Changes in turbidity and human activities along Haihe River Basin during lockdown of COVID-19 using satellite data.


Journal

Environmental science and pollution research international
ISSN: 1614-7499
Titre abrégé: Environ Sci Pollut Res Int
Pays: Germany
ID NLM: 9441769

Informations de publication

Date de publication:
Jan 2022
Historique:
received: 24 05 2021
accepted: 07 08 2021
pubmed: 15 8 2021
medline: 12 1 2022
entrez: 14 8 2021
Statut: ppublish

Résumé

During the outbreak of the COVID-19, China implemented an urban lockdown in the first period. These measures not only effectively curbed the spread of the virus but also brought a positive impact on the ecological environment. The water quality of urban inland river has a significant impact on urban ecology and public health. This study uses Sentinel-2 visible and near-infrared band reflectance and the Normalized Difference Turbidity Index (NDTI) to analyze the water quality of the Haihe River Basin during the control period of COVID-19. It is found that during the lockdown period, the river water quality was significantly improved compared to the same period in 2019. The average NDTI of the Haihe River Basin in March decreased by 0.27, a decrease of 219.06%; in April, it increased by 0.07, that is 38.38%. Further exploration using VIIRS lights found that the brightness of the lights in the main urban area was significantly lower in February, the beginning of the lockdown. However, as the city was unblocked, the lights rose sharply in March and then recovered to normal. There is obvious asynchrony in changes between river turbidity and light. The results can help understand the impact of human activities on the natural environment.

Identifiants

pubmed: 34389962
doi: 10.1007/s11356-021-15928-6
pii: 10.1007/s11356-021-15928-6
pmc: PMC8363492
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3702-3717

Informations de copyright

© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Auteurs

Xu Chen (X)

College of Environment and Resources, Fuzhou University, Fuzhou, 350108, China.

Wei Chen (W)

Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin, 300072, China. chenwei19@tju.edu.cn.

Yanbing Bai (Y)

Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, 100872, China.

Xiaole Wen (X)

College of Environment and Resources, Fuzhou University, Fuzhou, 350108, China.

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Classifications MeSH