TY - JOUR
T1 - Estimating global economic well-being with unlit settlements
AU - McCallum, Ian
AU - Kyba, Christopher Conrad Maximillian
AU - Laso Bayas, Juan Carlos
AU - Elena, Moltchanova
AU - Matt, Cooper
AU - Crespo Cuaresma, Jesus
AU - Pachauri, Shonali
AU - See, Linda
AU - Danylo, Olga
AU - Moorthy, Inian
AU - Lesiv, Myroslava
AU - Baugh, Kimberly
AU - Elvidge, Christopher D.
AU - Hofer, Martin
AU - Fritz, Steffen
PY - 2022
Y1 - 2022
N2 - It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. 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. 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. Significant areas of unlit settlements are also located in some developed countries. 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%.
AB - It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. 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. 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. Significant areas of unlit settlements are also located in some developed countries. 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%.
U2 - 10.1038/s41467-022-30099-9
DO - 10.1038/s41467-022-30099-9
M3 - Journal article
SN - 2041-1723
VL - 13
SP - 2459
JO - Nature Communications
JF - Nature Communications
IS - 1
ER -