Analysing sub-standard areas using high resolution remote (VHR) sensing imagery

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Abstract

Urban planners and managers in developing countries often lack information on sub-standard areas. Base data mostly refer to relatively large and heterogeneous areas such as census or administrative wards, which are not necessarily a relevant geographical unit for representing and analysing deprivations. Moreover sub-standard areas are diverse, ranging from unrecognized slum areas (often in the proximity of hazardous areas) to regularized areas with poor basic services, and information on this diversity is difficult to capture. Sub-standard areas in Indian cities are typical examples of that diversity. In Mumbai, sub-standard areas range from unrecognized slum pockets to large regularized sub-standard areas.
This paper explores the usage of the latest generation of very high (spatial and spectral) resolution satellite images using 8-Band images of WorldView-2 to analyse spatial characteristics of sub-standard areas. The research illustrates how VHR imagery helps in rapidly extracting spatial information on sub-standard areas as well as provides a better understanding of their morphological characteristics (e.g. built-up density, greenness and shape). For this study an East-West cross-section of Mumbai (India) was selected, which is strongly dominated by a variety of sub-standard areas. The research employed image segmentation to extract building footprints and used texture and spatial metrics to analyse physical characteristics of sub-standard areas, combined with purposely-collected ground-truth information. The results show the capacity of this methodology for characterizing the diversity of sub-standard areas in Mumbai, providing strategic information for urban management.
Original languageEnglish
Title of host publicationProceedings of the 14th N-AERUS/GISDECO Conference, 12-14 September 2013, Enschede, Netherlands
Place of PublicationEnschede
Number of pages15
Publication statusPublished - 2013

Keywords

  • METIS-299328

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