Estamos trabajando para incorporar este artículo al repositorio
Consulte el artículo en la página del editor
Consulte la política de Acceso Abierto del editor


A common approach to the pixel-by-pixel atmospheric correction of satellite water colour imagery is to calculate aerosol and water reflectance at two spectral bands, typically in the near infra-red (NIR, 700-1000 nm) or the short-wave-infra-red (SWIR, 1000-3000 nm), and then extrapolate aerosol reflectance to shorter wavelengths. For clear waters, this can be achieved simply for NIR bands, where the water reflectance can be assumed negligible i.e., the "black water" assumption. For moderately turbid waters, either the NIR water reflectance, which is non-negligible, must be modelled or longer wavelength SWIR bands, with negligible water reflectance, must be used. For extremely turbid waters, modelling of non-zero NIR water reflectance becomes uncertain because the spectral slopes of water and aerosol reflectance in the NIR become similar, making it difficult to distinguish between them. In such waters the use of SWIR bands is definitely preferred and the use of the MODIS bands at 1240 nm and 2130 nm is clearly established although, on many sensors such as the Ocean and Land Colour Instrument (OLCI), such SWIR bands are not included. Instead, a new, cheaper SWIR band at 1016 nm is available on OLCI with potential for much better atmospheric correction over extremely turbid waters. That potential is tested here. In this work, we demonstrate that for spectrally-close band triplets (such as OLCI bands at 779-865-1016 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. We use the three BLRs defined by three consecutive band triplets of the group of bands 620-709-779-865-1016 nm to calculate water reflectance and hence aerosol reflectance at these wavelengths. Comparison with standard atmospheric correction algorithms shows similar performance in moderately turbid and clear waters and a considerable improvement in extremely turbid waters. © 2019 by the authors.


Documento: Artículo
Título:Atmospheric correction of OLCI imagery over extremely turbid waters based on the red, NIR and 1016 nm bands and a new baseline residual technique
Autor:Gossn, J.I.; Ruddick, K.G.; Dogliotti, A.I.
Filiación:Instituto de Astronomía y Física del Espacio (IAFE), CONICET-Universidad de Buenos Aires, Pabellón IAFE, Ciudad Universitaria (C1428ZAA), Ciudad Autónoma de Buenos Aires, Argentina
Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria (C1428ZAA), Ciudad Autónoma de Buenos Aires, Argentina
Remote Sensing and Ecosystem Modelling Team, Operational Directorate Natural Environment, Royal Belgian Institute of Natural Sciences, Rue Vautier 29, Brussels, 1000, Belgium
Pabellón IAFE, Ciudad Universitaria (C1428ZAA), Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
Palabras clave:Atmospheric correction; Extremely turbid waters; OLCI; Remote sensing of ocean colour; Aerosols; Color; Infrared devices; Pixels; Remote sensing; Satellite imagery; Atmospheric conditions; Atmospheric correction algorithm; Atmospheric corrections; OLCI; Remote sensing of ocean; Residual Techniques; Short wave infrared; Turbid water; Reflection
Título revista:Remote Sensing
Título revista abreviado:Remote Sens.


  • Gordon, H.R., Wang, M., Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: A preliminary algorithm (1994) Appl. Opt, 33, pp. 443-452
  • Stumpf, R., Arnone, R., Gould, R., Martinolich, P.M., Ransibrahmanakul, V., A partially coupled ocean-atmosphere model for retrieval of water-leaving radiance from SeaWiFS in coastal waters (2003) NASA Tech. Memo, pp. 51-59
  • Doxaran, D., Froidefond, J.M., Castaing, P., Spectral signature of highly turbid waters: Application with SPOT data to quantify suspended particulate matter concentrations (2002) Remote Sens. Environ, 81, pp. 149-161
  • Ruddick, K., Vanhellement, Q., Use of OLCI and SLSTR Bands for Atmospheric Correction over Turbid Coastal and Inland Waters (2015) In Proceedings of the Sentinel-3 for Science Workshop, 734, p. 55. , Casinò, Italy, 2-5 June
  • Ruddick, K.G., De Cauwer, V., Park, Y.J., Moore, G., Seaborne measurements of near infrared water-leaving reflectance: The similarity spectrum for turbid waters (2006) Limnol. Oceanogr, 51, pp. 1167-1179
