Tracking poverty using satellite imagery and big data

van Dijk, M. ORCID: https://orcid.org/0000-0002-5207-7304, Moorthy, I., Nguyen, B. ORCID: https://orcid.org/0000-0002-2260-8186, See, L. ORCID: https://orcid.org/0000-0002-2665-7065, & Fritz, S. ORCID: https://orcid.org/0000-0003-0420-8549 (2019). Tracking poverty using satellite imagery and big data. IIASA Working Paper. Laxenburg, Austria: WP-19-014

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Abstract

Despite recent improvements in the availability and quality of socioeconomic data from developing countries, there are still persistent data gaps that are preventing comprehensive monitoring and evaluation of targets and indicators of the Sustainable Development Goals. Approaches are hampered by the inconsistent spatial and temporal coverage of census data and Demographic and Health Surveys, which serve as the primary source for population-level statistics in most developing countries. Traditional censuses are too expensive to be implemented in remote areas where population density is low and road networks are poor. However, the recent and rapid diffusion of high-resolution satellite imagery offers a new wealth of relatively untapped information that can be used to gain in-depth information on groups that have historically been left out by traditional surveys. Moreover, there are new data streams such as call detail records from mobile phone data networks can help to derive behavioral indicators and improve tracking of expenditure and wealth. This exploratory research conflates various data streams to derive spatially explicit poverty indicators for Senegal with immense scaling potential to other regions.

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