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.
CITATION STYLE
Owusu, M., Kuffer, M., Belgiu, M., Grippa, T., Lennert, M., Georganos, S., & Vanhuysse, S. (2021). Towards user-driven earth observation-based slum mapping. Computers, Environment and Urban Systems, 89. https://doi.org/10.1016/j.compenvurbsys.2021.101681
Mendeley helps you to discover research relevant for your work.