Need for an Integrated Deprived Area “Slum” Mapping System (IDEAMAPS) in Low- and Middle-Income Countries (LMICs)

Dana R. Thomson, Monika Kuffer, Gianluca Boo, Beatrice Hati, Tais Grippa, Helen Elsey, Catherine Linard, Ron Mahabir, Catherine Kyobutungi, Joshua Maviti, Dennis Mwaniki, Robert Ndugwa, Jack Makau, Richard Sliuzas, Salome Cheruiyot, Kilion Nyambuga, Nicholus Mboga, Nicera Wanjiru Kimani, Joao Porto de Albuquerque and Caroline Kabaria
Additional contact information
Dana R. Thomson: Department of Social Statistics and Demography, University of Southampton, Southampton SO17 1BJ, UK
Monika Kuffer: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands
Gianluca Boo: WorldPop Research Group, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
Beatrice Hati: Institute for Housing and Urban Development Studies, Erasmus University Rotterdam (EUR), 3000 Rotterdam, The Netherlands
Tais Grippa: Institute for Environmental Management and Land-Use Planning, Université Libre de Bruxelles, 1050 Bruxelles, Belgium
Helen Elsey: Department of Global Health, University of York, Heslington YO10 5DD, UK
Catherine Linard: Department of Geography, Université de Namur, 5000 Namur, Belgium
Ron Mahabir: Department of Computational and Data Sciences, George Mason University, Fairfax, VA 22030, USA
Catherine Kyobutungi: African Population and Health Research Center, Kitisuru Nairobi, Kenya
Joshua Maviti: Participatory Slum Upgrading Team, UN-Habitat, Gigiri Nairobi, Kenya
Dennis Mwaniki: Global Urban Observatory, UN-Habitat, Gigiri Nairobi, Kenya
Robert Ndugwa: Global Urban Observatory, UN-Habitat, Gigiri Nairobi, Kenya
Jack Makau: Slum Dwellers International, Kilimani Estate, Nairobi, Kenya
Richard Sliuzas: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands
Salome Cheruiyot: Global Urban Observatory, UN-Habitat, Gigiri Nairobi, Kenya
Kilion Nyambuga: Slum Dwellers International, Kilimani Estate, Nairobi, Kenya
Nicholus Mboga: Institute for Environmental Management and Land-Use Planning, Université Libre de Bruxelles, 1050 Bruxelles, Belgium
Nicera Wanjiru Kimani: Slum Dwellers International, Kilimani Estate, Nairobi, Kenya
Joao Porto de Albuquerque: Institute for Global Sustainable Development, University of Warwick, Coventry CV4 7AL, UK
Caroline Kabaria: African Population and Health Research Center, Kitisuru Nairobi, Kenya

Social Sciences, 2020, vol. 9, issue 5, 1-17

Abstract: Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human (visual) interpretation and machine classification of air or spaceborne imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of public services. We summarize common areas of understanding, and present a set of requirements and a framework to produce routine, accurate maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making across Low- and Middle-Income Countries (LMICs). We suggest that machine learning models be extended to incorporate social area-level covariates and regular contributions of up-to-date and context-relevant field-based classification of deprived urban areas.

Keywords: urban; poverty; SDG; slum; deprivation, spatial model (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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