population daily mobility distribution levels, flow distribution layers network aggregation, spatial patterns and characteristics of the complex structure of the flow network. Results show that “Tencent migration” big data clearly discovers the temporal-spatial pattern of population mobility in China during the period of NDMAF. The net inflow of population showed a diamond shaped with cross frame support in each period, the four nodes of the diamond contain Beijing, Shanghai, Guangzhou and Xi'an. Main mobility assembling centers are distributed in the urban agglomerations of Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta and Chengdu-Chongqing, and those centers have strong coherence with those urban hierarchies. Most cities are in a state of “relative equilibrium” in the population flow, and clear hierarchical structure and level distinction can be identified. Spatial patterns of population mobility present obvious core-periphery structures. The Dali-Hegang line exhibits a significant network of spatial differences in terms of boundary divisions. In this context, the spatial distribution of urban network could be summarized as “dense in the East and sparse in the West”, and the core linkages of urban network could be characterized as “parallel in the East and series in the West”. The whole network exhibits a typical “small world” network characteristic, which shows that China's urban population flow network has high connectivity and accessibility during the period of NDMAF. The network has a distinct “community” structure in the local area, including 2 national communities, 2 regional communities and 3 local-level communities.