Retrieval of optically active parameters from oceanic reflectance spectra using multi-layer perceptron and K-Nearest neighbour algorithms

Abstract

Artificial radiance sets, generated with the use of a biooptical and radiative transfer model Hydrolight, corresponding to Case 1 and Case 2 waters, are used as inputs to Multi-layer Perceptron and K-NN algorithms to study the algorithm’s retrieval capabilities for optically active constituents in the water. The radiative transfer model Hydrolight has been used to produce 18,000 artificial reflectance spectra representing various Case 1 and Case 2 water conditions. The remote sensing reflectances were generated at the MERIS wavebands 412, 442, 490, 510, 560, 620, 665 and 682nm from randomly generated triplet combinations of phytoplankton, non-chlorophyllous particles and CDOM concentrations. These reflectances were then used to assess the performance of the KNearest Neighbour and the Multilayer Perceptron algorithms, which were compared to some more traditional band ratio regression algorithms that had been a popular choice for CZCS and SeaWiFS imagery. The objective of the work was to establish the best kind of algorithm for this type of application.

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