Measuring the Contribution of Built-Settlement Data to Global Population Mapping
21 Pages Posted: 20 May 2020 Publication Status: Published
Top-down population modelling has gained applied prominence in public health, planning, and sustainability applications at the global scale. These top-down population modelling methods often rely on remote-sensing (RS) derived representation of the built-environment and settlements as key predictive covariates. While these RS-derived data, which are global in extent, have become more advanced and more available, gaps in spatial and temporal coverage remain. Here we have modelled built-settlement extents between 2000 and 2012 and demonstrate the applied utility and information provided by these annually modelled data for the application of annually modelling population across 172 countries. We demonstrate that the modelled built-settlement data are consistently the 2nd most important covariate in predicting population density, behind annual lights at night, across the globe and across the study period. Further, we demonstrate that this modelled built-settlement data often provides more information than current annually available RS-derived data and last observed built-settlement extents.
Keywords: urban, Population, growth model, built, settlement, Machine Learning, Meta-analysis
Suggested Citation: Suggested Citation