Since the 1980s, rapid population growth and urbanization have become issues in big cities like Greater Cairo (GC). As a consequence of explosive growth, the living conditions of Cairo Metropolis deteriorate. Development trends of the last twenty years have increased general wealth and modernization, this sets out how GC megacity is creating an increased demand for land combined with environmental degradation. Planning a sustainable development of mega cities requires understanding of physical change of the main environmental drivers. However, this talk will be concerned with monitoring and analysis of dynamic environment changes to capture and refine the urban patterns in Greater Cairo Metropolis on the basis of pixel-based and object-based classifications. Satellite images (TM, ETM+, & Spot) of different dates and resolutions, and ground truth data collected from available maps, field observation, and personal experience were used to execute the image segmentation analysis to reveal urban patterns and expansions. By using Erdas Imagine, and eCognition Developer software, land use/land cover image classifications were constructed, which detect regimes and trends in land changes. Two main types of urban patterns could be detected (passing from centre to periphery). The first one is informal and the second one is formal building. The informal type mainly comprises slums and urban encroachment on arable land. The formal one mostly consists of new cities and legal houses. Moreover, a rate of land cover changes in Greater Cairo during the last three decades could be described as a rapid progression. In contrast, the combination between field observations and classification analyses showed that the high urban densities based on classification of satellite images does not reflect the real densities of population in urban areas in Greater Cairo.
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