Table 1.
Census variables represented as CA-POP grids.
Fig 1.
Data sources used for the population grid creation process.
Examples are shown in in urban (top row) and rural (bottom row) settings. The 2020 census blocks represent the source zones of population and the parcel and building footprint data the ancillary data comprising the target population zones. (Satellite base-imagery source: USGS (NAIP) from The National Map).
Fig 2.
CA-POP’s dasymetric mapping method applied to a single census block.
Example shown is just north of Modesto, CA. Panel (a) shows the block boundary; (b) shows the ancillary residential parcel and building footprint boundaries; (c) shows the polygon boundaries used as the final target zones to assign the block’s population values, retaining the small residential parcel polygons and building footprint polygons within large residential parcels; (d) shows the 100m-resolution grid produced from population apportioned to the final target zones. (Satellite base imagery source: USGS (NAIP) from The National Map).
Fig 3.
Process workflow illustrating the identification of population target zones.
Dasymetric mapping process using the residential parcel and building footprint ancillary datasets within each census block and producing the final statewide grids for each population variable considered.
Fig 4.
CA-POP compared to the GPW and LS 1km resolution datasets.
Examples are shown for the Fresno area, CA. (Satellite base imagery source: USGS (NAIP) from The National Map).
Table 2.
Description of gridded datasets assessed.
GPW, WPC, WPUC and LS datasets all currently use 2010 census blocks as their source zones, which will likely be updated to 2020 census blocks in subsequent grids.
Fig 5.
Examples are shown for four demographic population variables at three different locations in California. (Satellite base imagery source: USGS (NAIP) from The National Map, Ocean boundary layer source: Natural Earth).
Table 3.
Summary error statistics of block group-constrained CA-POP grid.
Fig 6.
Pixel-wise differences between the CA-POP and 2020 SocScape total population grids.
SocScape’s 2020 total population grid was converted to population density, aggregated from 30m to 100m resolution using an average resampling approach and then re-converted to units of people per cell prior to differencing with CA-POP’s total population grid. Blue areas represent regions where CA-POP pixel values are greater than SocScape and red areas are those where SocScape is greater.
Fig 7.
Comparison of CA-POP with the unconstrained and constrained WorldPop grids.
Example shown for three locations in California. The first two rows represent populated areas and the third row represents largely unpopulated, open space. Over-apportionment of population across open space is seen in the unconstrained WorldPop grid and under-apportionment to buildings footprints detected by Microsoft (yellow area) in residential parcels is evident in the constrained WorldPop grid, as compared to CA-POP. (Satellite base imagery source: USGS (NAIP) from The National Map).