After experiencing many years of shrinking in bike mode share, the birth of dockless bike has incurred a large-scale bike renaissance since 2016. However, the quick expansion of dockless bikeshare is coincident with the serious oversupply of bikes and chaos of parking on the streets. Predicting the right level of dockless bike use is essential to maintain the order of the road space. This study aims to control the number of dockless bikes in each neighborhood. With data obtained from a smartphone app, MoBike, this study examines factors associated with dockless bikeshare. A generalized additive mixed model is applied to investigate associations between dockless bike trip density and various factors. The results are: (1) floor area ratio, which represents density, is positively associated with dockless bike trip density; (2) percentages of residential, industrial and green spaces, and degrees of mixed land use, are positively related to dockless bike trip density; (3) densities of primary and secondary roads are positively related to dockless bike trip density, while the density of intersections is negatively associated with dockless bike trip density; (4) females and children are less likely to ride dockless bikes; (5) dockless bikes are more often used during peak hours, on sunny or cloudy days, and on weekdays. To promote dockless bike use, the right level supply for different weather, time and location conditions should be identified, encouraging dense urban development in establishing a friendly biking environment, and improving street connectivity to reduce the impedance of biking in intersection dense areas.