Understanding city dynamics based on public bicycle data: A case study in Hangzhou

Abstract

With the development of wireless communication and network technology, large amounts of public transportation data can be acquired and analyzed to discover the underlying city dynamics. In this paper, by using trip level data collected from Hangzhou public bicycle system(PBS), we visually analyze the city dynamics under different external conditions based on the heat map and conditional analysis method. According to the analysis results, we could not only find the city heart and understand people's travel purpose by cycling in different days, but also compare the changing of bicycle rental patterns and spatial distributions under different weather conditions and calendar properties in different time granularity.