Abstract
Since its democratic dispensation in 1994, the South African government enacted a number of legislative and policy interventions aimed at availing equal housing opportunities to the previously marginalized citizens. Mismanagement and unreliable reporting has been widely reported in publicly funded housing programmes which necessitated the government to audit and monitor housing development projects in municipalities using more robust and independent methodologies. The objective of this study was therefore to test and demonstrate the effectiveness of high spatial resolution satellite imagery in validating the presence of government funded houses using an object-oriented classification technique that applies a Canny edge detection filter. The results of this study demonstrate that object-orientated classification applied on pan-sharpened SPOT 6 satellite imagery can be used to conduct a reliable inventory and validate the number of houses. The application of the multi-resolution segmentation and Canny edge detection filtering technique proved to an effective means of mapping individual houses as shown by the high detection accuracy of 99% and quality percentage of 96%.
Highlights
Provision of state-subsidized housing to low income and marginalized citizens has longstanding been a key priority area of most governments worldwide (Abbott, 2002; Huchzermeyer, 2003; Kenna, 2005)
Canny edge detection algorithm applied on pan-sharpened SPOT 6 image was successful in detecting and distinguishing structural edges of different objects in the study area, as shown in Figure 3 a. and b
The Canny edge detection results show that houses have stronger edges compared to other land use objects, stronger edges were observed in areas where houses have a size bigger than 40m2 than in areas where houses have smaller sizes
Summary
Provision of state-subsidized housing to low income and marginalized citizens has longstanding been a key priority area of most governments worldwide (Abbott, 2002; Huchzermeyer, 2003; Kenna, 2005). The number of government subsidised houses built under these programmes are usually estimated and inconsistent (Tissington, et al, 2013). This creates a need to explore other ways of gathering information on the number of houses built at different projects areas. Information of the number of houses built is required to support planning of services such as electrification, water, and sanitation and health
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