Metropolitan fringe areas are transitional spaces where urban expansion, industrial relocation, residential spillover, transport infrastructure, and ecological recreation jointly reshape land-use functions. However, urban vitality research has mainly focused on central urban areas, leaving limited evidence on how activity intensity is organized in metropolitan fringe spaces. Taking the Chengdu Metropolitan Area, China, as a case, this study delineates metropolitan fringe areas using POI kernel density analysis and density–distance relationships, calibrated with impervious-surface and remote-sensing evidence, measures village-level relative activity intensity using Baidu heatmap data, and examines nonlinear associations between built-environment variables and urban vitality using LightGBM and SHAP. The results show that vitality across the delineated fringe does not form a uniform core–periphery gradient. Instead, high-vitality units are clustered around industrial parks, residential spillover zones, transport corridors, public-service nodes, and ecological recreation spaces. Population density, nighttime light, gross domestic product, building density, and commercial POI density are the main predictors in both weekday and weekend models. Several variables show nonlinear and saturation-like associations rather than simple linear effects. These findings suggest that higher predicted fringe vitality is more likely to occur where population concentration, development intensity, service provision, transport linkage, and socioeconomic activity coexist, rather than where densification occurs alone. The study extends urban vitality research to metropolitan fringe areas and provides evidence for differentiated land-use planning in urban-rural transition zones.

Long commuting times may constrain opportunities for exercise, but evidence remains limited on whether built-environment associations vary across area-level commuting-time burden. This cross-sectional spatial study analyzed 229,563 June 2024 Keep walking, running and cycling trajectories aggregated to 5802 500 m × 500 m grid cells in central Jinan, China. A within-mode, sample-relative activity index based on GPS-reconstructed distance and mean speed classified trajectories into low-, medium- and high-activity groups. Four theory-defined built-environment composites were examined using PPML models with distance to the urban-core reference, district fixed effects and 391 commuting-location clusters; primary models included 5012 grids. Green/recreation, street/public-transport accessibility and development intensity were positively associated with total and activity-specific trajectory counts in the primary models, whereas daily service provision was not independently associated. Continuous commuting time was not statistically associated with any outcome, and no built-environment dimension showed FDR-adjusted overall moderation. Alternative distance–speed weights did not alter the activity-specific conclusions. However, the green/recreation association was substantially attenuated after adjustment for the origin-based observed platform user base, while the street/transit association was sensitive to trajectory assignment and exposure specification. These findings support cautious interpretation of area-level platform-observed activity associations.