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Abstract:

The standard NASA atmospheric correction using near infrared bands (700 nm-900 nm) may work for clear to moderately turbid waters, but generally fails for extreme turbidities because of flattening of the water reflectance spectrum. The use of SWIR bands at 1.6 μm and/or 2.3 μm, such as the bands present on MODIS, can be effective in extremely turbid waters, but may not be present, such as in the case of OLCI (Sentinel 3A), where a new SWIR band at 1016 nm is placed instead. This band may help to improve atmospheric correction in turbid waters at a lower marginal cost than longer SWIR bands. In this work, we endeavored to find 'atmospheric invariant' quantities using the RED/NIR/SWIR bands on OLCI to construct an atmospheric correction scheme over turbid waters. We found that if we choose certain spectrally-close band triplets (such as OLCI bands at 709-779-865 nm), the Rayleigh-corrected reflectance of the triplet's 'middle' band after baseline subtraction (or baseline residual, BLR) is essentially independent of the atmospheric conditions (including for very hazy scenes). In this work, we used three consecutive band triplets of the group of bands 620-709-779-865-1016 nm to construct the three corresponding BLRs and relate them to water reflectances at these wavelengths. To establish this relation, we used a simple water reflectance model for turbid scenarios where we varied backscattering and absorption properties according to previously reported values and the spectral behaviour of in-situ radiometric data from Río de la Plata (Argentina). We also tested the algorithm on a simulated dataset, obtaining good performances (almost 1:1 relation and R2 ≥ 97%) for scenarios without direct sunglint. © 2017 Comisión Permanente RPIC.

Registro:

Documento: Conferencia
Título:Atmospheric correction of OLCI imagery over very turbid waters based on the RED/NIR/SWIR bands
Autor:Gossn, J.I.; Ruddick, K.G.; Dogliotti, A.I.
Filiación:Quantitative Remote Sensing Team, Marine Division, Instituto de Astronomía y Física Del Espacio, Buenos Aires, Argentina
Remote Sensing and Ecosystem Modelling, Operational Natural Environment, Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Palabras clave:atmospheric correction; OLCI; turbid waters; Infrared devices; Infrared radiation; NASA; Reflection; Absorption property; Atmospheric conditions; Atmospheric correction schemes; Atmospheric corrections; Near infrared band; OLCI; Turbid water; Water reflectances; Water absorption
Año:2017
Volumen:2017-January
Página de inicio:1
Página de fin:6
DOI: http://dx.doi.org/10.23919/RPIC.2017.8214356
Título revista:17th Workshop on Information Processing and Control, RPIC 2017
Título revista abreviado:Workshop Inf. Process. Control, RPIC
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97898754_v2017-January_n_p1_Gossn

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Citas:

---------- APA ----------
Gossn, J.I., Ruddick, K.G. & Dogliotti, A.I. (2017) . Atmospheric correction of OLCI imagery over very turbid waters based on the RED/NIR/SWIR bands. 17th Workshop on Information Processing and Control, RPIC 2017, 2017-January, 1-6.
http://dx.doi.org/10.23919/RPIC.2017.8214356
---------- CHICAGO ----------
Gossn, J.I., Ruddick, K.G., Dogliotti, A.I. "Atmospheric correction of OLCI imagery over very turbid waters based on the RED/NIR/SWIR bands" . 17th Workshop on Information Processing and Control, RPIC 2017 2017-January (2017) : 1-6.
http://dx.doi.org/10.23919/RPIC.2017.8214356
---------- MLA ----------
Gossn, J.I., Ruddick, K.G., Dogliotti, A.I. "Atmospheric correction of OLCI imagery over very turbid waters based on the RED/NIR/SWIR bands" . 17th Workshop on Information Processing and Control, RPIC 2017, vol. 2017-January, 2017, pp. 1-6.
http://dx.doi.org/10.23919/RPIC.2017.8214356
---------- VANCOUVER ----------
Gossn, J.I., Ruddick, K.G., Dogliotti, A.I. Atmospheric correction of OLCI imagery over very turbid waters based on the RED/NIR/SWIR bands. Workshop Inf. Process. Control, RPIC. 2017;2017-January:1-6.
http://dx.doi.org/10.23919/RPIC.2017.8214356