Estimating changes in urban land and urban population using refined areal interpolation techniques

Abstract

Abstract:The analysis of changes in urban land and population is important because the majority of future population growth will take place in urban areas. U.S. Census historically classifies urban land using population density and various land-use criteria. This study analyzes the reliability of census-defined urban lands for delineating the spatial distribution of urban population and estimating its changes over time. To overcome the problem of incompatible enumeration units between censuses, regular areal interpolation methods including Areal Weighting (AW) and Tar-get Density Weighting (TDW), with and without spatial refinement, are implemented. The goal in this study is to estimate urban population in Massachusetts in 1990 and 2000 (source zones), within tract boundaries of the 2010 census (target zones), respectively, to create a consistent time series of comparable urban population estimates from 1990 to 2010. Spatial refinement is done using ancillary variables such as census-defined urban areas, the National Land Cover Database (NLCD) and the Global Human Settlement Layer (GHSL) as well as different combi-nations of them. The study results suggest that census-defined urban areas alone are not necessarily the most meaningful delineation of urban land. Instead, it appears that alternative combinations of the above-mentioned ancillary variables can better depict the spatial distribution of urban land, and thus make it possible to reduce the estimation error in transferring the urban population from source zones to target zones when running spatially-refined temporal areal interpolation.

Data-enriched interpolation for temporally consistent population compositions

“…Refinement using census-defined urban areas in 1990, 2000 and 2010 does not generally reduce the selected error measures at the tract-level in comparison to the unrefined TDW (although it reduces mean percent error and mean absolute percent error for 1990-2010 substantially, which may indicate that it leads to less biased estimates, and is more effective for sparsely-populated target tracts and the longer time period), as indicated by Tables 4 and 5. This suggests that the underlying statistical surface of urban population is not well represented by these areas, justifying the need for their further dasymetric refinement (Zoraghein and Leyk 2018b). This observation may be due to the dichotomy between the two concepts of urban population and urban land.…”

“…The U.S. Census Bureau uses various criteria based on population, population density, identification of designated places, land-use and road segments, among others, to identify urban lands, which are delineated by layers of Urbanized Areas (UAs) and Urban Clusters (UCs) (Department of Commerce 2011; U.S. Census Bureau 2011). One well-known problem in using these layers is the change in the underlying definition of what and who is urban (Zoraghein and Leyk 2018b). Thus, in addition to the temporal incompatibility in small-area enumeration units, the concepts of urban lands and consequently urban population change over time.…”

“…Census-defined urban areas of Massachusetts in 1990Massachusetts in , 2000Massachusetts in , and 2010 were available and accessed from the NHGIS portal. Figure 3 shows these areas similar to Zoraghein and Leyk (2018b) with an improvement upon their depiction in 1990 by aggregating urban census blocks. The goal of this urban analysis part is two-fold.…”