    {"datasetrec":{"DasID":8496,"Acronym":null,"StandardTitle":"PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2023","OrigTitle":null,"OrigTitleLangID":null,"OrigTitleLangCode":null,"OrigTitleLang":null,"OrigTitleLangNL":null,"VersionName":null,"ContactEmail":null,"VersionDate":null,"VersionDay":null,"VersionMonth":null,"VersionYear":null,"SizeReference":null,"EngAbstract":"<p>Autonomously acquired above-water PANTHYR water reflectance data from a pair of TriOS RAMSES radiance and irradiance sensors, details provided in Vansteenwegen et al. 2019. Data passed automated quality control but has not been screened by an expert.</p>","EngDescr":"<p>This dataset contains autonomously acquired abovewater PANTHYR water reflectance data from a pair of TriOS RAMSES radiance and irradiance sensors. Measurements are performed under a sun-sensor geometry that minimises sun and sky glint on the air-water interface, as recommended by Mobley (1999), and utilised commonly in above water measurements, e.g. by Ruddick et al. (2006). Irradiance and radiance measurements are made sequentially rather than simultaneously, with a full cycle containing 3 irradiance (Ed), 3 downwelling radiance (Ld), 11 upwelling radiance (Lu), 3 more Ld and 3 more Ed. This sequence takes about 1 minute to complete in normal illumination conditions, and temporal stability checks are performed on these sequential measurements (Vanhellemont 2020). A given number of valid measurements (Ed: 5/6, Ld: 5/6, Lu: 9/11) are required for further processing. RAMSES data are resampled to a common wavelength grid between 355 and 945 nm with a 2.5 nm step. A \"Fresnel\" correction for the air-water interface reflectance is performed using the Mobley (1999) LUT for a fixed (2 m/s) or modeled (NCEP) wind speed. Full details on the PANTHYR system are provided in Vansteenwegen et al. 2019. This dataset contains the average and standard deviation of hyperspectral irradiance (ed), downwelling radiance (ld), total upwelling radiance (lu), and derived water-leaving radiance (lw). Water-leaving radiance reflectance is provided with NIR similarity spectrum correction (rhow) and without NIR similarity spectrum correction (rhow_nosc). Data passed automated quality control but have not been screened by an expert.</p><p>The general objective of the HYPERMAQ project was to develop and test new algorithms for aquatic remote sensing of coastal and inland waters, using both hyperspectral and high resolution multispectral satellite data to provide more than “just” concentration of suspended particulate matter and chlorophyll. Test sites focused particularly on turbid waters. The PANTHYR (pan-and-tilt hyperspectral radiometer system) was designed in HYPERMAQ for autonomous measurement of hyperspectral water reflectance for the validation of satellite reflectance in visible and near-infrared bands (400–900 nm).</p>","OrigAbstract":null,"OrigDescr":null,"Comments":null,"ReleaseDate":null,"ReleaseDate0":null,"OrigDescrLang":null,"EmbargoDate":null,"OrigDescrLangNL":null,"OrigLangCode":null,"OrigLangCodeExtended":null,"OrigLangID":null,"DescrCompFlag":null,"DescrTransFlag":null,"Citation":"Vansteenwegen, D.; Vanhellemont, Q.; Flanders Marine Institute (VLIZ); Royal Belgian Institute for Natural Sciences (RBINS): Belgium; (2024): PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2023. Marine Data Archive.","AccessConstraints":"If you use the data provided by PANTHYR, please refer to it in any of your publications as: \"This work was supported by PANTHYR data & infrastructure provided by the Flanders Marine Institute (VLIZ) and Royal Belgian Institute for Natural Sciences (RBINS)\".","UDate":"2025-03-24","CDate":"2024-02-29","CurrencyDate":null,"RevisionDate":null,"DateLastModified":{"date":"2026-05-14 01:44:00.153333","timezone_type":1,"timezone":"+02:00"},"CheckedFlag":1,"PublicFlag":1,"VlizCoreFlag":1,"MarineFlag":null,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"StatusID":1,"DasType":"Data","DasTypeID":1,"DasOrigin":"Sensor