Serveur d'exploration sur l'OCR

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Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory

Identifieur interne : 000671 ( PascalFrancis/Curation ); précédent : 000670; suivant : 000672

Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory

Auteurs : S. A. Ahmed [États-Unis] ; T. Harmel [États-Unis] ; A. Gilerson [États-Unis] ; A. Tonizzo [États-Unis] ; S. Hlaing [États-Unis] ; A. Weidemann [États-Unis] ; R. A. Arnone [États-Unis]

Source :

RBID : Pascal:12-0109485

Descripteurs français

English descriptors

Abstract

Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. However, this task remains highly challenging due to the optical complexity of the atmosphere-water system in coastal areas. In order to support present and future multi- and hyper-spectral calibration/validation activities for the Ocean Color Radiometry (OCR) satellites, as well as the development of new measurements and retrieval techniques for coastal waters, City College of New York along with the Naval Research Laboratory (Stennis) has established a scientifically comprehensive observation platform, the Long Island Sound Coastal Observatory (LISCO). As an integral part of the NASA AERONET - Ocean Color Network, LISCO is equipped with a multispectral SeaPRISM system. In addition, LISCO expands its observational capabilities through hyperspectral measurements with a HyperSAS system. The related multi- and hyperspectral data processing and data quality analysis are described. The three main OCR satellites, MERIS, MODIS and SeaWiFS, have been evaluated against the LISCO dataset of quality-checked measurements of SeaPRISM and HyperSAS. Adjacency effects impacting satellite data have been analyzed and found negligible. The remote sensing reflectances retrieved from satellite and in situ data are also compared. These comparisons show satisfactory correlations (R2 > 0.91 at 547nm) and consistencies (median value of the absolute percentage difference ∼ 7.4%). It is also found that merging of the SeaPRISM and HyperSAS data at LISCO site significantly improve the overall data quality which makes this dataset highly suitable for satellite data validation purposes or for potential vicarious calibration activities.
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A11 04  1    @1 TONIZZO (A.)
A11 05  1    @1 HLAING (S.)
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C01 01    ENG  @0 Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. However, this task remains highly challenging due to the optical complexity of the atmosphere-water system in coastal areas. In order to support present and future multi- and hyper-spectral calibration/validation activities for the Ocean Color Radiometry (OCR) satellites, as well as the development of new measurements and retrieval techniques for coastal waters, City College of New York along with the Naval Research Laboratory (Stennis) has established a scientifically comprehensive observation platform, the Long Island Sound Coastal Observatory (LISCO). As an integral part of the NASA AERONET - Ocean Color Network, LISCO is equipped with a multispectral SeaPRISM system. In addition, LISCO expands its observational capabilities through hyperspectral measurements with a HyperSAS system. The related multi- and hyperspectral data processing and data quality analysis are described. The three main OCR satellites, MERIS, MODIS and SeaWiFS, have been evaluated against the LISCO dataset of quality-checked measurements of SeaPRISM and HyperSAS. Adjacency effects impacting satellite data have been analyzed and found negligible. The remote sensing reflectances retrieved from satellite and in situ data are also compared. These comparisons show satisfactory correlations (R2 > 0.91 at 547nm) and consistencies (median value of the absolute percentage difference ∼ 7.4%). It is also found that merging of the SeaPRISM and HyperSAS data at LISCO site significantly improve the overall data quality which makes this dataset highly suitable for satellite data validation purposes or for potential vicarious calibration activities.
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C03 08  3  FRE  @0 Eau côtière @5 62
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A30 01  1  ENG  @1 Remote sensing of the ocean, sea ice, coastal waters, and large water regions. Conference @3 Prague CZE @4 2011-09-21

