Turbidity is a visual property of water, related to the presence of suspended particles in waters. This parameter is measured in different water quality monitoring programmes as it can determine negative environmental effects both on the biotic and abiotic marine ecosystem. Traditional methods, e.g., in situ monitoring, offer high accuracy but provide sparse information in space and time. On the other hand, Earth Observation (EO) techniques have the potential to provide a comprehensive, fast and inexpensive monitoring system to observe the biophysical and biochemical conditions of water bodies. In the present work, a method for seawater turbidity retrieval from Sentinel-2 multispectral optical images, freely available within the EU Copernicus programme, is presented. The study explores different atmospheric correction methods available in open source software (QGIS, GRASS GIS and SNAP), in order to convert Level-1C (L1C) Top-Of-Atmosphere (TOA) images to Level-2A (L2A) Bottom-Of-Atmosphere (BOA), when the latter is not directly available. Once the proper method for atmospheric correction was identified and applied, the correlation between the in situ dataset and the individual bands known to be most sensitive to water turbidity, i.e., blue (B2), green (B3), red (B4) and near infrared (B8 and B8A) bands, were investigated and a linear regression model between selected band values and turbidity was identified.

SEA WATER TURBIDITY ANALYSIS FROM SENTINEL-2 IMAGES: ATMOSPHERIC CORRECTION AND BANDS CORRELATION

Ferrando, I.;Federici, B.
2022-01-01

Abstract

Turbidity is a visual property of water, related to the presence of suspended particles in waters. This parameter is measured in different water quality monitoring programmes as it can determine negative environmental effects both on the biotic and abiotic marine ecosystem. Traditional methods, e.g., in situ monitoring, offer high accuracy but provide sparse information in space and time. On the other hand, Earth Observation (EO) techniques have the potential to provide a comprehensive, fast and inexpensive monitoring system to observe the biophysical and biochemical conditions of water bodies. In the present work, a method for seawater turbidity retrieval from Sentinel-2 multispectral optical images, freely available within the EU Copernicus programme, is presented. The study explores different atmospheric correction methods available in open source software (QGIS, GRASS GIS and SNAP), in order to convert Level-1C (L1C) Top-Of-Atmosphere (TOA) images to Level-2A (L2A) Bottom-Of-Atmosphere (BOA), when the latter is not directly available. Once the proper method for atmospheric correction was identified and applied, the correlation between the in situ dataset and the individual bands known to be most sensitive to water turbidity, i.e., blue (B2), green (B3), red (B4) and near infrared (B8 and B8A) bands, were investigated and a linear regression model between selected band values and turbidity was identified.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1093753
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