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Slums are home to approximately one quarter of the world’s urban population, in most cities of the Global South the majority of the urban population lives in such areas. In support of global slum eradication and transformation policies, such as the SDG goal 11 which aims to reduce slums by ensuring inclusiveness of urban areas and developments, consistent global information about the amount and spatial distribution of slums across cities in the Global South is needed. We explore the generic slum ontology (GSO) and available spatial data to seek for robust and transferable indicators for global slum mapping. The initial results of our analysis demonstrate that indicators such as building density and road characteristics in an image are potentially useful to describe differences between slum and non-slum built-up areas. In conclusion, this study highlights the opportunities of the GSO for the development of a global slum repository but also show the need of local adaptations and hence, the importance of the conceptualization of real-world features into image domain features.
|Title of host publication||IEEE - Joint Urban Remote Sensing Event, 2019|
|Place of Publication||Vannes|
|Number of pages||4|
|Publication status||Published - Jun 2019|
|Event||Joint Urban Remote Sensing Event, JURSE 2019 - Vannes, France|
Duration: 22 May 2019 → 24 May 2019
|Conference||Joint Urban Remote Sensing Event, JURSE 2019|
|Abbreviated title||JURSE 2019|
|Period||22/05/19 → 24/05/19|
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