University of Twente Student Theses


Spatio-temporal slum mapping at citywide scale using high-resolution images

Owusu, Maxwell (2020) Spatio-temporal slum mapping at citywide scale using high-resolution images.

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Abstract:Rapid urbanisation in low-and middle-income countries has led to the proliferation of slums, with over 60% of the urban population living in deprived areas. Whiles remote sensing promise a sustainable source of information on slums, methods for citywide slum maps remains uncertain, and only few studies have focused on the spatio-temporal dynamics of slums. Moreover, the remote sensing community does not sufficiently understand the spatial information required of end-users. This study presents a processing chain for spatio-temporal slum mapping at a citywide scale using low-cost SPOT 6 image using Accra, Ghana as a case study. The processing chain relies on free and open software for geospatial (FOSS4G) solutions. Our research comprises of three parts: understanding the spatial information requirements of end-users, understanding ethical concerns of slum maps, citywide land-use mapping at street-block level, with the focus on slums, and change detection and analysis of uncertainties. We found out that the required spatial information and its level of details vary depending on the purpose of the institution. Interviewed experts agreed to make slum information publicly available. However, they raised geo-ethical issues that map producers need to address. Using the random forest (RF) classifier, land-use maps achieved high overall accuracy of over 80%. We applied class probability membership obtained from RF to identity uncertain street-blocks and further investigated the causes of uncertainties on grounds. The study identified three main causes including similar morphological characteristics of slums and old towns, areas with slum-like appearance due to unplanned and uncontrolled extension and slum areas which have been regularised. Post-classification change detection was applied to analyse spatio-temporal dynamics between 2013 and 2017 at the street-block level. we revealed that land-use change is stable is Accra with over 90% of the area remaining unchanged. Slums appeared on vacant lands or in kiosk estates whereas slums in floodable zones disappeared. Finally, we exploited the trajectory error metrics to assess the accuracy of change detection. Change detection accuracy using trajectory error metrics improve from 53% to 67% when uncertain street-blocks were removed. The proposed framework offers a way to map slums at a citywide scale with high accuracy to support pro-poor initiatives and produced the needed information required by end-users.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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