Polarized reflectance and transmittance properties of windblown sea surfaces

Mobley, Curtis D.

doi:10.1364/ao.54.004828

Cited by 138 publications

(142 citation statements)

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“…where, r sky is the air-water interface reflection coefficient that minimizes skylight reflection effects, and can be obtained in Mobley [38] as a function of a given view zenith and azimuth angles (θ v ; φ v ), sun zenith angle (θ 0 ) and wind speed W (m/s). In-situ R w * spectra were weighted by spectral response functions SRF(λ) of MSI bands, thus deriving a multi-spectral data comparable to atmospherically corrected MSI-reflectance from image.…”

Section: Site Description and Field Datamentioning

confidence: 99%

Assessment of Atmospheric Correction Methods for Sentinel-2 MSI Images Applied to Amazon Floodplain Lakes

et al. 2017

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Satellite data provide the only viable means for extensive monitoring of remote and large freshwater systems, such as the Amazon floodplain lakes. However, an accurate atmospheric correction is required to retrieve water constituents based on surface water reflectance (R W ). In this paper, we assessed three atmospheric correction methods (Second Simulation of a Satellite Signal in the Solar Spectrum (6SV), ACOLITE and Sen2Cor) applied to an image acquired by the MultiSpectral Instrument (MSI) on-board of the European Space Agency's Sentinel-2A platform using concurrent in-situ measurements over four Amazon floodplain lakes in Brazil. In addition, we evaluated the correction of forest adjacency effects based on the linear spectral unmixing model, and performed a temporal evaluation of atmospheric constituents from Multi-Angle Implementation of Atmospheric Correction (MAIAC) products. The validation of MAIAC aerosol optical depth (AOD) indicated satisfactory retrievals over the Amazon region, with a correlation coefficient (R) of~0.7 and 0.85 for Terra and Aqua products, respectively. The seasonal distribution of the cloud cover and AOD revealed a contrast between the first and second half of the year in the study area. Furthermore, simulation of top-of-atmosphere (TOA) reflectance showed a critical contribution of atmospheric effects (>50%) to all spectral bands, especially the deep blue (92%-96%) and blue (84%-92%) bands. The atmospheric correction results of the visible bands illustrate the limitation of the methods over dark lakes (R W < 1%), and better match of the R W shape compared with in-situ measurements over turbid lakes, although the accuracy varied depending on the spectral bands and methods. Particularly above 705 nm, R W was highly affected by Amazon forest adjacency, and the proposed adjacency effect correction minimized the spectral distortions in R W (RMSE < 0.006). Finally, an extensive validation of the methods is required for distinct inland water types and atmospheric conditions.

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Section: Site Description and Field Datamentioning

confidence: 99%

Assessment of Atmospheric Correction Methods for Sentinel-2 MSI Images Applied to Amazon Floodplain Lakes

et al. 2017

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“…To minimize the near-surface effects such as sun glint, platform shadowing and sea spray, angles of θ v " 40˝and 90˝ă φ ă 135˝(ideally 135˝) are considered suitable for ship-borne above-water radiometry [5,6,9,11,13,21,23]. Under these optimized viewing angles, ρ varies between 2.5%-8% at 550 nm with varying sea surface roughness and cloud cover [9,11,13,24].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Garaba, Voss, Wollschlager and Zielinski [17] proposed a multi-model average of four approaches to retrieve the best approximation of R rs . Recently Mobley [24] proposed a revised ρ table (M15 hereafter) computed using elevation-and slope-resolving surfaces and polarized ray tracing.…”

Section: The Dalec Instrumentmentioning

confidence: 99%

“…As wind speed is not logged on RV Solander, a constant W = 3 ms´1 was used in all analyses shown above to select ρ pθ v " 40˝, φ, θ s , Wq from the Mobley [24] tabulated ρ. To evaluate the effect of this assumption, all instantaneous R rs were also calculated with W = 1 ms´1 and W = 5 ms´1 for comparison.…”

