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A satellite survey of the cumulative radiant emissions from electric lighting across China reveals a large radiance decline in lighting from December 2019 to February 2020—the peak of the lockdown established to suppress the spread of COVID-19 infections. To illustrate the changes, an analysis was also conducted on a reference set from a year prior to the pandemic. In the reference period, the majority (62%) of China's population lived in administrative units that became brighter in March 2019 relative to December 2018. The situation reversed in February 2020, when 82% of the population lived in administrative units where lighting dimmed as a result of the pandemic. The dimming has also been demonstrated with difference images for the reference and pandemic image pairs, scattergrams, and a nightly temporal profile. The results indicate that it should be feasible to monitor declines and recovery in economic activity levels using nighttime lighting as a proxy. [ABSTRACT FROM AUTHOR]

Abstract Various scientific researches were conducted to monitor human activities and natural phenomena with the availability of various night time satellite data such as Defense Meteorological Satellite Program (DMPS). Population growth especially in a faster growing economy like China is an important indicator for assessing socio-economic development, urban planning and environmental management. Thus, spatial distribution of population is instrumental in assessing growth and developmental activities in Beijing city of China. The satellite observation data derived from Defense Meteorological Satellite Program (DMSP) was utilized to estimate population density through the measurement of light flux with radiometric recording. The data was calibrated using C 0 , C 1 , C 2 parameters before processing. Population density of Beijing city was estimated using light volume of this calibrated data. Regression analysis between urban population and light volume revealed high correlation (r 2 = 0.89). Thus, population density can effectively be estimated using light intensity. The model used for estimating urban population density can effectively be utilized for other major cities of the world. Graphical abstract Image 1 Highlights • Multitemporal NTL data can serve as an excellent proxy for estimating population density of a geographic region. • NTL data better predict population density than optical data. • Future research can leverage VIIRS′ superior sensitivity and on-board calibration. [ABSTRACT FROM AUTHOR]