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|Title:||Performance and applicability of bio-optical algorithms in different European seas|
|Authors:||D'ALIMONTE Davide; ZIBORDI Giuseppe; BERTHON Jean-Francois; CANUTI Elisabetta; KAJIYAMA Tamito|
|Citation:||REMOTE SENSING OF ENVIRONMENT vol. 124 p. 402-412|
|Publisher:||ELSEVIER SCIENCE INC|
|Type:||Articles in periodicals and books|
|Abstract:||Multi Layer Perceptron (MLP) neural networks for regional satellite ocean color applications have been developed and assessed using in situ data from various European seas. Considered MLP products are chlorophyll a concentration (Chl-a), absorption by yellow substance at 412 nm (ays(412)) and concentration of Total Suspended Matter (TSM), all determined from spectral remote sensing reflectance RRS . Investigated oceanographic regions comprise the Eastern Mediterranean Sea, the northern Adriatic Sea, the Western Black Sea and the Baltic Sea. The in situ measurements applied in the study were produced within the framework of the Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical mapping of Marine Properties (BiOMaP) programs. Peculiarity of this reference dataset is the capability of representing different water types including chlorophyll a, yellow substance and sediment dominated waters. has been investigated through cross-basin product analysis and a practical solution is proposed. Performance analysis of the proposed regional MLPs indicates that Chl-a can be quantified with the highest accuracy in the Eastern Mediterranean Sea (with absolute percent difference of 14%). In the case of ays(412), the most accurate determinations are observed for the Baltic Sea waters (13 %). Instead TSM retrieval is the most accurate in the Black Sea (14 %). The saturation of MLP output occurring with input data not statistically represented in the training set,|
|JRC Institute:||Sustainable Resources|
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