Using household counts as ancillary information for areal interpolation of population: Comparing formal and informal, online data sources

Abstract

Fine-scale population estimates are needed to support both public and private planning. Previous areal interpolation research has used various types and sources of data as ancillary information to guide and constrain the disaggregation from (usually) larger source zones to (usually) smaller target zones. Many new forms of open and free to access geo-located data are available, and as yet little research has evaluated the use of these data in areal interpolation. This study evaluates the effectiveness of household data as ancillary information from two sources: formal census household counts and informal data on residential (house) sales from commercial websites, applied to 2 case studies with different contexts - Leeds in UK and Qingdao in China. The proposed Household Proportion method uses household counts as ancillary information for areal interpolation of population. It is compared with other interpolation and the results show that HP method yields significantly better results than other interpolation approaches using ancillary data, with lower errors. This research also demonstrates that such data support the application of a suite of interpolation methods that make fewer assumptions about underlying spatial processes. The need to examine issues of representativeness and data coverage are identified and discussed, but the study demonstrates the opportunities for including freely available geo-located data to inform geographic analyses.