Comparison of Intercity Travel Network Structure during Daily Time and Holiday in China

Abstract

Intercity travel by residents promotes the regathering and dissemination of social and economic factors. Based on big data from Tencent’s location-based service, 346 cities above the prefecture level in China were chosen as study objects, with 2018 as the study time node. To construct the intercity residents’ travel network, complex network analysis and GIS spatial analysis methods were used. Furthermore, when analyzing the structural characteristics and spatial differences of Chinese residents’ intercity travel from different time perspectives (the whole year, daily, Spring Festival travel rush, and special holidays), Gephi network analysis tools and ArcGIS spatial analysis software were used. The following are the major findings: daily and the whole year intercity travel by Chinese residents, as well as intercity travel during special holidays and the Spring Festival, all exhibit the “diamond” structure, with Beijing, Shanghai, Guangzhou-Shenzhen, and Chengdu-Chongqing at the core. The distribution of lines in and around the “diamond” is large and concentrated from the perspective of the hierarchical nature of the residents’ intercity travel network. Significant increases in high-intensity population flow lines within the “diamond” can be seen during Spring Festival travel and holidays. The number of cities involved in the inflow line is significantly greater than that involved in the outflow line, as demonstrated by the number of residents in the first point of travel, indicating that there is a difference between the central cities flowing into and out of the network. The first flow of the central city is the most visible during the Spring Festival travel period. Most cities in the resident intercity travel network have relatively low degrees of centrality, closeness centrality, and betweenness centrality, and the number of cities with large values of the three is small, and they are concentrated in the apex and interior of the “diamond” structure.

Exploring the Impact of Localized COVID-19 Events on Intercity Mobility during the Normalized Prevention and Control Period in China

“…The distribution of routes within and around the “diamond” is large and concentrated. This is consistent with the results of previous studies [ 8 , 43 ]. In contrast, the overall size, intensity, and distance of intercity travel in China during the NEPC period ( Figure 1 b) have decreased significantly, but the overall “diamond” structure has not changed.…”

“…Intercity travel, which reflects the mass movement of people, has always been one of the key points in the study of human mobility. Abundant achievements have been made in the research of intercity travel, including the analysis of spatial and temporal patterns of intercity travel [ 6 , 7 , 8 ], flow prediction [ 9 , 10 ], influencing factors analysis [ 5 , 9 , 10 ], etc. In the aftermath of the COVID-19 pandemic outbreak, there emerged numerous articles exploring the relationship between the pandemic and human activities.…”

Validation of the Basic Supporting Role of Traffic Networks in Regional Factor Flow: A Case Study of Zhejiang Province

“…With improved access to data, the types of "flow" data have become more diverse, which promotes the diversification of research. Examples include research findings on passenger-flow networks using data on high-speed railway schedules [9][10][11], freight networks using data on logistics routes [12], inter-city-trip networks using data on human flow [13][14][15], and enterprise-association networks using data from corporate-headquarters branches [16][17][18]. Discussions of the interrelationships among different types of networks have also appeared in related studies in recent years [18][19][20][21].…”

Spatial Relationship of Inter-City Population Movement and Socio-Economic Determinants: A Case Study in China Using Multiscale Geographically Weighted Regression

“…As a medium for the dissemination of labor, capital, and information, inter-city population movement serves as a functional linkage between cities [5], highlighting the underlying socio-economic factors driving these flows. Consequently, the heterogeneity of socio-economic elements across Chinese cities has resulted in differentiated inter-city population movement, with a substantial influx of individuals moving towards economically developed coastal areas, city agglomerations, and provincial capitals located inland [14].…”