A supervised global water classifier followed by XGBoost regression and a residual CNN stage produces chlorophyll-a retrievals with R²=0.79 across 867 water bodies using Sentinel-2 reflectance matched to in-situ data.
Controlling harmful cyanobacterial blooms in a world experiencing anthropogenic and climatic- induced change.Science of The Total Environment, 409(10):1739–1745
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Global Chlorophyll-\textit{a} Retrieval algorithm from Sentinel 2 Using Residual Deep Learning and Novel Machine Learning Water Classification
A supervised global water classifier followed by XGBoost regression and a residual CNN stage produces chlorophyll-a retrievals with R²=0.79 across 867 water bodies using Sentinel-2 reflectance matched to in-situ data.