European Commission, Joint Research Centre, Via E. Fermi 2749, 21027, Ispra, Italy.
Institute of Geography, Slovak Academy of Sciences, Štefánikova 49, 814 73, Bratislava, Slovakia.
Nat Commun. 2020 Sep 15;11(1):4631. doi: 10.1038/s41467-020-18344-5.
The knowledge of the spatial and temporal distribution of human population is vital for the study of cities, disaster risk management or planning of infrastructure. However, information on the distribution of population is often based on place-of-residence statistics from official sources, thus ignoring the changing population densities resulting from human mobility. Existing assessments of spatio-temporal population are limited in their detail and geographical coverage, and the promising mobile-phone records are hindered by issues concerning availability and consistency. Here, we present a multi-layered dasymetric approach that combines official statistics with geospatial data from emerging sources to produce and validate a European Union-wide dataset of population grids taking into account intraday and monthly population variations at 1 km resolution. The results reproduce and systematically quantify known insights concerning the spatio-temporal population density structure of large European cities, whose daytime population we estimate to be, on average, 1.9 times higher than night time in city centers.
人口的时空分布知识对于城市研究、灾害风险管理或基础设施规划至关重要。然而，人口分布的信息通常基于官方来源的居住地点统计数据，因此忽略了由人类流动性导致的不断变化的人口密度。现有的时空人口评估在细节和地理覆盖范围上都受到限制，有前途的移动电话记录也受到可用性和一致性问题的阻碍。在这里，我们提出了一种多层次的分配方法，该方法将官方统计数据与新兴来源的地理空间数据相结合，以生成和验证考虑到日内和每月人口变化的 1 公里分辨率的整个欧盟人口网格数据集。该结果再现并系统地量化了关于大型欧洲城市时空人口密度结构的已知见解，我们估计这些城市中心的日间人口平均比夜间高 1.9 倍。
