Trasberg Terje, Cheshire James
University College London, UK.
Urban Stud. 2023 Jun;60(8):1427-1447. doi: 10.1177/00420980211040409. Epub 2021 Aug 31.
We use data on human mobility obtained from mobile applications to explore the activity patterns in the neighbourhoods of Greater London as they emerged from the first wave of COVID-19 lockdown restrictions during summer 2020 and analyse how the lockdown guidelines have exposed the socio-spatial fragmentation between urban communities. The location data are spatially aggregated to 1 km grids and cross-checked against publicly available mobility metrics (e.g. Google COVID-19 Community Report, Apple Mobility Trends Report). They are then linked to geodemographic classifications to compare the average decline of activities in the areas with different sociodemographic characteristics. We found that the activities in the deprived areas dominated by minority groups declined less compared to the Greater London average, leaving those communities more exposed to the virus. Meanwhile, the activity levels declined more in affluent areas dominated by white-collar jobs. Furthermore, due to the closure of non-essential stores, activities declined more in premium shopping destinations and less in suburban high streets.
我们利用从移动应用程序获取的人类移动性数据,来探究大伦敦各社区在2020年夏季第一波新冠疫情封锁限制措施解除后的活动模式,并分析封锁指南如何揭示了城市社区之间的社会空间碎片化现象。位置数据在空间上被聚合到1公里的网格中,并与公开可用的移动性指标(如谷歌新冠疫情社区报告、苹果移动趋势报告)进行交叉核对。然后将这些数据与地理人口分类相联系,以比较不同社会人口特征地区活动的平均下降情况。我们发现,与大伦敦的平均水平相比,以少数群体为主的贫困地区的活动下降幅度较小,这使得这些社区更容易接触到病毒。与此同时,以白领工作为主的富裕地区的活动水平下降幅度更大。此外,由于非必要商店的关闭,高端购物目的地的活动下降幅度更大,而郊区商业街的活动下降幅度较小。