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Article

Upscaling Household Survey Data Using Remote Sensing to Map Socioeconomic Groups in Kampala, Uganda

1
Department of Earth and Environmental Sciences, KU Leuven, 3001 Leuven, Belgium
2
Fonds Wetenschappelijk Onderzoek (FWO) Vlaanderen, 1000 Brussel, Belgium
3
Institute for Environmental Studies, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
4
Department of Geography, Geo-Informatics and Climatic Sciences, Makerere University, P.O. Box 7062 Kampala, Uganda
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(20), 3468; https://doi.org/10.3390/rs12203468
Received: 31 August 2020 / Revised: 18 October 2020 / Accepted: 20 October 2020 / Published: 21 October 2020
(This article belongs to the Special Issue Remote Sensing Application to Population Mapping)
Sub-Saharan African cities are expanding horizontally, demonstrating spatial patterns of urban sprawl and socioeconomic segregation. An important research gap around the geographies of urban populations is that city-wide analyses mask local socioeconomic inequalities. This research focuses on those inequalities by identifying the spatial settlement patterns of socioeconomic groups within the Greater Kampala Metropolitan Area (Uganda). Findings are based on a novel dataset, an extensive household survey with 541 households, conducted in Kampala in 2019. To identify different socioeconomic groups, a k-prototypes clustering method was applied to the survey data. A maximum likelihood classification method was applied on a recent Landsat-8 image of the city and compared to the socioeconomic clustering through a fuzzy error matrix. The resulting maps show how different socioeconomic clusters are located around the city. We propose a simple method to upscale household survey responses to a larger study area, to use these data as a base map for further analysis or urban planning purposes. Obtaining a better understanding of the spatial variability in socioeconomic dynamics can aid urban policy-makers to target their decision-making processes towards a more favorable and sustainable future. View Full-Text
Keywords: urban population; spatial analysis; remote sensing; household surveys; census; Sub-Saharan Africa; GIS urban population; spatial analysis; remote sensing; household surveys; census; Sub-Saharan Africa; GIS
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MDPI and ACS Style

Hemerijckx, L.-M.; Van Emelen, S.; Rymenants, J.; Davis, J.; Verburg, P.H.; Lwasa, S.; Van Rompaey, A. Upscaling Household Survey Data Using Remote Sensing to Map Socioeconomic Groups in Kampala, Uganda. Remote Sens. 2020, 12, 3468. https://doi.org/10.3390/rs12203468

AMA Style

Hemerijckx L-M, Van Emelen S, Rymenants J, Davis J, Verburg PH, Lwasa S, Van Rompaey A. Upscaling Household Survey Data Using Remote Sensing to Map Socioeconomic Groups in Kampala, Uganda. Remote Sensing. 2020; 12(20):3468. https://doi.org/10.3390/rs12203468

Chicago/Turabian Style

Hemerijckx, Lisa-Marie, Sam Van Emelen, Joachim Rymenants, Jac Davis, Peter H. Verburg, Shuaib Lwasa, and Anton Van Rompaey. 2020. "Upscaling Household Survey Data Using Remote Sensing to Map Socioeconomic Groups in Kampala, Uganda" Remote Sensing 12, no. 20: 3468. https://doi.org/10.3390/rs12203468

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