Studies deriving relationships between nighttime radiance and daytime imagery 10, estimating poverty via mobile phone data 8 or the socioecological treatment of satellite data 29 all require upscaling and are dependent on disparate proprietary datasets 10. Such proxies have proved significant in nations with measurable lighting, but for impoverished regions, where there is often little or no detectable light, these approaches are difficult to implement 9, 10, 28. Relationships between radiance and prosperity 9, 23, 24, 25, 26, 27 have long focused on economic predictors, for example, gross domestic product (GDP). With an original spatial resolution of 10 m, the WSF dataset currently represents the most detailed global inventory of human settlements to date 21, 22. In addition, recent advances in the development of a World Settlement Footprint 21, 22 (WSF) mean it is now possible to estimate the amount of building infrastructure globally that has no associated satellite-detectable radiance. Most of the artificial light observed by VIIRS DNB comes from human settlements 20. Owing to its improved spatial and radiometric accuracy over its predecessor (the Defense Meteorological Satellite Program), this sensor allows for analysis of lighting at the neighborhood scale 19. The Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS DNB), a global night light satellite sensor first launched in 2012, images almost the entire Earth nightly 16 at a resolution of approximately 750 m in the 500–900 nm spectral band 18. Given the paucity of relevant information, one of the most promising methods for estimating economic activity-especially for countries with low-quality statistical systems 9, 15-is that of satellite-derived radiance 16, 17. Targeting resources to where the poorest live is thus crucial if extreme poverty is to be addressed 6, 14. Recent studies show, however, that aid typically does not flow to poor areas in countries, but rather to places where there is relative wealth 6, 13. The international donor community is attempting to address poverty by spending billions of dollars annually in aid for the world’s poorest countries 12 based on the assumption that aid is flowing to where poor people live. However, many developing countries, particularly in sub-Saharan Africa, have only rudimentary economic statistics, and in many cases, lack regional data 9, 10, 11. Traditionally, wealth and poverty have been measured through surveys of household income and consumption 8. Knowing the location of those one billion is crucial if aid and infrastructure are to reach them 6, 7. A lack of access to modern energy impacts health and welfare and impedes sustainable development 3, 4, 5. Similar content being viewed by othersĭespite the global poverty rate having been halved since 2000 1, almost one billion people are still living without access to reliable and affordable electricity 2. For 49 countries spread across Africa, Asia and the Americas we are able to predict and map the wealth class obtained from ~2,400,000 geo-located households based upon the percent of unlit settlements, with an overall accuracy of 87%. Significant areas of unlit settlements are also located in some developed countries. The majority of unlit settlement footprints are found in Africa (39%), rising to 65% if we consider only rural settlement areas, along with numerous countries in the Middle East and Asia. Here we combine satellite nighttime lights and the world settlement footprint for the year 2015 to show that 19% of the total settlement footprint of the planet had no detectable artificial radiance associated with it. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe.
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