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.
Phytoplankton pigment dynamics in lake kinneret determined using hplc and remote sensing.Journal of Plankton Research, 33(8):1233–1243, 2011
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.geo-ph 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.