Abstract:
The quality of information provided by ocean color imagery relies on the availability of an accurate atmospheric correction algorithm, which turns to be more complicated in highly turbid coastal regions, such as in the Río de la Plata River (RdP) (Argentina-Uruguay). In these waters, the usual black pixel assumption in the Near Infra-Red (NIR, 700-1000 nm) bands is often invalid due to high backscattering from suspended particulate matter (SPM) present in the water. In this work, an atmospheric correction scheme is presented to estimate water reflectance in the 865 nm NIR band. This scheme is based on shifting the black pixel assumption to the Short-Wave-Infra-Red (SWIR, 1000-3000 nm) bands and a Principal Component Analysis (PCA) decomposition of simulated atmosphere-interface reflectances. To estimate the latter component in the top of atmosphere (TOA) signal, the weight of each of these PCA eigenvectors is determined from the SWIR bands in a per-pixel-basis. The algorithm was theoretically tested from a set of simulated TOA reflectances performed considering atmospheric conditions and in-situ water reflectance data from RdP. Four schemes were analyzed using different sets of SWIR bands present in MODIS and SABIA-Mar (future Argentinian-Brazilian ocean color mission) sensors. These sets differ from each other in their correlation to the NIR and the validity of the black pixel assumption. Without considering instrument noise, the scheme with better performance is the one in which water reflectance is negligible in the SWIR bands considered: 1640 nm (SABIA-Mar/MODIS) and 2130 nm (MODIS). © 2016 IEEE.
Registro:
| Documento: |
Conferencia
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| Título: | SWIR-based atmospheric correction for Satellite Ocean Color using Principal Component Analysis decomposition over the la Plata River highly turbid waters |
| Autor: | Gossn, J.I.; Frouin, R.; Dogliotti, A.I.; Grings, F.M. |
| Filiación: | Quantitative Remote Sensing Group, Marine Division, Instituto de Astronomía y Física Del Espacio, CONICET-UBA, Pabellón IAFE, Ciudad Universitaria, Int. Güiraldes 2620, Buenos Aires, C1428ZAA, Argentina
Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, San Diego, CA 92037, United States
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| Palabras clave: | Color; Infrared devices; Pixels; Radiometers; Reflection; Atmospheric conditions; Atmospheric correction algorithm; Atmospheric correction schemes; Atmospheric corrections; Quality of information; Satellite Ocean Color; Short wave infrared; Suspended particulate matters; Principal component analysis |
| Año: | 2016
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| DOI: |
http://dx.doi.org/10.1109/ARGENCON.2016.7585311 |
| Título revista: | 2016 IEEE Biennial Congress of Argentina, ARGENCON 2016
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| Título revista abreviado: | IEEE Bienn. Congr. Argent., ARGENCON
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| Registro: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814673_v_n_p_Gossn |
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Citas:
---------- APA ----------
Gossn, J.I., Frouin, R., Dogliotti, A.I. & Grings, F.M.
(2016)
. SWIR-based atmospheric correction for Satellite Ocean Color using Principal Component Analysis decomposition over the la Plata River highly turbid waters. 2016 IEEE Biennial Congress of Argentina, ARGENCON 2016.
http://dx.doi.org/10.1109/ARGENCON.2016.7585311---------- CHICAGO ----------
Gossn, J.I., Frouin, R., Dogliotti, A.I., Grings, F.M.
"SWIR-based atmospheric correction for Satellite Ocean Color using Principal Component Analysis decomposition over the la Plata River highly turbid waters"
. 2016 IEEE Biennial Congress of Argentina, ARGENCON 2016
(2016).
http://dx.doi.org/10.1109/ARGENCON.2016.7585311---------- MLA ----------
Gossn, J.I., Frouin, R., Dogliotti, A.I., Grings, F.M.
"SWIR-based atmospheric correction for Satellite Ocean Color using Principal Component Analysis decomposition over the la Plata River highly turbid waters"
. 2016 IEEE Biennial Congress of Argentina, ARGENCON 2016, 2016.
http://dx.doi.org/10.1109/ARGENCON.2016.7585311---------- VANCOUVER ----------
Gossn, J.I., Frouin, R., Dogliotti, A.I., Grings, F.M. SWIR-based atmospheric correction for Satellite Ocean Color using Principal Component Analysis decomposition over the la Plata River highly turbid waters. IEEE Bienn. Congr. Argent., ARGENCON. 2016.
http://dx.doi.org/10.1109/ARGENCON.2016.7585311