High-resolution gridded estimates of population sociodemographics from the 2020 census in California.

ABSTRACT: 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 accura

SUBMITTER: Depsky NJ 

PROVIDER: S-EPMC9282657 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature