As an important means of shared micro-mobility, shared bicycles have become a crucial component of urban transportation in China. The impact of the built environment on bicycling has been widely acknowledged. However, can streetscape perceptions influence bicycle-sharing volume (BSV) and supplement the built environment? We first obtained millions of pieces of shared-cycling data from the Shenzhen Open Data Platform and carried out geographical quantification of BSV. As for streetscape, we improved the classification of subjective streetscape perception based on street view images using the k-means clustering algorithm and conducted predictions using XGBoost. Through the application of different regression models, we unveiled the nonlinear spatial interdependencies between BSV and streetscape perceptions as a complement to the built environment. Our findings indicate that greenery, vivid street-front facades, and diverse street facilities can promote BSV. Targeted strategies are proposed for different districts. For instance, urban planners can provide incentives for high-income groups in central urban areas to adopt active travel, and increase the supply of shared bicycles in suburban areas with high building density, particularly in industrial urban villages. As a supplement to the long-term planning recommendations derived from the macro-built environment analysis, an in-depth spatial perception quantitative assessment proffers a human-centric, flexible blueprint for urban street design.
