Detecting informal settlements from QuickBird data in Rio de Janeiro using an object based approach
Informal settlements behave very dynamical over space and time and the number of people living in such housing areas is growing worldwide. The reasons for this dynamical behavior are manifold and are not matter of this article. Nevertheless, informal sett
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P. Hofmann1, J. Strobl1, T. Blaschke1, H. Kux2 1
Centre for Geoinformatics, Salzburg University, Austria, [email protected], [email protected], [email protected]
2
Divisão de Sensoriamento Remoto, INPE, Brazil [email protected]
KEYWORDS: Urban remote sensing, ontologies, transferability ABSTRACT: Informal settlements behave very dynamical over space and time and the number of people living in such housing areas is growing worldwide. The reasons for this dynamical behavior are manifold and are not matter of this article. Nevertheless, informal settlements represent a status quo of housing and living conditions which is from a humanitarian point of view in the most cases below acceptable levels. Therefore, reliable spatial information about informal settlements is vital for any actions of improvement of these living conditions. Since remote sensing data is a well suited data source for mapping and monitoring we demonstrate a methodology to detect informal settlements (favelas) from QuickBird data using an object-based approach. On the one hand we therefore use experiences and adapt them which were already made by Hofmann, P. (2001) regarding the image segmentation of an IKONOS scene of Cape Town. On the other hand we resort to a general ontology of informal settlements which we then transfer to a fuzzy-logic rule base which acts as basic classifier of the generated segments. This basic rule base is than extended in a way that features of segregation given by the ontology (namely neighbor-
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P. Hofmann, J. Strobl, T. Blaschke, H. Kux
hood) are applied to the extraction method as an iterative process (i.e. a knowledge based region growing). Finally, we assess the results of the simple and iterative method by comparing them with the results of a manual mapping.
1 Introduction Informal settlements are usually a phenomenon which mostly occurs in developing and newly industrializing countries. Although different definitions of informal settlement do exist, slum, favella, squatter settlement or shanty town are commonly used synonyms for this special type of settlement. Sub-standard sanitary situations and high crime rates are only a few of attributes which go aside with the phenomenon informal settlement. Nevertheless, the UN (UNSTAT 2005) define informal settlements as: „1. areas where groups of housing units have been constructed on land that the occupants have no legal claim to, or occupy illegally; 2. unplanned settlements and areas where housing is not in compliance with current planning and building regulations (unauthorized housing).“ Both definitions are obviously emphasizing the illegal character of informal settlements. In contrast, the definition of Mason and Fraser (1998) takes the environmental, socio-economic and living conditions more into account. They describe informal settlements as: “... dense settlements comprising communities housed in selfconstructed shelters under conditions of informal or traditional land tenure ... . They are a common feature of developing countr
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