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

17 citations as recorded by crossref.

1. Use of Sentinel-2 optical imagery for the reconstruction of coastal bathymetry: a case study in Mozambique F. Varni et al. https://doi.org/10.1080/22797254.2025.2532543
2. Performance Evaluation of Gradient Descent Optimizers in Estuarine Turbidity Estimation with Multilayer Perceptron and Sentinel-2 Imagery N. Ndou & N. Nontongana https://doi.org/10.3390/hydrology11100164
3. An Approach for Monitoring Chlorophyll-A and Turbidity Levels in Saduperi and Kaveripakkam Lakes Located in and Around Vellore Region, Tamil Nadu, India, Using Spectral Unmixing Technique M. Raghul & P. Porchelvan https://doi.org/10.1007/s12524-024-02019-5
4. Integration of Machine Learning and Remote Sensing for Water Quality Monitoring and Prediction: A Review S. Mohan et al. https://doi.org/10.3390/su17030998
5. A Study of Abrasive Solid Particles Erosion for a Centrifugal Pump Operated as a Pump and as a Turbine Using Computational Fluid Dynamics J. El Mansour et al. https://doi.org/10.3390/pr14040707
6. Atmospheric Correction Algorithms Assessment for Sentinel-2A Imagery over Inland Waters of China: Case Study, Qiandao Lake M. Allam et al. https://doi.org/10.1007/s41748-023-00366-w
7. Beyond Accuracy: Transferability Limits, Validation Inflation, and Uncertainty Gaps in Satellite-Based Water Quality Monitoring—A Systematic Quantitative Synthesis and Operational Framework S. Pourmorad et al. https://doi.org/10.3390/rs18071098
8. Evaluation of machine learning methods for forecasting turbidity in river networks using Sentinel-2 remote sensing data V. Santos et al. https://doi.org/10.1016/j.ecoinf.2025.103313
9. Machine learning-driven SSC retrieval in the high-turbidity lower Yellow River leveraging a novel red-edge and narrow NIR band synergy G. Shen et al. https://doi.org/10.1016/j.ijsrc.2026.07.001
10. Assessing the effects of land use on water turbidity in a fluvial lake floodplain using Sentinel-2 imagery J. Ziyad et al. https://doi.org/10.2166/wqrj.2025.009
11. Paint it black: Chronic whiting event degrades bottom communities in a Mediterranean coastal lagoon V. Orenes-Salazar et al. https://doi.org/10.1016/j.marpolbul.2026.120106
12. Machine Learning Algorithms for Acid Mine Drainage Mapping Using Sentinel-2 and Worldview-3 F. Farahnakian et al. https://doi.org/10.3390/rs16244680
13. Crop Identification with Monte Carlo Simulations and Rotation Models from Sentinel-2 Data A. Racoviteanu et al. https://doi.org/10.3390/agriengineering7080259
14. Retrieval of Underwater Turbidity in Gyeonggi Bay Using Sentinel-2 Satellite Data S. Kim et al. https://doi.org/10.5467/JKESS.2023.44.5.469
15. Sea Water Turbidity Variability and Relation to Tides and Environmental Factors in the Korean Coastal Region of the Yellow Sea S. Kim et al. https://doi.org/10.1007/s12601-024-00183-w
16. From multi-scale observations to integrated applications: a review of remote sensing for inland water quality monitoring D. Xu et al. https://doi.org/10.3389/fenvs.2026.1832807
17. AI-Driven Time Series Forecasting of Coastal Water Quality Using Sentinel-2 Imagery: A Case Study in the Gulf of Thailand A. Sukkuea et al. https://doi.org/10.3390/w17121798