Visual Analysis of Shared Bicycle Data Based on User's Spatiotemporal Behavior Characteristics

With the continuous development of shared bicycles, large-scale spatiotemporal trajectory data has been generated and stored. Visual research and analysis of these data provide guidance and reference for bicycle scheduling, station planning, urban road planning. Moreover, what kind of visualization technology can efficiently mine the hidden information in data, which has attracted people's attention. Based on this research motivation, a visual analysis system of shared bicycle user's behavior was constructed, which started from time and space to construct spatiotemporal trajectory data and high-dimensional multivariate data visualization. Via the analysis of cycling routes and stations, the purpose is to use collaborative interaction between views to realize visual analysis of users' cycling activity patterns and influencing factors.