Retrieval of Oceanic Chlorophyll Concentration Using Support Vector Machines

This letter investigates the possibility of using a new universal approximator--support vector machines (SVMs)--as the nonlinear transfer function between oceanic chlorophyll concentration and marine reflectance. The SeaBAM dataset is used to evaluate the proposed approach. Experimental results show that the SVM performs as well as the optimal multilayer perceptron (MLP) and can be a promising alternative to the conventional MLPs for the retrieval of oceanic chlorophyll concentration from marine reflectance.