Towards user-driven earth observation-based slum mapping

M. Owusu*, M. Kuffer, M. Belgiu, Tais Grippa, Moritz Lennert, Stefanos Georganos, Sabine Vanhuysse

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
98 Downloads (Pure)


Earth observation (EO) capabilities to produce up-to-date geographical information on slums over large areas supporting urban planning and evidence-based policymaking are largely acknowledged. Most EO studies typically use a data-driven approach without an understanding of end-user requirements. This study addresses this gap by aligning EO methods with societal needs and concerns using a user-driven approach in Accra, Ghana. By carrying out in-situ observations and slum experts interviews, we produced a user-driven slum map that meets potential users' expectations. To do so, we used a random forest classifier, SPOT 6 imagery, and ancillary geospatial data such as OpenStreetMap information. The overall classification accuracy for the user-driven approach reached 84%. The results show that the addition of local context-knowledge, end-user requirements, and geo-ethics, help to better contextualise and conceptualise slums. Our research demonstrates an approach of slum mapping that is reflective and open to societal needs and concerns.
Original languageEnglish
Article number101681
Pages (from-to)101681
Number of pages1
JournalComputers, environment and urban systems
Early online date20 Jul 2021
Publication statusPublished - 1 Sep 2021


  • Slums
  • Local context-knowledge
  • End-user requirement
  • Geo-ethics
  • Urban remote sensing
  • Geoinformation
  • Accra
  • UT-Hybrid-D


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