Determining the local spatial relationships between COVID-19 and NO₂ using sentinel 5P and MGWR

Ashnita Rahim, . and Rohayu Haron Narashid, . and Siti Nurhafizah Mohamad Yasim, . and Nurul Ain Mohd Zaki, . and Suhaila Hashim, . and Ruslan Rainis, . and Epa, Ailis Elizabeth (2023) Determining the local spatial relationships between COVID-19 and NO₂ using sentinel 5P and MGWR. Journal of Sustainability Science and Management (Malaysia), 18 (12). pp. 84-94. ISSN 2672-7226

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.

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Abstract

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.

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Item Type:	Article
AGROVOC Term:	nitrogen dioxide
AGROVOC Term:	COVID-19
AGROVOC Term:	air-borne infection
AGROVOC Term:	spatial data
AGROVOC Term:	remote sensing
AGROVOC Term:	regression analysis
AGROVOC Term:	airbone transmission
Geographical Term:	Malaysia
Depositing User:	Mr. Khoirul Asrimi Md Nor
Date Deposited:	28 Oct 2025 15:12
Last Modified:	28 Oct 2025 15:13
URI:	http://webagris.upm.edu.my/id/eprint/2175

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