  • Lee, Z., Shang, S., Lin, G., Chen, J., Doxaran, D., On the modeling of hyperspectral remote-sensing reflectance of high-sediment-load waters in the visible to shortwave-infrared domain (2016) Appl. Opt, 55, pp. 1738-1750
  • Luo, Y., Doxaran, D., Ruddick, K., Shen, F., Gentili, B., Yan, L., Huang, H., Saturation of water reflectance in extremely turbid media based on field measurements, satellite data and bio-optical modelling (2018) Opt. Express, 26, pp. 10435-10451
  • Dogliotti, A., Ruddick, K., Nechad, B., Lasta, C., ImprovingWater Reflectance Retrieval from MODIS Imagery in the Highly TurbidWaters of La Plata River (2011) Proceedings of the VI International Conference: Current Problems in Optics of Natural Waters (ONW 2011), p. 152. , St. Petersburg, Russia, 6-10 September
  • Wang, M., Shi, W., Estimation of ocean contribution at the MODIS near-infrared wavelengths along the east coast of the US: Two case studies (2005) Geophys. Res. Lett, 32
  • Knaeps, E., Dogliotti, A.I., Raymaekers, D., Ruddick, K., Sterckx, S., In situ evidence of non-zero reflectance in the OLCI 1020nm band for a turbid estuary (2012) Remote Sens. Environ, 120, pp. 133-144
  • Doerffer, R., Schiller, H., The MERIS Case 2 water algorithm (2007) Int. J. Remote Sens, 28, pp. 517-535
  • Chomko, M., Gordon, H., Atmospheric Correction of Ocean Color Imagery: Test of the Spectral Optimization Algorithm with the Sea-Viewing Wide Field-of-View Sensor (2001) Appl. Opt, 40, pp. 2973-2984
  • Steinmetz, F., Deschamps, P.Y., Ramon, D., Atmospheric correction in presence of sun glint: Application to MERIS (2011) Opt. Express, 19, pp. 9783-9800
  • Philpot, W., The derivative ratio algorithm: Avoiding atmospheric effects in remote sensing (1991) IEEE Trans. Geosci. Remote Sens, 29, pp. 350-357
  • Letelier, R., Abbott, M., An analysis of chlorophyll fluorescence algorithms for the Moderate Resolution Imaging Spectrometer (MODIS) (1996) Remote Sens. Environ, 58, pp. 215-223
  • Dogliotti, A., Ruddick, K., Nechad, B., Doxaran, D., Knaeps, E., A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters (2015) Remote Sens. Environ, 156, pp. 157-168
  • Dogliotti, A., Ruddick, K., Guerrero, R., Seasonal and inter-annual turbidity variability in the Río de la Plata from 15 years of MODIS: El Niño dilution effect (2016) Estuar. Coast. Shelf Sci, 182, pp. 27-39
  • Nechad, B., Ruddick, K., Park, Y., Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters (2010) Remote Sens. Environ, 114, pp. 854-866
  • Shen, F., Zhou, Y.X., Li, D.J., Zhu, W.J., Salama, M., Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary (2010) Int. J. Remote Sens, 31, pp. 4635-4650
  • Moreira, D., Simionato, C., Gohin, F., Cayocca, F., Luz Clara, M., Suspended matter mean distribution and seasonal cycle in the Rio de La Plata estuary and the adjacent shelf from ocean color satellite (MODIS) and in-situ observations (2013) Cont. Shelf Res, 68, pp. 51-66
  • Gilerson, A.A., Gitelson, A.A., Zhou, J., Gurlin, D., Moses, W., Ioannou, I., Ahmed, S.A., Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands (2010) Opt. Express, 18, pp. 24109-24125
  • Gitelson, A., The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration (1992) Int. J. Remote Sens, 13, pp. 3367-3373
  • Gons, H.J., Rijkeboer, M., Ruddick, K.G., Effect of a waveband shift on chlorophyll retrieval from MERIS imagery of inland and coastal waters (2005) J. Plankton Res, 27, pp. 125-127
  • Framiñan, M., Brown, O., Study of the Río de la Plata turbidity front, Part 1: Spatial and temporal distribution (1996) Cont. Shelf Res, 16, pp. 1259-1282
  • Mueller, L.J., Morel, A., Frouin, R., Davis, C., Arnone, R., Carder, K., Li, Z., Mobley, C., (2003) Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume III: Radiometric Measurements and Data Analysis Protocols, , Technical Report NASA/TM-2003-21621/Rev-Vol III; NASA Goddard Space Flight Center: Greenbelt, MD, USA
  • Mobley, C.D., Estimation of the remote-sensing reflectance from above-surface measurements (1999) Appl. Opt, 38, pp. 7442-7455
  • Lenoble, J., Herman, M., Deuzé, J.L., Lafrance, B., Santer, R., Tanré, D., A successive order of scattering code for solving the vector equation of transfer in the earth's atmosphere with aerosols (2007) J. Quant. Spectrosc. Radiat. Transf, 107, pp. 479-507
  • Cox, C., Munk, W., Measurement of the Roughness of the Sea Surface from Photographs of the Sun's Glitter (1954) J. Opt. Soc. Am, 44, pp. 838-850
