Modification to the atmospheric correction of SeaWiFS ocean colour images over turbid waters

Lavender, Samantha; Pinkerton, Matthew H.; Moore, Gerald; Aiken, James; Blondeau-Patissier, David

doi:10.1016/j.csr.2004.10.007

Cited by 124 publications

(71 citation statements)

References 26 publications

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“…Without knowing the concentration and size of aerosol in the path T cannot be calculated; the aerosol quantities can vary significantly over time scales of days and space scales of a few kilometers [26].…”

Section: Radiative Transfer Processesmentioning

confidence: 99%

“…For example, water is a good absorber of NIR radiation [23], so the water-leaving radiance is often assumed to be zero for these wavelengths [2,24]. However, this may not be true if the water is shallow or turbid [25,26]. It is particularly difficult to distinguish between sun glint and light scattered by aerosols, i.e., particles suspended in the air, for two reasons:…”

Section: Radiative Transfer Processesmentioning

confidence: 99%

“…The wavelength dependence of sun glint is through variation in the refractive index (see Equations 12 and 28)-for pure water this varies from 1.339 at 400 nm to 1.328 at 900 nm [27], while for sea water it varies from 1.35 at 400 nm to 1.34 at 700 nm [28]. The aerosol reflectance varies as λ α , where α is the Angström exponent, whose value varies from about +1 to −2 depending on environmental conditions [26]. Typical maritime values are 0.3-1.0 [29]; for low values, corresponding to large aerosols, the wavelength dependence is weak.…”

Section: Radiative Transfer Processesmentioning

confidence: 99%

See 2 more Smart Citations

Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths

2009

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Sun glint, the specular reflection of light from water surfaces, is a serious confounding factor for remote sensing of water column properties and benthos. This paper reviews current techniques to estimate and remove the glint radiance component from imagery. Methods for processing of ocean color images use statistical sea surface models to predict the glint from the sun and sensor positions and wind data. Methods for higher resolution imaging, used in coastal and shallow water mapping, estimate the glint radiance from the near-infrared signal. The effects of some current methods are demonstrated and possibilities for future techniques are briefly addressed.

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Section: Radiative Transfer Processesmentioning

confidence: 99%

Section: Radiative Transfer Processesmentioning

confidence: 99%

Section: Radiative Transfer Processesmentioning

confidence: 99%

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Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths

2009

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“…Title: Understanding and managing complex transnational river -sea systems: problems and opportunities in the Danube -Black Sea waters, particle scattering dominates the red spectrum confounding the accurate atmospheric correction of satellite data and the retrieval of phytoplankton absorption and pigment concentrations in these wavelengths (Dekker et al, 1997;Lavender et al, 2005;Ruddick et al, 2000;Morel & Bélanger, 2006).…”

Section: Special Issue Science Of the Total Environmentmentioning

confidence: 99%

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

Tyler

Hunter

Spyrakos

et al. 2016

Science of The Total Environment

120

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The Earth's surface waters are a fundamental resource and encompass a broad range of ecosystems that are core to global biogeochemical cycling and food and energy production.Despite this, the Earth's surface waters are impacted by multiple natural and anthropogenic pressures and drivers of environmental change. The complex interaction between physical, chemical and biological processes in surface waters poses significant challenges for in situ monitoring and assessment and often limits our ability to adequately capture the dynamics of aquatic systems and our understanding of their status, functioning and response to pressures. Here we explore the opportunities that Earth observation (EO) has to offer to basin-scale monitoring of water quality over the surface water continuum comprising inland, transition and coastal water bodies, with a particular focus on the Danube and Black Sea region. This review summarises the technological advances in EO and the opportunities that the next generation satellites offer for water quality monitoring. We provide an overview of algorithms for the retrieval of water quality parameters and demonstrate how such models have been used for the assessment and monitoring of inland, transitional, coastal and shelfsea systems. Further, we argue that very few studies have investigated the connectivity between these systems especially in large river-sea systems such as the Danube-Black Sea. Subsequently, we describe current capability in operational processing of archive and near real-time satellite data. We conclude that while the operational use of satellites for the assessment and monitoring of surface waters is still developing for inland and coastal waters and more work is required on the development and validation of remote sensing algorithms for these optically complex waters, the potential that these data streams offer for developing an improved, potentially paradigm-shifting understanding of physical and biogeochemical processes across large scale river-sea continuum including the Danube-Black Sea is considerable.

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“…To overcome the black pixel assumption that progressively degrades L w signals with increasing suspended load (SS) and algal blooms in nearshore waters, a number of authors have proposed modifications to account for non-negligible L w (λ NIR1 and λ NIR2 ) within the framework of the SeaDAS atmospheric correction algorithm (Arnone et al, 1998;Ruddick et al, 2000;Hu et al, 2000;Stumpf et al, 2003;Lavender et al, 2005). Relaxing the black pixel assumption through these modifications in the correction of satellite ocean colour data has shown significant improvements in the L w (λ) and Chl-a retrievals under normal circumstances (i.e.…”

Section: Introductionmentioning

confidence: 99%

CAAS: an atmospheric correction algorithm for the remote sensing of complex waters

Shanmugam

2012

Ann. Geophys.

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Abstract. The current SeaDAS atmospheric correction algorithm relies on the computation of optical properties of aerosols based on radiative transfer combined with a nearinfrared (NIR) correction scheme (originally with assumptions of zero water-leaving radiance for the NIR bands) and several ancillary parameters to remove atmospheric effects in remote sensing of ocean colour. The failure of this algorithm over complex waters has been reported by many recent investigations, and can be attributed to the inadequate NIR correction and constraints for deriving aerosol optical properties whose characteristics are the most difficult to evaluate because they vary rapidly with time and space. The possibility that the aerosol and sun glint contributions can be derived in the whole spectrum of ocean colour solely from a knowledge of the total and Rayleigh-corrected radiances is developed in detail within the framework of a Complex water Atmospheric correction Algorithm Scheme (CAAS) that makes no use of ancillary parameters. The performance of the CAAS algorithm is demonstrated for MODIS/Aqua imageries of optically complex waters and yields physically realistic water-leaving radiance spectra that are not possible with the SeaDAS algorithm. A preliminary comparison with in-situ data for several regional waters (moderately complex to clear waters) shows encouraging results, with absolute errors of the CAAS algorithm closer to those of the SeaDAS algorithm. The impact of the atmospheric correction was also examined on chlorophyll retrievals with a Case 2 water bio-optical algorithm, and it was found that the CAAS algorithm outperformed the SeaDAS algorithm in terms of producing accurate pigment estimates and recovering areas previously flagged out by the later algorithm. These findings suggest that the CAAS algorithm can be used for applications focussing in quantitative assessments of the biological and biogeochemical properties in complex waters, and can easily be extended to other sensors such as OCM-2, MERIS and GOCI.

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Modification to the atmospheric correction of SeaWiFS ocean colour images over turbid waters

Cited by 124 publications

References 26 publications

Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths

Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

CAAS: an atmospheric correction algorithm for the remote sensing of complex waters

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