Abstract
Low- and middle-income country cities face unprecedented urbanization and growth in slums. Gridded population data (e.g., ~100 × 100 m) derived from demographic and spatial data are a promising source of population estimates, but face limitations in slums due to the dynamic nature of this population as well as modelling assumptions. In this study, we compared field-referenced boundaries and population counts from Slum Dwellers International in Lagos (Nigeria), Port Harcourt (Nigeria), and Nairobi (Kenya) with nine gridded population datasets to assess their statistical accuracy in slums. We found that all gridded population estimates vastly underestimated population in slums (RMSE: 4958 to 14,422, Bias: −2853 to −7638), with the most accurate dataset (HRSL) estimating just 39 per cent of slum residents. Using a modelled map of all slums in Lagos to compare gridded population datasets in terms of SDG 11.1.1 (percent of population living in deprived areas), all gridded population datasets estimated this indicator at just 1–3 per cent compared to 56 per cent using UN-Habitat’s approach. We outline steps that might improve that accuracy of each gridded population dataset in deprived urban areas. While gridded population estimates are not yet sufficiently accurate to estimate SDG 11.1.1, we are optimistic that some could be used in the future following updates to their modelling approaches.
Highlights
We address the question: “How accurate are gridded population datasets in slums and informal settlements in three low- and middle-income countries (LMICs) cities?”, and assess the strengths and weaknesses of each dataset for measuring Sustainable Development Goals (SDGs) 11.1.1, the percent of population living in slums, informal settlements, and other deprived areas [26]
We compare nine multi-country gridded population datasets to Know Your City (KYC) Campaign population estimates reported by slum community profiling teams and to a survey-based estimate of the percent of population living in slums in Lagos
This study is among the first to assess the accuracy of gridded population datasets in deprived urban areas in LMICs
Summary
Over the 30 years, 90 per cent of global population growth is expected to take place in African and Asian cities alone, with a majority of those people added in slums, informal settlements, and other deprived urban areas [1]. While the rates of population growth in many low- and middle-income countries (LMICs) are similar to the rates of highincome countries (HIC) a century ago [2], the absolute numbers of people being added to LMIC cities today are unprecedented in human history [3]. Kinshasa (D.R. Congo) is expected to add 757,000 people per year, Lagos (Nigeria) 623,000 per year, Cairo (Egypt) 462,000 per year, and Dar es Salaam (Tanzania) 409,000 people per year [1]
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