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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Bibliographic Details
Published in:Bulletin of environmental contamination and toxicology 2023-01, Vol.110 (1), p.7, Article 7
Main Authors: Paul, Arnab, K.S., Vignesh, Sood, Atisha, Bhaumik, Swastika, Singh, Kunwar Abhishek, Sethupathi, Sumathi, Chanda, Arunima
Format: Article
Language:English
Subjects:
Algorithms
Aquatic Pollution
Cloud Computing
Communicable Disease Control
COVID-19
Earth and Environmental Science
Ecotoxicology
Environment
Environmental Chemistry
Environmental Health
Humans
Landsat
Particulate matter
Particulate Matter - analysis
Pollutants
Pollution
Radiometric resolution
Remote sensing
Reservoirs
Rivers
Search Engine
Sewage
Soil Science & Conservation
Spatial discrimination
Spatial resolution
Waste Water Technology
Water Management
Water Pollution Control
Workflow management systems
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Summary: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.
ISSN:0007-4861
1432-0800
DOI:10.1007/s00128-022-03638-9