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<div type="abstract" xml:lang="en">Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. However, this task remains highly challenging due to the optical complexity of the atmosphere-water system in coastal areas. In order to support present and future multi- and hyper-spectral calibration/validation activities for the Ocean Color Radiometry (OCR) satellites, as well as the development of new measurements and retrieval techniques for coastal waters, City College of New York along with the Naval Research Laboratory (Stennis) has established a scientifically comprehensive observation platform, the Long Island Sound Coastal Observatory (LISCO). As an integral part of the NASA AERONET - Ocean Color Network, LISCO is equipped with a multispectral SeaPRISM system. In addition, LISCO expands its observational capabilities through hyperspectral measurements with a HyperSAS system. The related multi- and hyperspectral data processing and data quality analysis are described. The three main OCR satellites, MERIS, MODIS and SeaWiFS, have been evaluated against the LISCO dataset of quality-checked measurements of SeaPRISM and HyperSAS. Adjacency effects impacting satellite data have been analyzed and found negligible. The remote sensing reflectances retrieved from satellite and in situ data are also compared. These comparisons show satisfactory correlations (R
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</fA18>
<fA20>
<s2>817505.1-817505.11</s2>
</fA20>
<fA21>
<s1>2011</s1>
</fA21>
<fA23 i1="01">
<s0>ENG</s0>
</fA23>
<fA25 i1="01">
<s1>SPIE</s1>
<s2>Bellingham Wash.</s2>
</fA25>
<fA26 i1="01">
<s0>978-0-8194-8802-2</s0>
</fA26>
<fA43 i1="01">
<s1>INIST</s1>
<s2>21760</s2>
<s5>354000174766650040</s5>
</fA43>
<fA44>
<s0>0000</s0>
<s1>© 2012 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45>
<s0>26 ref.</s0>
</fA45>
<fA47 i1="01" i2="1">
<s0>12-0109485</s0>
</fA47>
<fA60>
<s1>P</s1>
<s2>C</s2>
</fA60>
<fA61>
<s0>A</s0>
</fA61>
<fA64 i1="01" i2="1">
<s0>Proceedings of SPIE, the International Society for Optical Engineering</s0>
</fA64>
<fA66 i1="01">
<s0>USA</s0>
</fA66>
<fC01 i1="01" l="ENG">
<s0>Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. However, this task remains highly challenging due to the optical complexity of the atmosphere-water system in coastal areas. In order to support present and future multi- and hyper-spectral calibration/validation activities for the Ocean Color Radiometry (OCR) satellites, as well as the development of new measurements and retrieval techniques for coastal waters, City College of New York along with the Naval Research Laboratory (Stennis) has established a scientifically comprehensive observation platform, the Long Island Sound Coastal Observatory (LISCO). As an integral part of the NASA AERONET - Ocean Color Network, LISCO is equipped with a multispectral SeaPRISM system. In addition, LISCO expands its observational capabilities through hyperspectral measurements with a HyperSAS system. The related multi- and hyperspectral data processing and data quality analysis are described. The three main OCR satellites, MERIS, MODIS and SeaWiFS, have been evaluated against the LISCO dataset of quality-checked measurements of SeaPRISM and HyperSAS. Adjacency effects impacting satellite data have been analyzed and found negligible. The remote sensing reflectances retrieved from satellite and in situ data are also compared. These comparisons show satisfactory correlations (R
<sup>2</sup>
