Assessing the impact of COVID-19 on residents’ activities using baidu heat map data: from the lockdown era to the post-pandemic era

The COVID-19 pandemic has had a profound impact on individual human behaviour, making it a prominent research topic in recent years. However, most studies have focused on mobility, with limited attention given to changes in residents’ activities patterns. Furthermore, changes in these patterns at a finer spatiotemporal scale remain understudied. To fill this gap, we analysed and compared changes in residents’ activities across different streets and time slots from three perspectives – human activity intensity (HAI), population distribution, and daily activity patterns – using high-spatiotemporal-resolution Baidu heat map data. First, we tracked daily variations in HAI for each street across different time slots from the lockdown period to the post-pandemic era. On this basis, we calculated the changes in HAI and population distribution and inferred daily activity patterns. Our results revealed that HAI trends were similar across all streets, but relative changes varied across streets and different time slots. Moreover, the pattern of population distribution changed, with a shift from the central area to the surrounding regions. Additionally, daily activities transitioned from leisure and work activities to residential activities, with more pronounced changes in the forenoon and afternoon slots. These findings provide scientific evidence for guiding targeted urban management.