Examining the influence of neighborhood and street-level built environment on fitness jogging in Chengdu, China: A massive GPS trajectory data analysis

Wei Yang, Jie Hu, Yong Liu and Wenbo Guo

Journal of Transport Geography, 2023, vol. 108, issue C

Abstract: Few studies have investigated the influences of the multilevel built environment (BE) factors on jogging, compared with walking or cycling. This study explored neighborhood and street-level BE factors' associations with fitness jogging via multi-source urban data. Empirical analysis of Chengdu, China showed the following: (1) BE factors, including sky view factor, bus stop density, presence of waterscapes, and geographic location significantly, impact jogging activity. (2) The significance and effect of BE factors vary across time. Jogging activities are more sensitive to BE on weekends than on weekdays. (3) Jogging trips are more closely related to BE factors in urban areas than in the suburbs. Jogging activities are mainly affected by the artificial environment in urban areas and the natural environment in suburban areas. Moreover, the effects of multiple BE factors become obvious as trip distance increases. These findings call for urban planning and infrastructure provision strategies to promote jogging activities.

Keywords: Fitness jogging activity; Trajectory big data; Built environment; Spatial regression; Street view images (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:108:y:2023:i:c:s0966692323000479

DOI: 10.1016/j.jtrangeo.2023.103575

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