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Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir

Presence of suspended particulate matter (SPM) in a waterbody or a river can be caused by multiple parameters such as other pollutants by the discharge of poorly maintained sewage, siltation, sedimentation, flood and even bacteria. In this study, remote sensing techniques were used to understand the...

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Autores principales: Paul, Arnab, K.S., Vignesh, Sood, Atisha, Bhaumik, Swastika, Singh, Kunwar Abhishek, Sethupathi, Sumathi, Chanda, Arunima
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745272/
https://www.ncbi.nlm.nih.gov/pubmed/36512073
http://dx.doi.org/10.1007/s00128-022-03638-9
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author Paul, Arnab
K.S., Vignesh
Sood, Atisha
Bhaumik, Swastika
Singh, Kunwar Abhishek
Sethupathi, Sumathi
Chanda, Arunima
author_facet Paul, Arnab
K.S., Vignesh
Sood, Atisha
Bhaumik, Swastika
Singh, Kunwar Abhishek
Sethupathi, Sumathi
Chanda, Arunima
author_sort Paul, Arnab
collection PubMed
description Presence of suspended particulate matter (SPM) in a waterbody or a river can be caused by multiple parameters such as other pollutants by the discharge of poorly maintained sewage, siltation, sedimentation, flood and even bacteria. In this study, remote sensing techniques were used to understand the effects of pandemic-induced lockdown on the SPM concentration in the lower Tapi reservoir or Ukai reservoir. The estimation was done using Landsat-8 OLI (Operational Land Imager) having radiometric resolution (12-bit) and a spatial resolution of 30 m. The Google Earth Engine (GEE) cloud computing platform was used in this study to generate the products. The GEE is a semi-automated workflow system using a robust approach designed for scientific analysis and visualization of geospatial datasets. An algorithm was deployed, and a time-series (2013–2020) analysis was done for the study area. It was found that the average mean value of SPM in Tapi River during 2020 is lowest than the last seven years at the same time.
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spelling pubmed-97452722022-12-13 Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir Paul, Arnab K.S., Vignesh Sood, Atisha Bhaumik, Swastika Singh, Kunwar Abhishek Sethupathi, Sumathi Chanda, Arunima Bull Environ Contam Toxicol Article Presence of suspended particulate matter (SPM) in a waterbody or a river can be caused by multiple parameters such as other pollutants by the discharge of poorly maintained sewage, siltation, sedimentation, flood and even bacteria. In this study, remote sensing techniques were used to understand the effects of pandemic-induced lockdown on the SPM concentration in the lower Tapi reservoir or Ukai reservoir. The estimation was done using Landsat-8 OLI (Operational Land Imager) having radiometric resolution (12-bit) and a spatial resolution of 30 m. The Google Earth Engine (GEE) cloud computing platform was used in this study to generate the products. The GEE is a semi-automated workflow system using a robust approach designed for scientific analysis and visualization of geospatial datasets. An algorithm was deployed, and a time-series (2013–2020) analysis was done for the study area. It was found that the average mean value of SPM in Tapi River during 2020 is lowest than the last seven years at the same time. Springer US 2022-12-13 2023 /pmc/articles/PMC9745272/ /pubmed/36512073 http://dx.doi.org/10.1007/s00128-022-03638-9 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Paul, Arnab
K.S., Vignesh
Sood, Atisha
Bhaumik, Swastika
Singh, Kunwar Abhishek
Sethupathi, Sumathi
Chanda, Arunima
Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir
title Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir
title_full Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir
title_fullStr Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir
title_full_unstemmed Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir
title_short Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir
title_sort suspended particulate matter analysis of pre and during covid lockdown using google earth engine cloud computing: a case study of ukai reservoir
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745272/
https://www.ncbi.nlm.nih.gov/pubmed/36512073
http://dx.doi.org/10.1007/s00128-022-03638-9
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