The role of Earth observation in an Integrated Deprived Area Mapping “system” for low-to-middle income countries

M. Kuffer*, Dana R. Thomson, Gianluca Boo, Ron Mahabir, Taïs Grippa, Sabine Vanhuysse, Ryan Engstrom, Robert Ndugwa, Jack Makau, Edith Darin, João Porto de Albuquerque, Caroline Kabaria

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

37 Citations (Scopus)
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Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups.
Original languageEnglish
Article number982
Pages (from-to)1-26
Number of pages26
JournalRemote sensing
Issue number6
Early online date18 Mar 2020
Publication statusPublished - Mar 2020




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