New paper in Journal of the Royal Statistical Society Series A

Timo Schmid and co-authors investigate satellite imagery-based population estimates.

Intercensal updating using structure-preserving methods and satellite imagery

       Koebe, T.; Arias-Salazar, A.; Rojas-Perilla, N.; Schmid, T.

Abstract: Censuses are fundamental building blocks of most modern-day societies, yet collected every 10 years at best. We propose an extension of the widely popular census updating technique structure-preserving estimation by incorporating auxiliary information in order to take ongoing subnational population shifts into account. We apply our method by incorporating satellite imagery as additional source to derive annual small-area updates of multidimensional poverty indicators from 2013 to 2020 for a population at risk: female-headed households in Senegal. We evaluate the performance of our proposal using data from two different census periods.

Till Koebe, Alejandra Arias-Salazar, Natalia Rojas-Perilla & Timo Schmid (2022) Intercensal updating using structure-preserving methods and satellite imagery, Journal of the Royal Statistical Society Series A, DOI: https://doi.org/10.1111/rssa.12802