Ju Yang, Liang Ying, Kong Jinyu, Wang Xuelu, Wen Shicheng, Shang Huiyan, Wang Xize
School of Geography and Ocean Science, Nanjing University, Nanjing, China.
School of Architecture and Urban Planning, Nanjing University, Nanjing, China.
Sci Data. 2025 Jun 21;12(1):1058. doi: 10.1038/s41597-025-05401-1.
Gridded population datasets are instrumental for modeling the interactions between human and the environment at fine spatial scales. Many of these datasets are downscaled from source data of aggregated population counts by census units. Here, we introduce an Age-Stratified Population Estimation from the 2020 China Census by Township (ASPECT), estimating total population and population by age groups (0-14, 15-59, 60-64, ≥65 years old) at 100 m spatial resolution as of year 2020. ASPECT uses the updated source data from the most recent Census of year 2020, incorporating population counts and age structures from nearly all townships (n = 40,718) - the finest spatial unit for which the 2020 Census data are publicly available. Therefore, ASPECT likely provides improved accuracy in gridded population estimation when compared with datasets based on county-level data such as WorldPop. Furthermore, ASPECT presents greater spatial variations in the estimated population age structure than those from other existing datasets. These advantages of ASPECT allow for more accurate estimations on population exposure to environmental hazards and access to public services.
网格化人口数据集有助于在精细空间尺度上模拟人类与环境之间的相互作用。其中许多数据集是根据人口普查单位汇总的人口计数源数据进行降尺度处理得到的。在此，我们介绍了一种基于2020年中国乡镇人口普查的年龄分层人口估计（ASPECT）方法，该方法以2020年为时间节点，在100米空间分辨率下估计总人口和各年龄组（0-14岁、15-59岁、60-64岁、≥65岁）的人口数量。ASPECT使用了2020年最新人口普查的更新源数据，纳入了几乎所有乡镇（n = 40,718）的人口计数和年龄结构，这是2020年人口普查数据公开可用的最精细空间单元。因此，与基于县级数据（如WorldPop）的数据集相比，ASPECT在网格化人口估计中可能具有更高的准确性。此外，ASPECT在估计的人口年龄结构上呈现出比其他现有数据集更大的空间差异。ASPECT的这些优势使得对人口暴露于环境危害和获得公共服务的估计更加准确。
