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Developing daily gap-filled chlorophyll-a datasets using deep neural networks with co-located environmental variables
Published 2024“…Other environmental information (such as winds and sea surface temperature) is available and can be highly correlated with Chl-a due to the physical processes that drive nutrient loading and Chl-a movement. …”