Using satellite images and computer vision to study the effects of spatial apartheid in South Africa
dc.contributor.author | Sefala, Raesetje Bonjo | |
dc.date.accessioned | 2022-02-14T09:52:42Z | |
dc.date.available | 2022-02-14T09:52:42Z | |
dc.date.issued | 2020 | |
dc.description | A dissertation submitted in ful lfilment of the requirements for the degree of Master of Science to the Faculty of Science, University of the Witwatersrand, 2020 | en_ZA |
dc.description.abstract | Removing many of the legacies of Apartheid, a former policy of political and economic discrimination against non-European groups in South Africa, is a primary concern for the country. Aerial images of residential areas show the clear legacy of spatial apartheid, with completely segregated neighbourhoods of townships next to gated wealthy neighbourhoods, a phenomena which has largely remained una ected by the ending of apartheid. This research uses computer vision to analyse 698; 544 satellite images of 9 provinces in South Africa, taking the rst steps toward examining the evolution of spatial apartheid. To achieve this goal, we rst introduce a new dataset consisting of polygons demarcating land use, geographically labelled coordinates of all buildings in South Africa, and high resolution satellite imagery covering the entire country from 2006-2017. Using this dataset, we trained a UNet based semantic segmentation model to detect and classify clusters of buildings for 12 types of classes: Township, Suburb, Industrial area, Commercial land, Informal area, Farm, Collective living Quarters, Village, Smallholdings and Background. We classify these neighbourhoods with an accuracy of 57:45% and a Cohen's Kappa value of 0:4326, giving us the potential to investigate areas a ected by the Group Areas Act which enforced spatial apartheid/segregation. | en_ZA |
dc.description.librarian | TL (2022) | en_ZA |
dc.faculty | Faculty of Science | en_ZA |
dc.identifier.uri | https://hdl.handle.net/10539/32742 | |
dc.language.iso | en | en_ZA |
dc.title | Using satellite images and computer vision to study the effects of spatial apartheid in South Africa | en_ZA |
dc.type | Thesis | en_ZA |
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