Beyond the census: Satellite and tax data for ranking South African municipalities

This study comprehensively analyzes South Africa’s municipal rankings by employing unconventional data sources – specifically, satellite-derived and administrative tax data – to supplement traditional census counts. In light of recent controversies surrounding the accuracy of the 2022 Census data, we assessed the viability of alternative data sources in ensuring equitable and accurate municipal funding. We utilized data from South Africa’s 2022 Census, Oak Ridge National Laboratory’s LandScan 2022, Google Earth Engine’s nightlight database, the South African Revenue Service – National Treasury (SARS-NT) spatial tax panel, and the Regional Explorer database to calculate rank-size distributions and Spearman rank correlations across 213 municipalities. Results indicate exceptionally high concordance between census data and satellite-derived population estimates (Spearman’s ρ = 0.98), underscoring the robustness of satellite data in capturing demographic distributions. In addition, formal economic activity, as represented by SARS-NT establishment data, exhibits significant concentration, with metropolitan municipalities accounting for 67% of formal firms. Our findings also reveal that the population distribution among municipalities aligns closely with Zipf’s rank-size rule, with modest deviations indicating slight primacy in larger metropolitan areas. This analysis advocates for integrating satellite-derived growth factors into fiscal allocation models and establishing real-time economic monitoring using satellite night lights. These measures promise to enhance intergovernmental transfer responsiveness, equity, and accuracy, directly reinforcing sustainable urban development and governance that supports Sustainable Development Goal 11. The study further recommends annual recalibration of municipal population data using satellite-based adjustments to address funding disparities and mitigate migration-induced inequities in fiscal distribution.