Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China

Abstract

Due to constraints in data and technological approaches, there is a deficiency in the analysis of spatial patterns and formation mechanisms of large-scale destination tourist flows at the provincial level. This study leverages open GPS trajectory big data and employs grid units to meticulously characterize the spatial patterns and associated formation mechanisms of regional-scale tourist flows in Qinghai and Gansu Provinces. The findings reveal the following: (1) Regional tourist flows exhibit a distinct “point-axis-ring” agglomeration distribution pattern. (2) The “Gansu-Qinghai Tourist Grand Loop” has emerged as a predominant regional tourism corridor. Within this loop, there are smaller, high-density sub-loops centered on specific tourist attractions. (3) Ecology, service and scenic area are the three major influencing mechanisms for spatial differentiation of tourist flow in Gansu-Qinghai region. The findings can provide significant insights for the prioritization of regional tourism route marketing and planning, the configuration of tourism service facilities, etc.

Keywords

• GPS trajectory
• Big data
• Tourist flow
• Spatial network
• Gansu-Qinghai Region