Understanding heterogeneity in metropolitan India: The added value of remote sensing data for analyzing sub-standard residential areas |
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| Authors: | Isa Baud Monika Kuffer Karin Pfeffer Richard Sliuzas Sadasivam Karuppannan |
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| Institution: | 1. University of Amsterdam, Department of Geography, Planning and International Development Studies, Nieuwe Prinsengracht 130, 1018 VZ Amsterdam, The Netherlands;2. Urban and Regional Planning and Geo-Information Management, ITC, PO Box 6, 7500 AA Enschede, The Netherlands;3. School of Natural and Built Environments, University of South Australia, GPO Box 2471, Adelaide, SA 5001, Australia |
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| Abstract: | Analyzing the heterogeneity in metropolitan areas of India utilizing remote sensing data can help to identify more precise patterns of sub-standard residential areas. Earlier work analyzing inequalities in Indian cities employed a constructed index of multiple deprivations (IMDs) utilizing data from the Census of India 2001 (http://censusindia.gov.in). While that index, described in an earlier paper, provided a first approach to identify heterogeneity at the citywide scale, it neither provided information on spatial variations within the geographical boundaries of the Census database, nor about physical characteristics, such as green spaces and the variation in housing density and quality. In this article, we analyze whether different types of sub-standard residential areas can be identified through remote sensing data, combined, where relevant, with ground-truthing and local knowledge. The specific questions address: (1) the extent to which types of residential sub-standard areas can be drawn from remote sensing data, based on patterns of green space, structure of layout, density of built-up areas, size of buildings and other site characteristics; (2) the spatial diversity of these residential types for selected electoral wards; and (3) the correlation between different types of sub-standard residential areas and the results of the index of multiple deprivations utilized at electoral ward level found previously. |
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| Keywords: | Urban deprivations Sub-standard residential areas Remote sensing Visual image interpretation |
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