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The Generic Slum Ontology: Can a Global Slum Repository be created?

机译:普通贫民窟本体论:可以创建全球贫民窟存储库吗?

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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.
机译:贫民窟约占世界城市人口的四分之一,在南半球的大多数城市中,大多数城市人口居住在这些地区。为了支持全球消除贫民窟和改造政策,例如SDG目标11(旨在通过确保城市区域和发展的包容性来减少贫民窟),需要有关全球南方各个城市贫民窟的数量和空间分布的一致的全球信息。我们探索了通用的贫民窟本体论(GSO)和可用的空间数据,以寻找用于全球贫民窟制图的可靠且可转移的指标。我们的分析的初步结果表明,图像中的建筑密度和道路特征等指标可能对描述贫民窟和非贫民窟建成区之间的差异很有用。总而言之,这项研究突出了GSO在全球贫民窟资源库开发中的机遇,同时也表明了对本地适应的需求,因此,将现实世界特征概念化为图像域特征的重要性也很重要。

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