A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Towards user-driven earth observation-based slum mapping
Abstract 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.
Highlights The user-driven approach provides policy-relevant geoinformation on slums. Integrating local knowledge and user requirements is crucial for slum mapping Geo-ethics ensure ethical data production and sharing Assessment of uncertain areas improve the credibility of the map.
Towards user-driven earth observation-based slum mapping
Abstract 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.
Highlights The user-driven approach provides policy-relevant geoinformation on slums. Integrating local knowledge and user requirements is crucial for slum mapping Geo-ethics ensure ethical data production and sharing Assessment of uncertain areas improve the credibility of the map.
Towards user-driven earth observation-based slum mapping
Owusu, Maxwell (author) / Kuffer, Monika (author) / Belgiu, Mariana (author) / Grippa, Tais (author) / Lennert, Moritz (author) / Georganos, Stefanos (author) / Vanhuysse, Sabine (author)
2021-06-28
Article (Journal)
Electronic Resource
English
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