Urban development and population estimation in central Africa through remote sensing

摘要: In Central Africa, population data are not easily collected, and when available, always reliable. This situation regarding availability quality is due both to the lack of means local institutions for organising such collection, insecurity displacements that can prevent access remote areas. this context, sensing contribute enhance quality. Within GeoRisCA project (2012-2016), which aims at studying risk geo-hazards, two major urban sites located in East Democratic Republic Congo studied according their development current density: Bukavu/Cyangugu Goma/Gisenyi. Based on satellite imagery analyses, first objective our approach describe growth impact it has terms vulnerability specific geo-hazards (mass movements, seisms volcanic eruptions). order reach objective, Landsat SPOT images used study land-cover changes over a 30-year period, allowing also events region be evaluated (displacement refugees, destruction an eruption ). those rapidly growing cities, informal settlements constitute large part new neighbourhoods. Moreover, formal extensions may border or occur particular terrains, like lava flows increases classification difficulties. results OBIA pixel-based compared define most suitable approach. The second assess density cities Goma/Gisenyi by associating morphological neighbourhoods (using land-use, built-up density, structure ) sampled survey representative blocks. pattern city defined phase included neighbourhood support distinctions between types. output will identification efficient methodology describing its densely populated neighbourhood, highlight areas more vulnerable thus geo-hazards. Maps produced based these could become tool planning, as well prevention disaster management policies.