Spatio-temporal effects of built environment on running activity based on a random forest approach in nanjing, China

Abstract

Running activity is closely related to the urban built environment in terms of mental and physical health, and this relationship can change as a result of spatio-temporal changes. Most studies, however, do not account for this and assume a linear relationship exists between the built environment and running activity. This study, therefore, collected running data spanning 2019-2022, studied spatial distribution of four-year running activity, established built environment indicators, used a random forest approach to investigate the non-linear relationship between them, and evaluated spatio-temporal changes in the relationships over time. The findings suggested that running activities are spatially clustered and the degree of clustering varies over time, and nonlinear relationships and threshold effects between the built environment and running activity can be found through the random forest algorithm and partial dependence plots. Urban park green space, greenway, and the normalized difference vegetation index had the most significant effects on running activity. The effects of population, buildings, streets, road intersections, and points of interest on running activity changed during the Coronavirus disease 2019 pandemic. In 2022, however, these effects were consistent with those during the pre-pandemic period. Our findings fill research gaps by using spatio-temporal analysis and a non-linear approach; they can also provide a reference for urban planners in building running-suitable and healthy cities.

Keywords: Built environment; Random forest; Relative importance score; Running activity; Spatio-temporal change.