<p>Urban environments offer a wealth of opportunities for residents to respite from their hectic life. Outdoor running or jogging becomes increasingly popular of an option. Impacts of urban environments on outdoor running, despite some initial studies, remain underexplored. This study aims to establish an analytical framework that can holistically assess the urban environment on the healthy vitality of running. The proposed framework is applied to two modern Chinese cities, i.e., Guangzhou and Shenzhen. We construct three interpretable random forest models to explore the non-linear relationship between environmental variables and running intensity (RI) through analyzing the runners’ trajectories and integrating with multi-source urban big data (e.g., street view imagery, remote sensing, and socio-economic data) across the built, natural, and social dimensions, The findings uncover that road density has the greatest impact on RI, and social variables (e.g., population density and housing price) and natural variables (e.g., slope and humidity) all make notable impact on outdoor running. Despite these findings, the impact of environmental variables likely change across different regions due to disparate regional construction and micro-environments, and those specific impacts as well as optimal thresholds also alter. Therefore, construction of healthy cities should take the whole urban environment into account and adapt to local conditions. This study provides a comprehensive evaluation on the influencing variables of healthy vitality and guides sustainable urban planning for creating running-friendly cities.</p>