> 0.91 at 547nm) and consistencies (median value of the absolute percentage difference ∼ 7.4%). It is also found that merging of the SeaPRISM and HyperSAS data at LISCO site significantly improve the overall data quality which makes this dataset highly suitable for satellite data validation purposes or for potential vicarious calibration activities.</s0>
</fC01>
<fC02 i1="01" i2="3">
<s0>001B00A30C</s0>
</fC02>
<fC02 i1="02" i2="2">
<s0>001E02B06A</s0>
</fC02>
<fC02 i1="03" i2="3">
<s0>001B40B68W</s0>
</fC02>
<fC02 i1="04" i2="3">
<s0>001B40B79P</s0>
</fC02>
<fC03 i1="01" i2="3" l="FRE">
<s0>Traitement donnée</s0>
<s5>03</s5>
</fC03>
<fC03 i1="01" i2="3" l="ENG">
<s0>Data processing</s0>
<s5>03</s5>
</fC03>
<fC03 i1="02" i2="3" l="FRE">
<s0>Analyse donnée</s0>
<s5>23</s5>
</fC03>
<fC03 i1="02" i2="3" l="ENG">
<s0>Data analysis</s0>
<s5>23</s5>
</fC03>
<fC03 i1="03" i2="3" l="FRE">
<s0>Télédétection</s0>
<s5>30</s5>
</fC03>
<fC03 i1="03" i2="3" l="ENG">
<s0>Remote sensing</s0>
<s5>30</s5>
</fC03>
<fC03 i1="04" i2="3" l="FRE">
<s0>Etalonnage</s0>
<s5>31</s5>
</fC03>
<fC03 i1="04" i2="3" l="ENG">
<s0>Calibration</s0>
<s5>31</s5>
</fC03>
<fC03 i1="05" i2="3" l="FRE">
<s0>Méthode mesure</s0>
<s5>32</s5>
</fC03>
<fC03 i1="05" i2="3" l="ENG">
<s0>Measuring methods</s0>
<s5>32</s5>
</fC03>
<fC03 i1="06" i2="3" l="FRE">
<s0>Facteur réflexion</s0>
<s5>41</s5>
</fC03>
<fC03 i1="06" i2="3" l="ENG">
<s0>Reflectivity</s0>
<s5>41</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE">
<s0>Capteur imagerie hyperspectral</s0>
<s5>61</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG">
<s0>Hyperspectral imaging sensor</s0>
<s5>61</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA">
<s0>Sensor hiperespectral de formación de imágenes</s0>
<s5>61</s5>
</fC03>
<fC03 i1="08" i2="3" l="FRE">
<s0>Eau côtière</s0>
<s5>62</s5>
</fC03>
<fC03 i1="08" i2="3" l="ENG">
<s0>Coastal waters</s0>
<s5>62</s5>
</fC03>
<fC03 i1="09" i2="3" l="FRE">
<s0>Qualité eau</s0>
<s5>63</s5>
</fC03>
<fC03 i1="09" i2="3" l="ENG">
<s0>Water quality</s0>
<s5>63</s5>
</fC03>
<fC03 i1="10" i2="3" l="FRE">
<s0>Radiométrie</s0>
<s5>64</s5>
</fC03>
<fC03 i1="10" i2="3" l="ENG">
<s0>Radiometric analysis</s0>
<s5>64</s5>
</fC03>
<fC03 i1="11" i2="3" l="FRE">
<s0>Détroit Long Island</s0>
<s2>NG</s2>
<s5>65</s5>
</fC03>
<fC03 i1="11" i2="3" l="ENG">
<s0>Long Island Sound</s0>
<s2>NG</s2>
<s5>65</s5>
</fC03>
<fC03 i1="12" i2="3" l="FRE">
<s0>New York</s0>
<s2>NG</s2>
<s5>66</s5>
</fC03>
<fC03 i1="12" i2="3" l="ENG">
<s0>New York</s0>
<s2>NG</s2>
<s5>66</s5>
</fC03>
<fC03 i1="13" i2="3" l="FRE">
<s0>0130C</s0>
<s4>INC</s4>
<s5>83</s5>
</fC03>
<fC03 i1="14" i2="3" l="FRE">
<s0>4268X</s0>
<s4>INC</s4>
<s5>84</s5>
</fC03>
<fC03 i1="15" i2="3" l="FRE">
<s0>4268W</s0>
<s4>INC</s4>
<s5>85</s5>
</fC03>
<fC03 i1="16" i2="3" l="FRE">
<s0>Satellite</s0>
<s4>INC</s4>
<s5>86</s5>
</fC03>
<fC03 i1="17" i2="3" l="FRE">
<s0>Ile</s0>
<s4>INC</s4>
<s5>87</s5>
</fC03>
<fC03 i1="18" i2="3" l="FRE">
<s0>Surveillance</s0>
<s4>INC</s4>
<s5>88</s5>
</fC03>
<fC03 i1="19" i2="3" l="FRE">
<s0>Monde</s0>
<s4>INC</s4>
<s5>89</s5>
</fC03>
<fC03 i1="20" i2="3" l="FRE">
<s0>4279P</s0>
<s4>INC</s4>
<s5>91</s5>
</fC03>
<fC03 i1="21" i2="3" l="FRE">
<s0>0705K</s0>
<s4>INC</s4>
<s5>92</s5>
</fC03>
<fC03 i1="22" i2="3" l="FRE">
<s0>Optique océanique</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="22" i2="3" l="ENG">
<s0>Ocean optics</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fN21>
<s1>086</s1>
</fN21>
<fN44 i1="01">
<s1>OTO</s1>
</fN44>
<fN82>
<s1>OTO</s1>
</fN82>
</pA>
<pR>
<fA30 i1="01" i2="1" l="ENG">
<s1>Remote sensing of the ocean, sea ice, coastal waters, and large water regions. Conference</s1>
<s3>Prague CZE</s3>
<s4>2011-09-21</s4>
</fA30>
</pR>
</standard>
</inist>
</record>

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