DETERMINING THE LOCAL SPATIAL RELATIONSHIPS BETWEEN COVID-19 AND NO2 USING SENTINEL 5P AND MGWR

• Published in: Journal of Sustainability Science and Management
• Main Author: Rahim A.; Narashid R.H.; Yasim S.N.M.; Zaki N.A.M.; Hashim S.; Rainis R.; Epa A.E.
• Format: Article
• Language: English
• Published: Universiti Malaysia Terengganu 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185451688&doi=10.46754%2fjssm.2023.12.008&partnerID=40&md5=731eebec0a538ebd8378481cd293fd58

Nitrogen dioxide (NO2) may become one of the contributing factors to COVID-19 deaths. Nowadays, the effect of airborne epidemics on respiratory-related diseases, like COVID-19, can be demonstrated in the geographical region using GIS and Remote Sensing technologies. Thus, this study aims to determine the relationships between COVID-19 and NO2 using satellite remote sensing data and the local regression approach. The NO2 data were derived from Sentinel-5 Precursor satellite images, which were acquired in February and May 2021 respectively. Then, the Multiscale Geographically Weighted Regression (MGWR) approach was applied to determine the local spatial relationships between NO2 and COVID-19. It was found that the relationships between NO2 and COVID-19 were extremely low at a global relationship with the Ordinary Least Square (OLS) technique. However, with the use of MGWR, a moderate relationship between the derived NO2 and COVID-19 data cases was found in February 2021 (R2 =0.49) and May 2021 (R2 =0.47). The significant effect of NO2 on the COVID-19 outbreak was found in Negeri Sembilan, Kuala Lumpur, Johor, and Selangor. Although the lockdown had decreased air pollution, this study reveals that there was still a significant effect of air pollutants like NO2 on the outbreak of COVID-19 of the selected period in micro-scale areas. © 2023 UMT Press. All Rights Reserved.