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In contrast to the last century, where more people used to live in rural areas, at present, more than half of the world's population lives in urban settlements. Hence, the 21st century is the century of the cities and of urbanization. The rapid urbanization process experienced by the majority of developing countries during the last few decades has resulted in fundamental changes to the environment and to the social structure. In most of the megacities that have grown to unprecedented size, the pace of urbanization has far exceeded the growth of necessary infrastructure and services. In order to carry out the urban planning and development tasks necessary to improve the living conditions for the poorest world-wide, a detailed spatial data basis is required. Due to the high dynamics of megacities, traditional methods such as statistical analyses or fieldwork are limited to capture the urban process. Remote sensing provides the opportunity to monitor spatial patterns of urban structures with high spatial and temporal resolution. The present study investigates the potential to use very high-resolution (VHR) remote sensing data to identify urban structures and dynamics within Delhi, India. The paper presents a semi-automated, object-oriented classification approach which allows for the identification of informal settlements within the urban area. In order to provide indicators to identify socio-economic structures and their dynamics, the image classification results are embedded in an integrative analysis concept. Information on population and water related parameters are derived. This is understood to be a first step to the development of indicators which will help to identify and understand the different shapes, actors, and processes in megacities.