Title :

Evaluation of Five Atmospheric Correction Algorithms over French Optically-Complex Waters for the Sentinel-3A OLCI Ocean Color Sensor

Author(s) :

Mograne, Mohamed [Auteur]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Jamet, Cédric [Auteur]
Université du Littoral Côte d'Opale [ULCO]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Loisel, Hubert [Auteur]
Université du Littoral Côte d'Opale [ULCO]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Vantrepotte, Vincent [Auteur]
Université du Littoral Côte d'Opale [ULCO]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Meriaux, Xavier [Auteur]
Université du Littoral Côte d'Opale [ULCO]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Cauvin, Arnaud [Auteur]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]

Journal title :

Remote Sensing
Special Issue Sentinel-3 Satellites: A Three-Sensor Mission to Observe the Physical, Bio-Optical and Biogeochemical Properties of Marine/Water Bodies

Pages :

668

Publisher :

MDPI

Publication date :

2019

ISSN :

2072-4292

English keyword(s) :

ocean color
OLCI
Sentinel-3
match-ups exercise
coastal waters
validation
water-leaving reflectance
ASD
atmospheric correction
sensitivity study

HAL domain(s) :

Planète et Univers [physics]/Sciences de la Terre/Océanographie

English abstract : [en]

The Sentinel-3A satellite was launched on 16 February 2016 with the Ocean and Land Colour Instrument (OLCI-A) on-board for the study of ocean color. The accuracy of ocean color parameters depends on the atmospheric correction ...
Show more >The Sentinel-3A satellite was launched on 16 February 2016 with the Ocean and Land Colour Instrument (OLCI-A) on-board for the study of ocean color. The accuracy of ocean color parameters depends on the atmospheric correction algorithm (AC). This processing consists of removing the contribution of the atmosphere from the total measured signal by the remote sensor at the top of the atmosphere. Five ACs: the baseline AC, the Case 2 regional coast color neural network AC, its alternative version, the Polymer AC, and the standard NASA AC, are inter-compared over two bio-optical contrasted French coastal waters. The retrieved water-leaving reflectances are compared with in situ ocean color radiometric measurements collected using an ASD FielSpec4 spectrometer. Statistical and spectral analysis were performed to assess the best-performing AC through individual (relative error (RE) at 412 nm ranging between 23.43 and 57.31%; root mean squared error (RMSE) at 412 nm ranging between 0.0077 and 0.0188) and common (RE(412 nm) = 24.15–50.07%; RMSE(412 nm) = 0.0081–0.0132) match-ups. The results suggest that the most efficient schemes are the alternative version of the Case 2 regional coast color neural network AC with RE(412 nm) = 33.52% and RMSE(412 nm) = 0.0101 for the individual and Polymer with RE(412 nm) = 24.15% and RMSE(412 nm) = 0.0081 for the common ACs match-ups. Sensitivity studies were performed to assess the limitations of the AC, and the errors of retrievals showed no trends when compared to the turbidity and CDOM. View Full-TextShow less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Laboratoire d'Océanologie et de Géosciences (LOG) - UMR 8187

Source :

Harvested from HAL