Semantic Scholar Open Access 2022 57 sitasi

Estimating global economic well-being with unlit settlements

I. Mccallum C. Kyba J. L. Bayas E. Moltchanova Matt Cooper +10 lainnya

Abstrak

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%. Nighttime lights from satellite are combined with a map of human settlements, showing that 19% of these areas, mainly in Africa, the Middle East and Asia, have no detectable artificial light. These data were then used in models to predict well-being.

Topik & Kata Kunci

Penulis (15)

I

I. Mccallum

C

C. Kyba

J

J. L. Bayas

E

E. Moltchanova

M

Matt Cooper

J

J. Cuaresma

S

S. Pachauri

L

L. See

O

O. Danylo

I

I. Moorthy

M

M. Lesiv

K

K. Baugh

C

C. Elvidge

M

Martin Hofer

S

S. Fritz

Format Sitasi

Mccallum, I., Kyba, C., Bayas, J.L., Moltchanova, E., Cooper, M., Cuaresma, J. et al. (2022). Estimating global economic well-being with unlit settlements. https://doi.org/10.1038/s41467-022-30099-9

Akses Cepat

Lihat di Sumber doi.org/10.1038/s41467-022-30099-9
Informasi Jurnal
Tahun Terbit
2022
Bahasa
en
Total Sitasi
57×
Sumber Database
Semantic Scholar
DOI
10.1038/s41467-022-30099-9
Akses
Open Access ✓