The unseen population: Do we underestimate slum dwellers in cities of the Global South?

• Published in: Habitat international 2024-06, Vol.148, p.103056, Article 103056
• Main Authors: Breuer, Julius H.P., Friesen, John, Taubenböck, Hannes, Wurm, Michael, Pelz, Peter F.
• Format: Article
• Language: English
• Subjects: Earth-observation; Slum population; Uniform approach; Validation
• ISSN: 0197-3975; 1873-5428
• DOI: 10.1016/j.habitatint.2024.103056

The Sustainable development goals (SDG) aim for reducing poverty (SDG 1) and to upgrade all slums (SDG 11). The first indicator in SDG 11 describes the proportion of the urban population residing in slums. However, the currently available data is based on national estimates that follow globally varying methodologies and concepts. In this paper, a uniform approach is implemented to obtain slum population estimates in eight different cities from three continents. The approach relies on earth observation datasets on the spatial extent of the slums and one of the most accepted gridded population dataset: WorldPop. The results shed light on the distribution of population in slums around the world. Nevertheless, the question of the accuracy of these population numbers arises. Therefore, a broad range of literature data containing population counts is gathered for the cities investigated, for varying years and for different spatial scales. The literature data is compared to results obtained by the presented approach. The comparison yields a plausibility assessment for different cities, indicating varying levels of deviation. We find in all cities a clear bias in estimating the slum population - mostly underestimations -, even though some cities reveal a significantly better fit to the data. In conclusion, this study provides a methodology to systematically assess the accuracy of globally available datasets in the context of slums and thereby to highlight the large uncertainties which can empirically be observed. [Display omitted] •Definition of a uniform approach to estimate slum population.•Obtaining slum population estimates for eight cities in the Global South.•Plausibility assessment of population counts using a broad range of literature sources.•Results show significant underestimations of slums worldwide.