Effects of urban park environment on recreational jogging activity based on trajectory data: A case of Chongqing, China

Abstract

Existing studies have seldom used large-scale trajectory data to analyze jogging activities in urban parks. Most of them have relied on traditional questionnaires and on-site interviews. Therefore, this study aims to uncover the characteristics and the potential influencing factors of jogging activities based on trajectory data recorded by a mobile app, using the case of Chongqing city. The results show that urban parks with high jogging flow are mainly distributed within the inner ring road of Chongqing, whereas urban parks with low jogging flow are newly built outside the inner ring road. The volume of jogging flow in urban parks in the spring and summer is higher than that of autumn and winter, and the volume on weekends is higher than that of weekdays. The peaks of jogging in urban parks vary across space and over time, leading to different spatiotemporal patterns. Urban parks along the subcenters, riversides, and airport corridors have morning (6–7 a.m.) and evening peaks (7–8 p.m.). Urban parks in the newly urbanized areas and industrial zones have evening peaks. The regression models show that walking loops and waterscapes have positive effects on jogging flow. The landscape shape index of urban parks and the distance to the city center negatively affect the jogging flow. Finally, the study indicates the possibility of using large-scale trajectory data to analyze jogging activities, which is helpful for urban park planners and managers to improve the frequency of jogging activity.