CHLOROPHYLL ESTIMATION OF LAKE WATER AND COASTAL WATER USING LANDSAT-8 AND SENTINEL-2A SATELLITE

20 citations as recorded by crossref.

1. Coastal-to-offshore submesoscale horizontal stirring enhances wintertime phytoplankton blooms in the ultra-oligotrophic Eastern Mediterranean Sea Y. Fadida et al. https://doi.org/10.5194/os-22-329-2026
2. Spatiotemporal Analysis of Water Quality Conditions in High-Andean Lakes Based on Satellite Indicators Using Sentinel 2 and Landsat 8/9 Images V. Cantos et al. https://doi.org/10.3390/w17213145
3. Current and emerging techniques for oceanic and lake chlorophyll-a estimation and monitoring: a global perspective R. Jena et al. https://doi.org/10.1007/s10661-026-15116-4
4. Improved water quality mapping based on cross‐fusion of Sentinel‐2 and Landsat‐8 imageries K. Rangzan et al. https://doi.org/10.1049/iet-ipr.2019.1503
5. Assessment of some water quality parameters in the Red River downstream, Vietnam by combining field monitoring and remote sensing method T. Tham et al. https://doi.org/10.1007/s11356-021-16730-0
6. Monitoring the Water Quality of Small Water Bodies Using High-Resolution Remote Sensing Data Z. Yigit Avdan et al. https://doi.org/10.3390/ijgi8120553
7. Application of Landsat-8 and Sentinel-2 for retrieval of chlorophyll-a in a shallow freshwater lake B. Karimi et al. https://doi.org/10.1016/j.asr.2024.03.056
8. Accurate and robust estimation of TDS, TOC, Chl-a and surface water temperature using Landsat-8, Sentinel-2, MODIS, and ASTER sensors A. Quevedo-Castro et al. https://doi.org/10.1007/s10661-025-14868-9
9. Development and Application of Miniaturized Multispectral Detection System for Water Reflection Detection Y. Song et al. https://doi.org/10.3390/s25247675
10. Comparison of multi-source satellite data for quantifying water quality parameters in a mining environment M. Modiegi et al. https://doi.org/10.1016/j.jhydrol.2020.125322
11. Detection and mapping of water and chlorophyll-a spread using Sentinel-2 satellite imagery for water quality assessment of inland water bodies A. Latwal et al. https://doi.org/10.1007/s10661-023-11874-7
12. Automatic water detection from multidimensional hierarchical clustering for Sentinel-2 images and a comparison with Level 2A processors M. Cordeiro et al. https://doi.org/10.1016/j.rse.2020.112209
13. Modeling and mapping trophic factors at deltaic Mediterranean Sea coast in Egypt using satellite imageries and statistical analyses D. Darwish et al. https://doi.org/10.1007/s12517-021-08650-7
14. Application of Optical Remote Sensing in Harmful Algal Blooms in Lakes: A Review S. Wang & B. Qin https://doi.org/10.3390/rs17081381
15. Assessment of chlorophyll-a using multiple and ratio bands algorithm in Sentinel-2: A case study in the coastal areas of Semarang L. Maslukah et al. https://doi.org/10.1016/j.ejrs.2026.05.004
16. Potential of Remote Sensing for Improved Understanding of Aquatic Chlorophyll, Biomass and Primary Productivity Estimation R. Gupta et al. https://doi.org/10.5958/2319-1198.2022.00006.9
17. Micro-Climate Computed Machine and Deep Learning Models for Prediction of Surface Water Temperature Using Satellite Data in Mundan Water Reservoir S. Mukonza & J. Chiang https://doi.org/10.3390/w14182935
18. Expanding the Application of Sentinel-2 Chlorophyll Monitoring across United States Lakes W. Salls et al. https://doi.org/10.3390/rs16111977
19. Seasonal Monitoring Of Chlorophyll-A With Landsat 8 Oli In The Madura Strait, Pasuruan, East Java, Indonesia A. Darmawan et al. https://doi.org/10.24057/2071-9388-2020-199
20. An Integrated Model of Summer and Winter for Chlorophyll-a Retrieval in the Pearl River Estuary Based on Hyperspectral Data H. Li et al. https://doi.org/10.3390/rs14092270