Section: Sensitivity To Dalec Processing Parametersmentioning

confidence: 99%

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The Potential of Autonomous Ship-Borne Hyperspectral Radiometers for the Validation of Ocean Color Radiometry Data

et al. 2016

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Calibration and validation of satellite observations are essential and on-going tasks to ensure compliance with mission accuracy requirements. An automated above water hyperspectral radiometer significantly augmented Australia's ability to contribute to global and regional ocean color validation and algorithm design activities. The hyperspectral data can be re-sampled for comparison with current and future sensor wavebands. The continuous spectral acquisition along the ship track enables spatial resampling to match satellite footprint. This study reports spectral comparisons of the radiometer data with Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua for contrasting water types in tropical waters off northern Australia based on the standard NIR atmospheric correction implemented in SeaDAS. Consistent match-ups are shown for transects of up to 50 km over a range of reflectance values. The MODIS and VIIRS satellite reflectance data consistently underestimated the in situ spectra in the blue with a bias relative to the "dynamic above water radiance and irradiance collector" (DALEC) at 443 nm ranging from 9.8ˆ10´4 to 3.1ˆ10´3 sr´1. Automated acquisition has produced good quality data under standard operating and maintenance procedures. A sensitivity analysis explored the effects of some assumptions in the data reduction methods, indicating the need for a comprehensive investigation and quantification of each source of uncertainty in the estimate of the DALEC reflectances. Deployment on a Research Vessel provides the potential for the radiometric data to be combined with other sampling and observational activities to contribute to algorithm development in the wider bio-optical research community.

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“…Furthermore, in the framework of the preparation of future polarimetric and multidirectional satellite sensors such as the forthcoming mission "Multi-Viewing, Multi-Channel, Multi-Polarization Imaging Mission-3MI" (ESA/Eumetsat), or the "Pre-Aerosol, Clouds, and ocean Ecosystem-PACE" mission (NASA), it is important to have appropriate radiative transfer models that predict accurately the radiance and polarization properties to build robust inverse remote sensing algorithms. The consideration of a rough sea surface remains a challenging task due to the complexity of the optical mechanisms affecting the photons along their pathways in the coupled atmosphere-ocean system [24][25][26]. To our knowledge, only a few vector radiative transfer models considering the rough sea surface are currently devoted to ocean color remote sensing purposes [14,17,18,20,26].…”

Section: Introductionmentioning

confidence: 99%

OSOAA: a vector radiative transfer model of coupled atmosphere-ocean system for a rough sea surface application to the estimates of the directional variations of the water leaving reflectance to better process multi-angular satellite sensors data over the ocean

Chami¹,

Lafrance²,

Fougnie³

et al. 2015

Opt. Express

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International audienceIn this study, we present a radiative transfer model, so-called OSOAA, that is able to predict the radiance and degree of polarization within the coupled atmosphere-ocean system in the presence of a rough sea surface. The OSOAA model solves the radiative transfer equation using the successive orders of scattering method. Comparisons with another operational radiative transfer model showed a satisfactory agreement within 0.8%. The OSOAA model has been designed with a graphical user interface to make it user friendly for the community. The radiance and degree of polarization are provided at any level, from the top of atmosphere to the ocean bottom. An application of the OSOAA model is carried out to quantify the directional variations of the water leaving reflectance and degree of polarization for phytoplankton and mineral-like dominated waters. The difference between the water leaving reflectance at a given geometry and that obtained for the nadir direction could reach 40%, thus questioning the Lambertian assumption of the sea surface that is used by inverse satellite algorithms dedicated to multi-angular sensors. It is shown as well that the directional features of the water leaving reflectance are weakly dependent on wind speed. The quantification of the directional variations of the water leaving reflectance obtained in this study should help to correctly exploit the satellite data that will be acquired by the current or forthcoming multi-angular satellite sensors

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Polarized reflectance and transmittance properties of windblown sea surfaces

Cited by 138 publications

References 30 publications

Assessment of Atmospheric Correction Methods for Sentinel-2 MSI Images Applied to Amazon Floodplain Lakes

Assessment of Atmospheric Correction Methods for Sentinel-2 MSI Images Applied to Amazon Floodplain Lakes

The Potential of Autonomous Ship-Borne Hyperspectral Radiometers for the Validation of Ocean Color Radiometry Data

OSOAA: a vector radiative transfer model of coupled atmosphere-ocean system for a rough sea surface application to the estimates of the directional variations of the water leaving reflectance to better process multi-angular satellite sensors data over the ocean

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