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The use of very-high-resolution earth observation satellite data for multi-thematic urban mapping in sub-Saharan Africa: Applications in population, household wealth and epidemiological modeling

par Georganos, Stefanos
Président du jury Gilbert, Marius
Promoteur Wolff, Eléonore
Co-Promoteur Grippa, Taïs
Publication Non publié, 2021-01-18

Thèse de doctorat

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Résumé :

Sub-Saharan African (SSA) cities are some of the most rapid-growing regions inthe world. As estimated by the United Nations, more than 50% of the Africanpopulation will reside in cities by 2030 while in absolute numbers, its population willhave doubled - from 1.2 billion in 2015 to 2.5 billion by 2050. This ongoing shift hasdramatically affected the capacity of several SSA cities to provide essential servicesfor its residents, such as durable housing, employment and healthcare accessibility.On the contrary, the proliferation of slums, further marginalizing the urban poor hasbeen an undisputed observation of the last years. It is therefore profound, that effortsto improve the quality of life of urban dwellers are needed. A starting point to do so,it to provide relevant authorities, stakeholders and organizations with useful socioeconomic,demographic and health indicators of the urban dwellers. Nonetheless, Inlarge parts of SSA, this type of critical information is at best scarce and at worstnon-existent and certainly not suited for sophisticated intra-urban analyses.This thesis harnesses the strength of very-high-resolution (VHR) satellite remotesensing to provide multi-level (physical, socio-economic, demographic and epidemiological)representations of the urban surface in several major SSA cities. First, cuttingedge advances relevant to the classification of urban land cover are presented.Afterwards, an assessment and evaluation of the potential of VHR satellite imageryas input to population estimation, household wealth and malaria risk models atunprecedented resolutions is investigated. The conclusions of this work encouragethe systematic exploitation of VHR data to support evidence-based decision makingshaping the sustainable future of SSA cities.