Detecting Informal Settlements from Ikonos Image Data Using Methods of Object Oriented Image Analysis – an Example from Cape Town (south Africa)

Detecting informal settlements might be one of the most challenging tasks within urban remote sensing. This phenomenon occurs mostly in developing countries. In order to carry out the urban planning and development tasks necessary to improve living conditions for the poorest world-wide, an adequate spatial data basis is needed (see Mason, O. S. & Fraser, C. S., 1998). This can only be obtained through the analysis of remote sensing data, which represents an additional challenge from a technical point of view. Formal settlements by definition are mapped sufficiently for most purposes. However, this does not hold for informal settlements. Due to their microstructure and instability of shape, the detection of these settlements is substantially more difficult. Hence, more sophisticated data and methods of image analysis are necessary, which ideally act as a spatial data basis for a further informal settlement management. While these methods are usually quite labour-intensive, one should nonetheless bear in mind cost-effectivity of the applied methods and tools. In the present article, it will be shown how eCognition can be used to detect and discriminate informal settlements from other land-use-forms by describing typical characteristics of colour, texture, shape and context. This software is completely objectoriented and uses a patented, multi-scale image segmentation approach. The generated segments act as image objects whose physical and contextual characteristics can be described by means of fuzzy logic. The article will show methods and strategies using eCognition to detect informal settlements from high resolution space-borne image data such as IKONOS. A final discussion of the results will be given.