Before revision:  As estimating the overall loss and the effectiveness of preventive measures in China is a complex task, we try to reveal the behavior change of people over time & space in order to infer the impact on daily life of and overall economy. Spatiotemporal behavior patterns can be reflected by share bike usage because great majority of Chinese urban residents use share bikes to connect public transports and both ends of travel. Taking records of Bike Sharing Systems (BSSs) in Beijing, this paper characterizes not only temporal behavior patterns of share bike users: during ordinary days, holidays and the pandemic, but also spatial behavior patterns: around malls, metros, normal communities and infected communities, etc.
After revision:  As estimating the overall loss and the effectiveness of preventive measures in China is a complex task, we try to reveal the behavior change of people over time & space within big cities. Although share bikes are playing an important role as data sources in data mining, they could be of help but are rarely reported in pandemic-related researches. Based on the share bike records in Beijing, this paper characterizes not only temporal behavior patterns of share bike users: during ordinary days, holidays and the pandemic, but also spatial behavior patterns: around malls, metros, normal communities and infected communities, etc.