Suitability of NASA’s Black Marble Daily Nighttime Lights for Population Studies at Varying Spatial and Temporal Scales

Juan Fernando Martinez; Kytt MacManus; Eleanor C. Stokes; Zhuosen Wang; Alex de Sherbinin

doi:10.3390/rs15102611

Remote Sensing (May 2023)

Suitability of NASA’s Black Marble Daily Nighttime Lights for Population Studies at Varying Spatial and Temporal Scales

Juan Fernando Martinez,
Kytt MacManus,
Eleanor C. Stokes,
Zhuosen Wang,
Alex de Sherbinin

Affiliations

Juan Fernando Martinez: Center for International Earth Science Information Network (CIESIN), the Columbia Climate School at Columbia University, New York, NY 10025, USA
Kytt MacManus: Center for International Earth Science Information Network (CIESIN), the Columbia Climate School at Columbia University, New York, NY 10025, USA
Eleanor C. Stokes: NASA Headquarters, Washington, DC 20546, USA
Zhuosen Wang: Terrestrial Information Systems Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Alex de Sherbinin: Center for International Earth Science Information Network (CIESIN), the Columbia Climate School at Columbia University, New York, NY 10025, USA

DOI: https://doi.org/10.3390/rs15102611
Journal volume & issue: Vol. 15, no. 10
p. 2611

Abstract

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This paper investigates the potential link between changes in NASA’s Black Marble VIIRS/NPP Gap-Filled Lunar BRDF-Adjusted Nighttime Lights Daily L3 Global 500 m Linear Lat Lon Grid (VNP46A2) nighttime lights product (NTL) and human dynamics, particularly population counts and changes at a variety of spatial and temporal scales. We conducted analyses in four case studies at varying resolutions to explore the relationship of NTL data for population studies, including demographic research, disaster mitigation and adaptation planning, and infrastructure development. The analyses were conducted using different administrative geographies, including a refugee camp, a subnational region, and a country. We compared changes in population counts, density, migration, and displacement against changes in daily, weekly, monthly, and annual NTL values. Our case study results demonstrate that out-migration does not always lead to a decrease in NTL. We found that rural population decline did not correspond to a decrease in NTL. Despite significant out-migration in many rural areas NTL remained largely unchanged. NTL provided essential information on infrastructure damage in the short-term aftermath of this disaster; however, NTL alone was not correlated to the location of displaced individuals. Through news reports, we were able to corroborate the NTL changes to downtimes of the electrical systems. Monthly NTL averages were highly correlated to population counts, but a pixel-level analysis showed that the changes in NTL were primarily attributed to economic diversification. In summary, NTL is the product of several factors including demographic, environmental, economic, and political forces that shape electricity infrastructure, and we suggest that NTL data must first be parameterized with ancillary ground-level information in order to be effectively applied to population models.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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