2020 Volume 8 Issue 3 Pages 101-121
Advanced technologies and big data have brought new visions and methods to urban planning research. Based on the Baidu heat map and POI data of two typical days (a weekend day and a workday) in 2018, this paper analyses the spatial and temporal aggregation patterns of crowds in the urban centre of Wuhan using ArcGIS. Aggregation patterns are defined by the intensity of population activities and the places where crowds gather. In terms of time, the daily change of population aggregation intensity is studied by counting the heat value of 24 moments captured throughout the day. The results show that on rest days, people prefer to travel around noon and in the afternoon, reaching the highest peak of the day around 15:00, while on workdays, residents' activities are affected by commuting, with obvious 'morning rush hours' and 'evening rush hours'. Firstly, the spatial correlation between the density of POI distribution and the degree of population aggregation has been studied by the spatial coupling relationship between the Baidu heat map and POI data. Secondly, the index of correlation between the aggregation of different POIs and population (ICPP) are mentioned to analyse the purposes and the degrees of aggregation during weekend and workday rush hours. Based on the ICPP, we analyse activities from three aspects: the different ICPPs between the workday and the weekend; the different ICPPs between the morning, afternoon and evening; and the different ICPPs among different POIs.