Large-scale slum mapping in sub-Saharan Africa's major cities: Remote sensing and deep learning reveal strong slum growth in the urban periphery between 2016 and 2022

Abstract

Around half of sub-Saharan Africa's urban population lives in slums, yet data on the spatiotemporal development of slums remains scarce, impeding policies to alleviate urban poverty and inequality. We propose a solution to this problem by applying deep learning to open-access satellite imagery to map slums in 529 major cities across sub-Saharan Africa and track their spatiotemporal development. Our model produced 10m resolution ‘slum probability maps’ allowing timely and cost-effective tracking of slum growth. On this basis, we estimated that in 2022 the share of the urban population living in slums exceeded 50% in 274 cities, and in 84% of cities this share increased between 2016 and 2022, most severely in Middle and West Africa. Slum growth occurred primarily in the urban periphery, which tends to be missed in survey-based slum monitoring. • Applying deep learning to open-access satellite images for large-scale slum mapping. • Over 50 % slum dwellers in half of Africa's major cities in 2022. • Slum dweller share increased in most of Africa's major cities from 2016 to 2022. • Africa's slums are growing primarily in the urban periphery. • Survey-based slum tracking is likely to miss significant shares of slum dwellers.

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