Exploring Usage Patterns and Station Functions Based on Public Bicycle Data

As an important part of public transportation, the public bicycle system (PBS) has a great impact on improving the operation efficiency of urban transportation. To understand the spatial-temporal pattern and station function of PBS, this paper takes four areas in Ningbo, Zhejiang Province as an example during June 2017. We analyze the temporal pattern and use kernel density analysis to show the spatial pattern on the ArcGIS, then combine the method of time statistics and spatial hotspot extraction to explore station function. Matching the time statistics classifying and space hotspot extraction novelly, the results show that these stations are divided into four categories, which are residential station, commercial and office station, transportation stations, and leisure stations respectively, each type of station presents different spatial-temporal characteristics. Finally, this research has direct implications for understanding the operating state of PBS, it provide a scientific scheme for real-time scheduling of public bicycles.