In search of light: Estimating diffuse attenuation coefficient of downwelling irradiance and its variation in optically complex shallow water habitats using Sentinel-2 imagery

Frequent resuspension of sediments in the water column hampers photosynthesis in submerged aquatic vegetation due to decreased light, reduces gas exchange from sediment deposition and affects their anchoring ability. Remote sensing of light attenuation of the water column in form of diffuse attenuation coefficient of downwelling photosynthetically available radiation (K<sub>dPAR</sub>) provides a spatial perspective to study light attenuation of water column. This study aims to use Sentinel-2 derived K<sub>dPAR</sub> to characterize light variation and test its significance in relation to occurrence of eelgrass (Zostera marina) at Horsens and Roskilde fjords located in coastal waters of Denmark. Areas with maximum of K<sub>dPAR</sub> (mean > 75<sup>th</sup> percentile) coinciding with maximum and minimum variation (standard deviation >75<sup>th</sup> and <25<sup>th</sup> percentile respectively) were identified at the study sites. The standard deviation (SD) of K<sub>dPAR</sub> and fraction of surface irradiance reaching bottom (PAR<sub>Z</sub>) was used to predict occurrences of eelgrass using Logistic regression (LR) and Support Vector Machine (SVM). The LR and SVM (linear kernel) could predict eelgrass presence-absence with 65 % overall accuracy and precision of 63 % and 62 % respectively on the test set (n = 238). SD correlation with eelgrss occurrences (Point-biserial correlation = -0.11, p = 0.002) and with predicted probabilities of logistic regression (Pearson's r = -0.46) indicates increased K<sub>dPAR</sub> variation reduces chances of eelgrass. The K<sub>dPAR</sub> for this study was derived using Quasi Analytical Algorithm Version-5 (QAA-V5) and Case-2 Regional Coast Colour (C2RCC) and validated against in-situ matched observations (n = 113) for duration of March to October of 2016-2018.

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Publication Details

Journal
The Science of The Total Environment
Published
2025-02-01
DOI
https://doi.org/10.1016/j.scitotenv.2025.178598
Citations
2
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
3.59

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article

In search of light: Estimating diffuse attenuation coefficient of downwelling irradiance and its variation in optically complex shallow water habitats using Sentinel-2 imagery

Satish Pawar, Rafael Gonçalves‐Araujo, Karen Timmermann
2 citations
The Science of The Total Environment
Marine and coastal ecosystems
3.59
article

In search of light: Estimating diffuse attenuation coefficient of downwelling irradiance and its variation in optically complex shallow water habitats using Sentinel-2 imagery

Satish Pawar, Rafael Gonçalves‐Araujo, Karen Timmermann
article en
2 citations

Abstract

Frequent resuspension of sediments in the water column hampers photosynthesis in submerged aquatic vegetation due to decreased light, reduces gas exchange from sediment deposition and affects their anchoring ability. Remote sensing of light attenuation of the water column in form of diffuse attenuation coefficient of downwelling photosynthetically available radiation (K<sub>dPAR</sub>) provides a spatial perspective to study light attenuation of water column. This study aims to use Sentinel-2 derived K<sub>dPAR</sub> to characterize light variation and test its significance in relation to occurrence of eelgrass (Zostera marina) at Horsens and Roskilde fjords located in coastal waters of Denmark. Areas with maximum of K<sub>dPAR</sub> (mean > 75<sup>th</sup> percentile) coinciding with maximum and minimum variation (standard deviation >75<sup>th</sup> and <25<sup>th</sup> percentile respectively) were identified at the study sites. The standard deviation (SD) of K<sub>dPAR</sub> and fraction of surface irradiance reaching bottom (PAR<sub>Z</sub>) was used to predict occurrences of eelgrass using Logistic regression (LR) and Support Vector Machine (SVM). The LR and SVM (linear kernel) could predict eelgrass presence-absence with 65 % overall accuracy and precision of 63 % and 62 % respectively on the test set (n = 238). SD correlation with eelgrss occurrences (Point-biserial correlation = -0.11, p = 0.002) and with predicted probabilities of logistic regression (Pearson's r = -0.46) indicates increased K<sub>dPAR</sub> variation reduces chances of eelgrass. The K<sub>dPAR</sub> for this study was derived using Quasi Analytical Algorithm Version-5 (QAA-V5) and Case-2 Regional Coast Colour (C2RCC) and validated against in-situ matched observations (n = 113) for duration of March to October of 2016-2018.

The Science of The Total EnvironmentVol. 965
Technical University of Denmark (DK)
Ministry of Environment, Miljøstyrelsen
Openalex Percentile: Top 10%
Marine and coastal ecosystems
3.59
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