Extraction of low cost houses from a high spatial resolution satellite imagery using Canny edge detection filter

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 be an effective means of mapping individual houses as shown by the high detection accuracy of 99% and quality percentage of 96%.

Keywords: Houses, Remote Sensing, SPOT 6, Canny edge detection, Multi-resolution Segmentation, Object-Oriented Classification