Do we underestimate the global slum population?

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Abstract

According to UN-Habitat, around one billion people live in slum conditions, this number is reported for the SDG indicator 11.1.1 (the proportion of urban population living in slums, informal settlements or inadequate housing). However, this number comes with many uncertainties. For several countries, estimates are not available, while for other countries reported data might not reflect the real population living in slum conditions. In this paper, we use Dar es Salaam in Tanzania as a showcase on how a combination of data extracted from remote sensing combined with locally available sample data and non-official data (e.g., from NGOs) could allow quantifying the degree of uncertainty about city-level slum population estimates. For the city of Dar es Salaam, the estimates based on the census data indicate that around 3 million of its inhabitants are living in slum-like conditions, while using a combination of household surveys, settlement level estimates from Shack/Slum Dwellers International combined with rooftop outlines extracted from Unmanned Aerial Vehicle (UAV) images, the estimated slum population is around 5 million. This raises the question of how much on a global level do we underestimate the number of people living in slum conditions and shows the potential of remote sensing to shed some light on this neglected issue.

Original languageEnglish
Title of host publication2019 Joint Urban Remote Sensing Event, JURSE 2019
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Electronic)9781728100098
DOIs
Publication statusPublished - 1 May 2019
EventJoint Urban Remote Sensing Event, JURSE 2019 - Vannes, France
Duration: 22 May 201924 May 2019
http://jurse2019.org/

Publication series

Name2019 Joint Urban Remote Sensing Event, JURSE 2019

Conference

ConferenceJoint Urban Remote Sensing Event, JURSE 2019
Abbreviated titleJURSE 2019
CountryFrance
CityVannes
Period22/05/1924/05/19
Internet address

Keywords

  • dasymetric modelling
  • deprived areas
  • informal settlement
  • population estimation
  • SDG indicator
  • slums

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  • Cite this

    Kuffer, M., Persello, C., Pfeffer, K., Sliuzas, R., & Rao, V. (2019). Do we underestimate the global slum population? In 2019 Joint Urban Remote Sensing Event, JURSE 2019 (pp. 1-4). [8809066] (2019 Joint Urban Remote Sensing Event, JURSE 2019). IEEE. https://doi.org/10.1109/JURSE.2019.8809066