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Advanced Techniques in Mapping Urban Poverty: Analysis of Slums utilizing Remote Sensing
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This thesis aims to explore advanced geospatial techniques for slum identification and
mapping, focusing on two case studies: Between Nairobi and Rio de Janeiro. Employing
high resolution satellite imagery and Geographical Information System (GIS)
technologies, the study adopts the Modified generic slum ontology scale to measure off
urban poverty. Thus, six parameters were used to compare slum areas with the formal
settlements, including the slope of the territory, the distance from industrial facilities,
fractal dimension, roof density, the area of buildings, and the irregularity of roads’
networks. The method used in the paper combines the use of Remote Rensing, Generic
Sum Ontology Framework and Object-Oriented Image Analysis (OOA) to give an
appreciation of the form of slums. Comparing Nairobi slum and Rio slum, research shows
that there exist striking variations on topography, city expansion, and structure congestion.
Slope measurements also suggested that slums in both cities are most likely sited on steep
and risky slopes, which makes development of infrastructures even more challenging.
Ideas such as the fractal dimension and road irregularity indicated the clustered nature of
slum formation. The study concludes with a step forward in this field and substative
discussion to assist the urban planners to use these spatial findings while implementing the
slum upgrading interventions towards the realization of the sustainable development goal
11. 1.
Descrição
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
Palavras-chave
Remote sensing GIS Fractal Dimension Digital image processing Generic Slum Ontology Urban Planning Free, open-source software Nairobi Rio De Janeiro