Assessment and Monitoring of VIIRS-DNB and SQML-L light Pollution in Lahore-Pakistan

Hajra Nisar, Faiza Sarwar, Safdar Ali Shirazi, Dania Amjad, Rana Waqar Aslam ()
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Hajra Nisar, Faiza Sarwar, Safdar Ali Shirazi, Dania Amjad, Rana Waqar Aslam: Department of Geography, University of the Punjab, Lahore 54000, Pakistan. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIEsSMARS), Wuhan University, Wuhan 430079, China.

International Journal of Innovations in Science & Technology, 2022, vol. 4, issue 1, 94-109

Abstract: The usage of artificial light is excessive and improper. Earth's night picture has changed significantly from space and studies have shown that over-exposure to artificial light in the night can influence animals, the environment and human beings. The purpose of this study was to monitor and measure skylights of Lahore City and temporary light pollution from 2012-2019. The Suite-Day/Night band of the Visible Image Radiometer was used for time changes analysis with GIS and Remote Sensing tools. Indicators were established as a table tool through zonal statistics, and a field survey was also undertaken to measure the Sky-Glow of Lahore with Sky Quality Meter-L. The results suggest that from 2012 to 2019, light pollution rose by 23.43 percent. Results suggest that around 53.99% of Lahore suffered from light pollution. The number of lights in Lahore has increased by 161.82 percent between 2012 and 2019. In the study period, the mean night light and the standard night light deviation were 127.87 and 98.22 percent, respectively. Lahore's night sky was heavily polluted by light. Lahore's average skylight is 17.15 meters above sea level, which means low quality skies at night. This research aims to provide people an insight into light pollution and the causes of local light pollution. Furthermore, this study aims to enhance public attention to light pollution mitigation attempts by governments and politicians.

Keywords: Light Pollution; Sky Glow; VIIRS; SQML; Sum of lights; Mean Night-time Light; Standard deviation Night-time Light; Remote Sensing (search for similar items in EconPapers)
Date: 2022
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