  • Programme, W.C.R., (1986) A Preliminary Cloudless Standard Atmosphere for Radiation Computation, , Technical Report WMO/TD, no. 24.; WCP (Series), 112; International Association of Meteorology and Atmospheric Physics: Boulder, CO, USA
  • Bodhaine, B.A., Slusser, J.R., On Rayleigh Optical Depth Calculations (1999) J. Atmos. Ocean. Technol, 16, pp. 1854-1861
  • Mobley, C., Werdell, J., Franz, B., Ahmad, Z., Bailey, S., (2016) Atmospheric Correction for Satellite Ocean Color Radiometry, , Technical report; NASA Goddard Space Flight Center: Greenbelt, MD, USA
  • EUMETSAT, ,, (accessed on 1 February 2018)
  • (2017) Sentinel-3 Product Notice S3A.PN-OLCI-L2L.02, Issue/Rev Date 06/11/2017, ,, (accessed on 20 November 2017)
  • Gossn, J.I., Effect of Prompt Particle Events on OLCI Ocean Color Imagery in the South Atlantic Anomaly: Detection and Removal (2018) IEEE Geosci. Remote Sens. Lett
  • D'Amico, G., Corsini, M.D., Nieke, J., (2015) Prompt-Particle-Events in ESA's Envisat/MERIS and Sentinel-3/OLCI Data: Observations, Analysis and Recommendations, , Master's Thesis, University of Pisa, Pisa, Italy
  • Bailey, S.W., Franz, B.A., Werdell, P.J., Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing (2010) Opt. Express, 18, pp. 7521-7527
  • Antoine, D., Morel, A., A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument): Principle and implementation for atmospheres carrying various aerosols including absorbing ones (1999) Int. J. Remote Sens, 20, pp. 1875-1916
  • Moore, G.F., Aiken, J., Lavender, S.J., The atmospheric correction of water colour and the quantitative retrieval of suspended particulate matter in Case II waters: Application to MERIS (1999) Int. J. Remote Sens, 20, pp. 1713-1733
  • Hu, C., A novel ocean color index to detect floating algae in the global oceans (2009) Remote Sens. Environ, 113, pp. 2118-2129
  • Gower, J., King, S., Distribution of floating Sargassum in the Gulf of Mexico and the Atlantic Ocean mapped using MERIS (2011) Int. J. Remote Sens, 32, pp. 1917-1929
  • Shettle, E., Fenn, R., Models for the Aerosols of the Lower Atmosphere and the Effects of Humidity Variations on their Optical Properties (1979) Environ. Res. Pap, 676, pp. 1-94
  • S3-OLCI Document Library: Sentinel-3 OLCI-A Spectral Response Functions, ,, (accessed on 11 December 2017)
  • Babin, M., Morel, A., Fournier-Sicre, V., Fell, F., Stramski, D., Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration (2003) Limnol. Oceanogr, 48, pp. 843-859
  • Babin, M., Stramski, D., Ferrari, G.M., Claustre, H., Bricaud, A., Obolensky, G., Hoepffner, N., Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe (2003) J. Geophys. Res, 108, pp. 3211-3231
  • He, X., Bai, Y., Pan, D., Tang, J., Wang, D., Atmospheric correction of satellite ocean color imagery using the ultraviolet wavelength for highly turbid waters (2012) Opt. Express, 20, pp. 20754-20770
  • Ruddick, K.G., Ovidio, F., Rijkeboer, M., Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters (2000) Appl. Opt, 39, pp. 897-912
  • Loisel, H., Morel, A., Non-isotropy of the upward radiance field in typical coastal (Case 2) waters (2001) Int. J. Remote Sens, 22, pp. 275-295
  • Morel, A., Gentili, B., Diffuse reflectance of oceanic waters III. Implication of bidirectionality for the remote-sensing problem (1996) Appl. Opt, 35, pp. 4850-4862
  • Mobley, C.D., (1994) Light andWater: Radiative Transfer in NaturalWaters, , Academic Press: San Diego, CA, USA


---------- APA ----------
Gossn, J.I., Ruddick, K.G. & Dogliotti, A.I. (2019) . Atmospheric correction of OLCI imagery over extremely turbid waters based on the red, NIR and 1016 nm bands and a new baseline residual technique. Remote Sensing, 11(3).
---------- CHICAGO ----------
Gossn, J.I., Ruddick, K.G., Dogliotti, A.I. "Atmospheric correction of OLCI imagery over extremely turbid waters based on the red, NIR and 1016 nm bands and a new baseline residual technique" . Remote Sensing 11, no. 3 (2019).
---------- MLA ----------
Gossn, J.I., Ruddick, K.G., Dogliotti, A.I. "Atmospheric correction of OLCI imagery over extremely turbid waters based on the red, NIR and 1016 nm bands and a new baseline residual technique" . Remote Sensing, vol. 11, no. 3, 2019.
---------- VANCOUVER ----------
Gossn, J.I., Ruddick, K.G., Dogliotti, A.I. Atmospheric correction of OLCI imagery over extremely turbid waters based on the red, NIR and 1016 nm bands and a new baseline residual technique. Remote Sens. 2019;11(3).