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Proceedings Paper

Simulation of the MERIS instrument and constituent estimation
Author(s): Daniel J. Buckton; Sean Danaher; Eon O'Mongain
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Paper Abstract

A simulation is defined and tested for oceanic constituent estimation in case II waters, for the future medium resolution imaging spectrometer (MERIS) oceanic remote sensing instrument, using singular valued decomposition (SVD) and artificial neural networks (ANN) inversion techniques. The SVD technique, which bears a close resemblance to multivariate statistic techniques has previously been successfully applied to the problem of chlorophyll estimation from case I waters. In this study, a model is developed for the calculation of oceanic surface reflectance, as a function of the three major constituents which contribute to the optical properties of the water, (chlorophyll like pigments, yellow substance and sediments). The oceanic models have been validated using optical data acquired in the North Sea (1994) using the MARAS instrument. This surface reflectance is used to predict top of atmosphere radiance, which is then inputted to the MERIS instrument model. The algorithms are implemented on the simulated data to provide robust algorithms for the estimation of chlorophyll, sediment and yellow substance concentrations. The results of this investigation are presented with emphasis on recommendations for algorithm development, pre-processing and sampling strategies.

Paper Details

Date Published: 18 December 1995
PDF: 12 pages
Proc. SPIE 2586, Global Process Monitoring and Remote Sensing of the Ocean and Sea Ice, (18 December 1995); doi: 10.1117/12.228611
Show Author Affiliations
Daniel J. Buckton, Leeds Metropolitan Univ. (United Kingdom)
Sean Danaher, Leeds Metropolitan Univ. (United Kingdom)
Eon O'Mongain, Univ. College Dublin (Ireland)

Published in SPIE Proceedings Vol. 2586:
Global Process Monitoring and Remote Sensing of the Ocean and Sea Ice
Donald W. Deering; Preben Gudmandsen, Editor(s)

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