Remote Sensing of Turbidity in Optically Shallow Waters Using Sentinel-2 MSI and PRISMA Satellite Data
| Type | : | ACL |
|---|---|---|
| Nature | : | Production scientifique |
| Au bénéfice du Laboratoire | : | Oui |
| Statut de publication | : | Publié |
| Année de publication | : | 2023 |
| Auteurs (4) | : | KATLANE Rim DOXARAN David ELKILANI Boubaker TRABELSI Chaïma |
| Revue scientifique | : | PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science |
| Volume | : | |
| Fascicule | : | |
| Pages | : | |
| DOI | : | 10.1007/s41064-023-00257-9 |
| URL | : | https://doi.org/10.1007/s41064-023-00257-9 |
| Abstract | : | This study aims to improve the retrieval and mapping of turbidity in optically shallow waters using satellite data by detecting then masking bottom-contaminated pixels. The methodology is developed based on multi-spectral Sentinel-2 MSI and hyper-spectral PRISMA high spatial resolution satellite data recorded over the lagoon and bay of Bizerte (Tunisia) and match-ups with field optical measurements. A mask is created to distinguish shallow water (bottom-contaminated) pixels from deep waters or turbid water pixels, using the water-leaving reflectance signal in the near-infrared spectral region (rhow_704 nm) with an empirically derived threshold value of 0.02. Match-ups between field and satellite data clearly identify rhow_560 (green spectral band of Sentinel-2 MSI) as the best proxy for water turbidity in the study area, using a robust empirical regional relationship. The satellite-derived turbidity values show a good agreement with in-situ measurements, with a coefficient of determination (R2) of 0.88 and a root mean square error (RMSE) of 0.122 NTU. These results highlight the reliability and accuracy of the turbidity algorithm, but also the efficiency of the shallow water (bottom contamination) mask, even though conditions with highly turbid waters in the bay or lagoon were not captured on available satellite images. They provide valuable quantitative insights for assessing water quality and improving understanding of the impact of human activities on marine ecosystems. |
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| Commentaire | : | - |
| Tags | : | - |
| Fichier attaché | : | - |
| Citation | : |
Katlane R, Doxaran D, Elkilani B, Trabelsi C (2023) Remote Sensing of Turbidity in Optically Shallow Waters Using Sentinel-2 MSI and PRISMA Satellite Data. PFG - J Photogramm Remote Sens Geoinf Sci | doi: 10.1007/s41064-023-00257-9
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