Associations between overhead-view and eye-level urban greenness and cycling behaviors

Cycling is one type of physical activities with documented health and environmental benefits. Little consensus has been reached about the impacts of urban greenness on cycling behavior because of the widely varying estimation techniques, especially at street scale. We objectively measured the urban greenness in two ways: overhead-view greenness by Normalized Difference Vegetation Index (NDVI) and eye-level street greenness by Google Street View (GSV) images. Multilevel logistic regression models were used to examine the association between urban greenness and the odds of cycling (versus not cycling) for 5701 Hong Kong participants after controlling activity-influencing built environment and individual-level covariates. We found the odds of cycling were positively associated with eye-level street greenness but not with overhead-view greenness across three buffer zones: 400 m, 800 m and 1600 m. In addition, the odds of cycling were negatively associated with population density, number of bus stops, and terrain slope, while positively associated with bike lane density. To build a cycling-friendly city, planners and designers might need to pay more attention to improve citizens' daily exposure to urban greenness, instead of traditional greenspace indices such as greenspace area or number of parks. The GSV technique is a novel and reliable method for measuring eye-level urban greenness with potential usage in further healthy city studies. •We used Google Street View images to measure the relationship between cycling behaviors and eye-level street greenery.•The results confirmed street greenery, but not NDVI, was positively associated with the odds of cycling.•Our method may be a novel, superior and reliable predictor for cycling behaviors than traditional green indices, e.g. NDVI.•Urban planners need to pay attention to improve citizens’ daily exposure to urban greenness, instead of green indices.