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Need for an integrated deprived area “slum” mapping system (IDEAMAPS) in low- and middle-income countries (LMICs)

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Thomson, Dana R., Kuffer, Monika, Boo, Gianluca, Hati, Beatrice, Grippa, Tais, Elsey, Helen, Linard, Catherine, Mahabir, Ron, Kyobutungi, Catherine, Maviti, Joshua et al.
(2020) Need for an integrated deprived area “slum” mapping system (IDEAMAPS) in low- and middle-income countries (LMICs). Social Sciences, 9 (5). 80. doi:10.3390/socsci9050080

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Official URL: http://dx.doi.org/10.3390/socsci9050080

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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. View Full-Text

Item Type: Journal Article
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HT Communities. Classes. Races
H Social Sciences > HV Social pathology. Social and public welfare
Divisions: Faculty of Arts > School for Cross-faculty Studies
Faculty of Arts > School for Cross-faculty Studies > Institute for Global Sustainable Development
Library of Congress Subject Headings (LCSH): Slums, Slums -- Developing countries, Urban poor -- Housing -- Developing countries, Cities and towns -- Developing countries -- Growth, Cities and towns -- Developing countries -- Aerial views, Slums -- Developing countries -- Simulation methods, Squatter settlements -- Developing countries -- Simulation methods
Journal or Publication Title: Social Sciences
Publisher: M D P I AG
ISSN: 2076-0760
Official Date: 2020
Dates:
DateEvent
2020Published
13 May 2020Available
7 May 2020Accepted
Volume: 9
Number: 5
Article Number: 80
DOI: 10.3390/socsci9050080
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
SR/11/380Belgian Federal Science Policy Officehttp://dx.doi.org/10.13039/501100002749
VI. Veni. 194.025[NWO] Nederlandse Organisatie voor Wetenschappelijk Onderzoekhttp://dx.doi.org/10.13039/501100003246
EP/T029900/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266

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