Spatial-temporal Dynamics of Population Aggregation during the Spring Festival based on Baidu Heat Map in Central Area of Chengdu City, China


  •  Yunjiao Zhou    

Abstract

The application of location-aware devices and location-based services enables big data to provide a convenient and efficient way to study the dynamics of urban population distribution. Based on the Baidu heat map data, the spatial-temporal population aggregation in the main urban areas of Chengdu City was explored in the context of the Spring Festival. The results suggested that population aggregation showed regular fluctuation within a day, consistent with the commuting activities. Also, population mobility showed difference before, during and after the festival; population density during the holiday was significantly lower than that on the other two working days, meanwhile the heat value on the working day before the festival was slightly higher than that after the festival. The conclusion showed that the Spring Festival affected the population distribution density. Chinese government’s emergent measures taken to suppress the nationwide spread of COVID_19 at early 2020 also had great influence on the low population aggregation during and after the Spring Festival, indicating the effectiveness of emergency control of human interactions. Better understanding of Spatial-temporal dynamics of population aggregation during the Spring Festival is of great value for optimizing the city expansion and structure planning.



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