Frontiers in public health · 2026
Environmental determinants of hiking, jogging, and cycling along the Beijing-Tianjin-Hebei grand canal: implications for health promotion.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Cai Zihan, Yu Yi, Lu Ming
Аннотация
INTRODUCTION: The Grand Canal in the Beijing-Tianjin-Hebei offers abundant ecological resources and socio-economic value that can support physical activity and social interaction, yet its use remains largely spontaneous and underutilized for regional health promotion.
METHODS: This study quantifies how canal-adjacent space promotes hiking, jogging, and cycling, identifies correlating features and spatial heterogeneity, and proposes optimization recommendations. Using participant movement trajectories, we combine XGBoost with multiscale geographically weighted regression to assess factor importance and spatial nonlinearity. K-Means clustering classifies canal-adjacent areas into ecology (52.9%), service (29.5%), living (11.7%), and mixed (5.9%) types; Natural Breaks delineates advantage zones for physical activity.
RESULTS: Promotion indices derived from factor weight coefficients quantifies conversion efficiency across spatial types. Illumination intensity and population density correlate strongly with three activity types. Hiking is mainly driven by slope gradient, accessibility to fitness facilities, and NDVI; jogging correlates with office complex, canopy height, and distance to bus station; cycling depends mostly on natural features.
DISCUSSION: Effects are generally nonlinear and spatially heterogeneous, centering on the Beijing-Tianjin segment with decreasing influence toward the periphery. In addition, comparing the four spatial types, mixed spaces show the highest conversion efficiency. We propose targeted development strategies and a progressive spatial enhancement model to strengthen sports functions.
METHODS: This study quantifies how canal-adjacent space promotes hiking, jogging, and cycling, identifies correlating features and spatial heterogeneity, and proposes optimization recommendations. Using participant movement trajectories, we combine XGBoost with multiscale geographically weighted regression to assess factor importance and spatial nonlinearity. K-Means clustering classifies canal-adjacent areas into ecology (52.9%), service (29.5%), living (11.7%), and mixed (5.9%) types; Natural Breaks delineates advantage zones for physical activity.
RESULTS: Promotion indices derived from factor weight coefficients quantifies conversion efficiency across spatial types. Illumination intensity and population density correlate strongly with three activity types. Hiking is mainly driven by slope gradient, accessibility to fitness facilities, and NDVI; jogging correlates with office complex, canopy height, and distance to bus station; cycling depends mostly on natural features.
DISCUSSION: Effects are generally nonlinear and spatially heterogeneous, centering on the Beijing-Tianjin segment with decreasing influence toward the periphery. In addition, comparing the four spatial types, mixed spaces show the highest conversion efficiency. We propose targeted development strategies and a progressive spatial enhancement model to strengthen sports functions.