Evaluation of four atmospheric correction algorithms for MODIS-Aqua images over contrasted coastal waters

Goyens, Clémence; Jamet, Cédric; Schroeder, T.

doi:10.1016/j.rse.2012.12.006

Cited by 140 publications

(93 citation statements)

References 36 publications

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“…Similar limitations would be expected for radiance-based methods. While the atmospheric correction can be a challenge over some coastal waters (Goyens et al, 2013), if R rs (λ) is accurately retrieved, the dynamic range of CDOM and NAP that impart a significant signal to R rs (λ) require empirical relationships and thresholds defined for various PFTs and PSCs to be reestablished. The approaches that build upon semi-analytic expressions that first retrieve IOPs from R rs (λ) and then PFTs from the retrieved IOPs, have the greatest ability to accommodate dynamic environments.…”

Section: Algorithm Selectionmentioning

confidence: 99%

A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean

et al. 2017

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Phytoplankton are composed of diverse taxonomical groups, which are manifested as distinct morphology, size, and pigment composition. These characteristics, modulated by their physiological state, impact their light absorption and scattering, allowing them to be detected with ocean color satellite radiometry. There is a growing volume of literature describing satellite algorithms to retrieve information on phytoplankton composition in the ocean. This synthesis provides a review of current methods and a simplified comparison of approaches. The aim is to provide an easily comprehensible resource for non-algorithm developers, who desire to use these products, thereby raising the level of awareness and use of these products and reducing the boundary of expert knowledge needed to make a pragmatic selection of output products with confidence. The satellite input and output products, their associated validation metrics, as well as assumptions, strengths, and limitations of the various algorithm types are described, providing a framework for algorithm organization to assist users and inspire new aspects of algorithm development capable of exploiting the higher spectral, spatial and temporal resolutions from the next generation of ocean color satellites.

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Section: Algorithm Selectionmentioning

confidence: 99%

A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean

et al. 2017

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“…A time difference of 2 h between the satellite overpass and the in situ measurement reduced the number of matchup pairs. However this ensures that in situ measurements and HICO-derived ρ w actually correspond, particularly considering the high spatial and temporal variability of coastal waters (Goyens et al, 2013). For each match-up pair, the ρ w in situ measurement was resampled to HICO ™ wavelengths and the median of the HICO ™ -derived ρ w (λ) was calculated over a 3 by 3 pixel window around the station (Goyens et al, 2013;Jamet et al, 2011).…”

Section: Validation Of Hico@cri Algorithmmentioning

confidence: 99%

The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters

et al. 2015

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Abstract.Hyperspectral imaging provides quantitative remote sensing of ocean colour by the high spectral resolution of the water features. The HICO ™ (Hyperspectral Imager for the Coastal Ocean) is suitable for coastal studies and monitoring. The accurate retrieval of hyperspectral waterleaving reflectance from HICO ™ data is still a challenge. The aim of this work is to retrieve the water-leaving reflectance from HICO ™ data with a physically based algorithm, using the local microphysical properties of the aerosol in order to overcome the limitations of the standard aerosol types commonly used in atmospheric correction processing. The water-leaving reflectance was obtained using the HICO@CRI (HICO ATmospherically Corrected Reflectance Imagery) atmospheric correction algorithm by adapting the vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) radiative transfer code. The HICO@CRI algorithm was applied on to six HICO ™ images acquired in the northern Mediterranean basin, using the microphysical properties measured by the Acqua Alta Oceanographic Tower (AAOT) AERONET site. The HICO@CRI results obtained with AERONET products were validated with in situ measurements showing an accuracy expressed by r 2 = 0.98. Additional runs of HICO@CRI on the six images were performed using maritime, continental and urban standard aerosol types to perform the accuracy assessment when standard aerosol types implemented in 6SV are used. The results highlight that the microphysical properties of the aerosol improve the accuracy of the atmospheric correction compared to standard aerosol types. The normalized root mean square (NRMSE) and the similar spectral value (SSV) of the water-leaving reflectance show reduced accuracy in atmospheric correction results when there is an increase in aerosol loading. This is mainly when the standard aerosol type used is characterized with different optical properties compared to the local aerosol. The results suggest that if a water quality analysis is needed the microphysical properties of the aerosol need to be taken into consideration in the atmospheric correction of hyperspectral data over coastal environments, because aerosols influence the accuracy of the retrieved water-leaving reflectance.

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“…The standard NASA atmospheric correction algorithm was applied [51][52][53]. Numerous studies have shown that this algorithm generally provides the best overall performances over optically-complex coastal waters (i.e., [54][55][56][57]). …”

Section: Satellite Datamentioning

confidence: 99%

Seasonal and Inter-Annual Analysis of Chlorophyll-a and Inherent Optical Properties from Satellite Observations in the Inner and Mid-Shelves of the South of Buenos Aires Province (Argentina)

et al. 2015

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Abstract:The aim of this study is to describe and understand the seasonal and inter-annual physical and biological dynamics of the inner and mid shelves of the Southwestern Buenos Aires Province (Argentina). We used chlorophyll-a (chl-a) concentrations and inherent optical properties (IOPs), derived from ocean color products between 2002 and 2010, as a proxy for the physical and biological parameters of interest. This study focuses on the absorption by phytoplankton, aph(443), particulate backscattering, bbp(443), and absorption due to dissolved and particulate detrital matter, adg (443), and chl-a derived from a multiband quasi-analytical algorithm (QAA). A regionalization based on the coefficient of variation and the Census X-11 method were applied to define regions and to analyze the inter-annual and seasonal variability of the ocean color parameters, with regards to climate OPEN ACCESSRemote Sens. 2015, 7 11822 variability. The coastal zone presents the highest values of chl-a with two maxima in winter and autumn, while the mid-shelf shows a strong spring chl-a maximum. After 2009, all parameters under study shifted their seasonality and their magnitude changed over the entire area. In the coastal zone, mean values of aph(443) and bbp(443) increased, while in the mid-shelf, chl-a and aph(443) decreased. The observed inter-annual and seasonal behavior of the parameters is tightly related to climate variability of the study area.

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Evaluation of four atmospheric correction algorithms for MODIS-Aqua images over contrasted coastal waters

Cited by 140 publications

References 36 publications

A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean

A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean

The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters

Seasonal and Inter-Annual Analysis of Chlorophyll-a and Inherent Optical Properties from Satellite Observations in the Inner and Mid-Shelves of the South of Buenos Aires Province (Argentina)

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