Using Local Climate Zones in Sub-Saharan Africa to tackle urban health issues

Oscar Brousse, Stefanos Georganos, Matthias Demuzere, Sabine Vanhuysse, Hendrik Wouters, Eléonore Wolff, Catherine Linard, Nicole P.M. van Lipzig, Sébastien Dujardin

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)227-242
Number of pages16
JournalUrban Climate
Volume27
DOIs
Publication statusPublished - 1 Mar 2019

Funding

The authors would especially like to thank our colleagues from the University of Maine, namely, Benoit Parmentier, Marco Millones and Daniel Casey for their comments and review on the paper; and our colleague from the Vrije Universiteit Brussel and the ETH Zurich, Wim Thiery for his valuable help for running the regional climate model. Moreover, we would particularly like to express our gratitudes to both the WUDAPT team and community, and to the COSMO-CLM community for their support and insights in engaging this study over Sub-Saharan Africa. We also acknowledge the CLM community for developing the COSMO-CLM model, and for providing the model code. This work was supported by the Remote sensing for Epidemiology in African CiTies (REACT: http://react.ulb.be /) project, funded by the STEREO-III program of the Belgian Science Policy (BELSPO, SR/00/337). Part of the work described in this paper has received funding from the Belgian Science Policy Office , Belgium through its Science for a Sustainable Development Programme under contract BR/143/A2/CORDEX .be. The authors would especially like to thank our colleagues from the University of Maine, namely, Benoit Parmentier, Marco Millones and Daniel Casey for their comments and review on the paper; and our colleague from the Vrije Universiteit Brussel and the ETH Zurich, Wim Thiery for his valuable help for running the regional climate model. Moreover, we would particularly like to express our gratitudes to both the WUDAPT team and community, and to the COSMO-CLM community for their support and insights in engaging this study over Sub-Saharan Africa. We also acknowledge the CLM community for developing the COSMO-CLM model, and for providing the model code. This work was supported by the Remote sensing for Epidemiology in African CiTies (REACT: http://react.ulb.be/) project, funded by the STEREO-III program of the Belgian Science Policy (BELSPO, SR/00/337). Part of the work described in this paper has received funding from the Belgian Science Policy Office, Belgium through its Science for a Sustainable Development Programme under contract BR/143/A2/CORDEX.be.

FundersFunder number
Remote sensing for Epidemiology in African CiTies
Belgian Federal Science Policy OfficeSR/00/337, BR/143/A2/CORDEX
Vrije Universiteit Brussel

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