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In order to reduce climate-related health issues in Sub-Saharan cities, a better understanding of the spatial and temporal processes affecting urban climates is required. In this context, this paper mobilizes the potential of urban climate modelling and remote sensing to improve the understanding of urban health risk variations in Sub-Saharan Africa. The combination of Stewart and Oke's (2012) universal classification of Local Climate Zones with very high resolution satellite imagery is explored for the parameterization of a simple urban canopy model (TERRA_URB) over two cities: Kampala (Uganda) and Dakar (Senegal). Key challenges, such as data scarcity and performing analyses on multi spatio-temporal scales are emphasized. Applications for a better understanding of links between urban climates and intra-urban health issues in highly dynamic urban environments are illustrated and discussed taking intra-urban malaria risk as an example.