2020
DOI: 10.2166/ws.2020.381
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Machine learning method for quick identification of water quality index (WQI) based on Sentinel-2 MSI data: Ebinur Lake case study

Abstract: Surface water quality is an important factor affecting the ecological environment and human living environment. The monitoring of surface water quality by remote sensing monitoring technology can provide important research significance for water resources protection and water quality evaluation. Finding the optimal spectral index sensitive to water quality for remote sensing monitoring of water quality is extremely important for surface water quality analysis and treatment in the Ebinur Lake Basin in arid area… Show more

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Cited by 20 publications
(17 citation statements)
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“…Different indices are sensitive to different areas and varying weather and lighting conditions. To address this problem, [ 71 ] first correlated water quality parameters to different RS bands. These correlations were then used to test four ML models and their ability to predict a water quality index.…”
Section: The State Of the Art: Advances In Intelligent Waterbody Info...mentioning
confidence: 99%
“…Different indices are sensitive to different areas and varying weather and lighting conditions. To address this problem, [ 71 ] first correlated water quality parameters to different RS bands. These correlations were then used to test four ML models and their ability to predict a water quality index.…”
Section: The State Of the Art: Advances In Intelligent Waterbody Info...mentioning
confidence: 99%
“…Our study area includes the Bortala River basin, the Jing River basin and the adjacent wetland of Lake Ebunur, and parts of the Kuitun River basin extending from 4°20’N to 45°23’N and 79°53’E to 83°53’E; the area is located in the arid inland region of northwest China [ 31 ]. The total area of the study area is 50 000 km 2 and includes the Mongolian autonomous prefecture of Bortala and part of the city of Kuitun in the Xinjiang Uygur autonomous region, China [ 32 ].…”
Section: Study Area Datasetmentioning
confidence: 99%
“…3'E to 83˚53'E; the area is located in the arid inland region of northwest China [31]. The total area of the study area is 50 000 km 2 and includes the Mongolian autonomous prefecture of Bortala and part of the city of Kuitun in the Xinjiang Uygur autonomous region, China [32].…”
Section: Study Areamentioning
confidence: 99%
“…For more than four decades, remote sensing has illustrated strong capabilities to monitor and evaluate the quality of inland waters [1,[6][7][8][9]. Indeed, optically active Disclaimer/Publisher's Note: The statements, opinions, and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s).…”
Section: Introductionmentioning
confidence: 99%