Integrating variable importance and spatial heterogeneity to reveal the environmental effects on outdoor jogging

Outdoor jogging is increasingly recognized as a crucial component of urban active transport strategies aimed at improving public health. Despite growing research on the influence of both natural and built environmental factors on outdoor jogging, less is known about the relative importance of these factors. Moreover, the spatial heterogeneity effects of environmental factors remain unclear. Failing to consider these varying effects regarding impact intensity and spatial scale results in inefficient planning policies aimed at promoting active transport. This study addresses these gaps by analyzing crowdsourced jogging trajectory data in Shenzhen using a computational framework that combines Random Forest Variable Importance (RF-VI) and Multi-Scale Geographically Weighted Regression (MGWR). The analysis identifies hierarchical environmental effects and the varying impacts of twelve key determinants across different spatial scales. Results reveal that natural environmental factors are most contributing to outdoor jogging, while density-related built environment factors contribute the least. Additionally, environmental effects vary in scale, direction, and intensity, with seven variables exerting global impacts and five showing localized effects. Notably, the central and suburban areas of Shenzhen display considerable spatial heterogeneity in environmental influences. The findings inform the importance of integrating green infrastructure, mitigating over-dense urban development, and enhancing pedestrian-accessible road networks to promote outdoor jogging. These insights advocate for context-sensitive urban planning that balances natural and built environments to to foster healthier mobility.