Publication | Open Access
The Role of Earth Observation in an Integrated Deprived Area Mapping “System” for Low-to-Middle Income Countries
72
Citations
86
References
2020
Year
Earth ObservationEngineeringGeovisualizationLand UseGeographic AnalyticsEarth System ScienceEarth ScienceSocial SciencesGlobal SouthGeographic Information SystemsGeospatial MappingGeographical AspectSpatial Database DesignGlobal Urban PlanningUrban StudiesLand Use PlanningCartographyGeographyUrban PlanningLow-to-middle Income CountriesEarth Observation DataUrban GeographySdg 11Urban DesignDifferent Interest GroupsRemote SensingDigital GeographyGeospatial Data
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.
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