Abstract

The worldwide coronavirus disease 2019 (COVID-19) pandemic and the associated social distancing measures have produced alterations in park visits of individuals, as well as their park-based physical activity (e.g. running exercise). Although studies on the influence of the COVID-19 pandemic on changes in running activity patterns are becoming an emerging focus, less is known about how these changes are related to the environmental attributes of parks before and after the pandemic, the knowledge of which is essential to planning green infrastructure that better supports physical activities. Therefore, we employed a volunteered geographic information approach to investigate the runnability of park trails in Shenzhen, utilizing self-tracking routes from Strava, in order to uncover the associations between trail characteristics and park features with the running intensity before and after the pandemic. Multilevel regression model analyses revealed that trail network connectivity was the only environmental attribute indicating consistent and positive associations with running intensity. Blue space density was positively correlated with running intensity in urban parks but indicated no significant association in forest parks before the pandemic. In the pre-pandemic era, population density was positively related to running intensity in urban and forest parks. However, after the pandemic, the associations between running behaviours and population density remained positive in forest parks but turned insignificant in urban parks. The outbreak of the pandemic also altered the influence of other park features (e.g. park shape and trail density) on running intensity. The evidence-based knowledge provides planners with significant insights into pandemic-resilient park planning for the post-COVID era.

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