Spatial Information Gaps on Deprived Urban Areas (Slums) in Low-and-Middle-Income-Countries: A User-Centered Approach Show others and affiliations
2021 (English) In: URBAN SCIENCE, ISSN 2413-8851, Vol. 5, no 4, p. 72-, article id 72Article in journal (Refereed) Published
Abstract [en]
Routine and accurate data on deprivation are needed for urban planning and decision support at various scales (i.e., from community to international). However, analyzing information requirements of diverse users on urban deprivation, we found that data are often not available or inaccessible. To bridge this data gap, Earth Observation (EO) data can support access to frequently updated spatial information. However, a user-centered approach is urgently required for the production of EO-based mapping products. Combining an online survey and several forms of user interactions, we defined five system specifications (derived from user requirements) for designing an open-access spatial information system for deprived urban areas. First, gridded maps represent the optimal spatial granularity to deal with high uncertainties of boundaries of deprived areas and to protect privacy. Second, a high temporal granularity of 1-2 years is important to respond to the high spatial dynamics of urban areas. Third, detailed local-scale information should be part of a city-to-global information system. Fourth, both aspects, community assets and risks, need to be part of an information system, and such data need to be combined with local community-based information. Fifth, in particular, civil society and government users should have fair access to data that bridges the digital barriers. A data ecosystem on urban deprivation meeting these requirements will be able to support community-level action for improving living conditions in deprived areas, local science-based policymaking, and tracking progress towards global targets such as the SDGs.
Place, publisher, year, edition, pages MDPI AG , 2021. Vol. 5, no 4, p. 72-, article id 72
Keywords [en]
slums, informal settlements, urban information system, digital data, planning support, remote sensing, spatial data
National Category
Public Health, Global Health and Social Medicine
Identifiers URN: urn:nbn:se:kth:diva-307168 DOI: 10.3390/urbansci5040072 ISI: 000737258300001 Scopus ID: 2-s2.0-85121373814 OAI: oai:DiVA.org:kth-307168 DiVA, id: diva2:1627494
Note QC 20220113
2022-01-132022-01-132025-02-20 Bibliographically approved