Publication: Guiding Social Protection Targeting Through Satellite Data in São Tomé and Príncipe
Date
2022-10
ISSN
Published
2022-10
Author(s)
Fisker, Peter
Gallego-Ayala, Jordi
Malmgren Hansen, David
Sohnesen, Thomas Pave
Murrugarra, Edmundo
Abstract
Social safety net programs focus on a
subset of the population, usually the poorest and most
vulnerable. However, in most developing countries there is
no administrative data on relative wealth of the population
to support the selection process of the potential
beneficiaries of the social safety net programs. Hence,
selection into programs is often multi-methodological
approached and starts with geographical targeting for the
selection of program implementation areas. To facilitate
this stage of the targeting process in São Tomé and
Príncipe, this working paper develops High Resolution
Satellite Imagery (HRSI) poverty maps, providing both
estimates of poverty incidence and program eligibility at a
highly detailed resolution (110 m x 110 m). Furthermore, the
analysis combines poverty incidence and population density
to enable the geographical targeting process. This working
paper shows that HRSI poverty maps can be used as key
operational tools to facilitate the decision-making process
of the geographical targeting and efficiently identify entry
points for rapidly expanding social safety net programs.
Unlike HRSI poverty maps based on census data, poverty maps
based on satellite data and machine learning can be updated
frequently at low cost supporting more adaptive social
protection programs.
Citation
“Fisker, Peter; Gallego-Ayala, Jordi; Malmgren Hansen, David; Sohnesen, Thomas Pave; Murrugarra, Edmundo. 2022. Guiding Social Protection Targeting Through Satellite Data in São Tomé and Príncipe. Social Protection & Jobs Discussion Paper;No. 2212. © World Bank, Washington, DC. http://openknowledge.worldbank.org/handle/10986/38222 License: CC BY 3.0 IGO.”