Can Nighttime Satellite Imagery Inform Our Understanding of Education Inequality?

Abstract

Education is a human right, and equal access to education is important for achieving sustainable development. Measuring socioeconomic development, especially the changes to education inequality, can help educators, practitioners, and policymakers with decision- and policy-making. This article presents an approach that combines population distribution, human settlements, and nighttime light (NTL) data to assess and explore development and education inequality trajectories at national levels across multiple time periods using latent growth models (LGMs). Results show that countries and regions with initially low human development levels tend to have higher levels of associated education inequality and uneven distribution of urban population. Additionally, the initial status of human development can be used to explain the linear growth rate of education inequality, but the association between trajectories becomes less significant as time increases.