Estimation of Ocean Water Chlorophyll-a Concentration Using Fuzzy C-means Clustering and Artificial Neural Networks

A system incorporating a fuzzy c-means clustering and an ensemble of artificial neural networks (ANNs) is proposed to estimate chlorophyll-a (Chl a) concentration from remotely sensed reflectance (Rrs) measurements. The proposed method can be used to estimate Chl a concentration from Rrs measured at various locations representing heterogeneous water types. The performance of the proposed method is compared with the traditional approach, where a single ANN is used for all water types. We showed that the cluster-based approach has the potential to build a more global Chl a prediction model.