Bayesian Neural Networks for Estimating Chlorophyll-A Concentration Based on Satellite-Derived Ocean Colour Observations
Mohamad Abed El Rahman Hammoud,
Nikolaos Papagiannopoulos,
Robert J.W. Brewin
et al.
Abstract:This study explores the use of Bayesian Neural Networks (BNNs) for estimating chlorophyll-a concentration ([CHL-a]) from remotely sensed data. The BNN model enables uncertainty quantification, offering additional layers of information compared to traditional ocean colour models. An extensive in situ bio-optical dataset is utilized, generated by merging 27 data sources across the world’s oceans. The BNN model demonstrates remarkable capability in capturing mesoscale features and ocean circulation patterns, prov… Show more
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