Effects of urban park environment on recreational jogging activity based on trajectory data: A case of Chongqing, China
Effects of urban park environment on recreational jogging activity based on trajectory data: A case of Chongqing, China
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基于轨迹数据的城市公园环境对休闲慢跑活动的影响：以中国重庆市为例
DOI：
10.1016/j.ufug.2021.127443
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发表时间：
2022-01-01
影响因子：
6.4
通讯作者：
Luo, Chang
中科院分区：
文献类型：
--
作者：
Liu, Yong;Hu, Jie;Luo, Chang
现有的研究很少使用大规模的轨迹数据来分析城市公园中的慢跑活动。他们中的大多数人都依赖于传统的问卷调查和现场访谈。因此，本研究以重庆市为例，基于移动的应用程序记录的轨迹数据，揭示慢跑活动的特征及其潜在影响因素。结果表明，重庆市高慢跑流量的城市公园主要分布在内环线以内，而低慢跑流量的城市公园主要分布在内环线以外。城市公园的慢跑流量在春、夏季高于秋、冬季，周末高于工作日。城市公园内的慢跑高峰在空间和时间上各不相同，导致不同的时空模式。城市公园沿着副中心，河边和机场走廊有早上（6-7点）及傍晚高峰时段（晚上七时至八时）。新城区和工业区的城市公园有晚高峰。回归模型表明，步行环路和水景对慢跑流有积极的影响。城市公园的景观形状指数和距市中心的距离对慢跑流有负向影响。最后，本研究指出利用大规模轨迹数据分析慢跑活动的可能性，有助于城市公园规划者和管理者提高慢跑活动的频率。
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.