Energy and Resources Group, University of California, Berkeley, Berkeley, California, United States of America.
Department of Environmental Health Sciences, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America.
PLoS One. 2022 Jul 14;17(7):e0270746. doi: 10.1371/journal.pone.0270746. eCollection 2022.
This paper introduces a series of high resolution (100-meter) population grids for eight different sociodemographic variables across the state of California using data from the 2020 census. These layers constitute the 'CA-POP' dataset, and were produced using dasymetric mapping methods to downscale census block populations using fine-scale residential tax parcel boundaries and Microsoft's remotely-sensed building footprint layer as ancillary datasets. In comparison to a number of existing gridded population products, CA-POP shows good concordance and offers a number of benefits, including more recent data vintage, higher resolution, more accurate building footprint data, and in some cases more sophisticated but parsimonious and transparent dasymetric mapping methodologies. A general accuracy assessment of the CA-POP dasymetric mapping methodology was conducted by producing a population grid that was constrained by population observations within block groups instead of blocks, enabling a comparison of this grid's population apportionment to block-level census values, yielding a median absolute relative error of approximately 30% for block group-to-block apportionment. However, the final CA-POP grids are constrained by higher-resolution census block-level observations, likely making them even more accurate than these block group-constrained grids over a given region, but for which error assessments of population disaggregation is not possible due to the absence of observational data at the sub-block scale. The CA-POP grids are freely available as GeoTIFF rasters online at github.com/njdepsky/CA-POP, for total population, Hispanic/Latinx population of any race, and non-Hispanic populations for the following groups: American Indian/Alaska Native, Asian, Black/African-American, Native Hawaiian and other Pacific Islander, White, other race or multiracial (two or more races) and residents under 18 years old (i.e. minors).
本文介绍了一系列针对加利福尼亚州 8 种不同社会人口变量的高分辨率（100 米）人口网格，这些数据来自 2020 年的人口普查。这些层构成了“CA-POP”数据集，是使用密度分配制图方法，根据精细尺度的住宅税包裹边界和微软的远程感应建筑物足迹层等辅助数据集，对普查块的人口进行降尺度处理而生成的。与一些现有的网格化人口产品相比，CA-POP 具有较好的一致性，并具有一些优势，包括更新的数据版本、更高的分辨率、更准确的建筑物足迹数据，以及在某些情况下更复杂但更简约和透明的密度分配制图方法。通过生成一个由块组内的人口观测值而不是块来约束的人口网格，对 CA-POP 密度分配制图方法进行了一般准确性评估，从而可以将此网格的人口分配与块级普查值进行比较，得出块组到块的分配的中位数绝对相对误差约为 30%。然而，最终的 CA-POP 网格受到更高分辨率的普查块级观测值的限制，在给定区域内，它们可能比这些块组约束的网格更准确，但由于缺乏子块级的观测数据，因此无法对人口分解的误差进行评估。CA-POP 网格可在 github.com/njdepsky/CA-POP 上在线获取 GeoTIFF 栅格形式，提供总人数、任何种族的西班牙裔/拉丁裔人口，以及以下群体的非西班牙裔人口：美洲印第安人/阿拉斯加原住民、亚洲人、黑人/非裔美国人、夏威夷原住民和其他太平洋岛民、白人、其他种族或多种族（两种或多种种族）以及 18 岁以下的居民（即未成年人）。
