Satellite sensing of nighttime light, combined with population density data, can be used to estimate economic inequity, a study finds. The extent of economic inequality around the world is unclear due to the lack of reliable household income data. M. Usman Mirza, Marten Scheffer, and colleagues explored an alternative approach based on calculations of spatial variation in average nighttime light emissions per person. This method leverages the well-established link between nighttime light and economic prosperity, as well as the widespread phenomenon of spatial residential segregation, which generally increases with income inequality. The resulting light-based indicator is positively correlated with existing estimates of net income inequality based on self-reported household incomes, both across nations and US states. For example, both methods show that economic inequality is lower for high-income countries than for low-income and middle-income countries. In particular, inequality hotspots are evident in Russia, China, Southeast Asia, and most of Africa and South America. In addition, western and southern regions of the United States are more unequal than northern and central states. Combining light-based indicators with self-reported household incomes may reduce uncertainties in the economic inequality estimates. According to the authors, the fine-scale light-based maps may be particularly useful for regions currently lacking inequality data.
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Article #19-19913: "Global inequality remotely sensed," by M Usman Mirza, Chi Xu, Bas van Bavel, Egbert H van Nes, and Marten Scheffer
MEDIA CONTACTS: M. Usman Mirza, Maastricht University, Maastricht, NETHERLANDS; email: < m.mirza@maastrichtuniversity.nl >; Marten Scheffer, Wageningen University, Wageningen, NETHERLANDS; tel: +31641804880; email: < marten.scheffer@wur.nl >
Proceedings of the National Academy of Sciences