platform","Progress":"Completed","AccessConstraint":"Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND)","AccConstrEN":"Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND)","AccConstrDisplay":"<a rel=\"license\" href=\"https://creativecommons.org/licenses/by-nc-nd/4.0/\" target=\"_blank\"><img alt=\"Creative Commons License\" style=\"border:0px;height:15px;width:80px;vertical-align:middle;\" src=\"https://www.marinespecies.org/aphia/images/cc/by-nc-nd.png\" /></a> This dataset is licensed under a <a rel=\"license\" href=\"https://creativecommons.org/licenses/by-nc-nd/4.0/\" target=\"_blank\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.","License":"https://creativecommons.org/licenses/by-nc-nd/4.0","AccConstrDescription":"This license is the most restrictive of our six main licenses, only allowing others to download your works and share them with others as long as they credit you, but they can’t change them in any way or use them commercially.","Lineage":null,"AccConID":26},"dois":[{"DOIID":1155,"PublicationYear":2025,"DOI":"10.14284/724","Citation":"Vansteenwegen, D.; Vanhellemont, Q.; Flanders Marine Institute (VLIZ); Royal Belgian Institute for Natural Sciences (RBINS): Belgium; (2024): PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2023. 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Ocean color atmospheric correction methods in view of usability for different optical water types. <i>Front. Mar. Sci. 10</i>: 1129876. <a href=\"https://dx.doi.org/10.3389/fmars.2023.1129876\" target=\"_blank\">https://dx.doi.org/10.3389/fmars.2023.1129876</a>","RR":"<b>Hieronymi, M. <i>et al.</i></b> (2023). Ocean color atmospheric correction methods in view of usability for different optical water types. <i>Front. Mar. Sci. 10</i>: 1129876. <a href=\"https://dx.doi.org/10.3389/fmars.2023.1129876\" target=\"_blank\">https://dx.doi.org/10.3389/fmars.2023.1129876</a>","4":"Ocean color atmospheric correction methods in view of usability for different optical water types","StT":"Ocean color atmospheric correction methods in view of usability for different optical water types","5":"Hieronymi, M.; Bi, S.; Müller, D.; Schütt, E.M.; Behr, D.; Brockmann, C.; Lebreton, C.; Steinmetz, F.; Stelzer, K.; Vanhellemont, Q.","RSA":"Hieronymi, M.; Bi, S.; Müller, D.; Schütt, E.M.; Behr, D.; Brockmann, C.; Lebreton, C.; Steinmetz, F.; Stelzer, K.; Vanhellemont, Q.","6":"Gebaseerd op deze dataset","DutchTerm":"Gebaseerd op deze dataset","7":2023,"AnaDate":2023,"8":null,"MonDate":null,"9":". <i>Front. Mar. Sci. 10</i>: 1129876. <a href=\"https://dx.doi.org/10.3389/fmars.2023.1129876\" target=\"_blank\">https://dx.doi.org/10.3389/fmars.2023.1129876</a>","":". <i>Front. Mar. Sci. 10</i>: 1129876. <a href=\"https://dx.doi.org/10.3389/fmars.2023.1129876\" target=\"_blank\">https://dx.doi.org/10.3389/fmars.2023.1129876</a>","10":"https://dx.doi.org/10.3389/fmars.2023.1129876","doi":"https://dx.doi.org/10.3389/fmars.2023.1129876"},{"0":366388,"BRefID":366388,"1":"Based on this dataset","Relation":"Based on this dataset","2":2,"RelationID":2,"3":"<b>Lavigne, H. <i>et al.</i></b> (2023). Turbid water sun glint removal for high resolution sensors without SWIR, <b><i>in</i></b>: Bostater, C.R. <i>et al.</i> <i>Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions, 2023, 3 - 6 September 2023, Amsterdam, Netherlands. Proceedings of SPIE, the International Society for Optical Engineering,</i> : pp. 1272804","RR":"<b>Lavigne, H. <i>et al.</i></b> (2023). Turbid water sun glint removal for high resolution sensors without SWIR, <b><i>in</i></b>: Bostater, C.R. <i>et al.</i> <i>Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions, 2023, 3 - 6 September 2023, Amsterdam, Netherlands. Proceedings of SPIE, the International Society for Optical Engineering,</i> : pp. 1272804","4":"Turbid water sun glint removal for high resolution sensors without SWIR","StT":"Turbid water sun glint removal for high resolution sensors without SWIR","5":"Lavigne, H.; Vanhellemont, Q.; Ruddick, K.; Vansteenwegen, D.","RSA":"Lavigne, H.; Vanhellemont, Q.; Ruddick, K.; Vansteenwegen, D.","6":"Gebaseerd op deze dataset","DutchTerm":"Gebaseerd op deze dataset","7":2023,"AnaDate":2023,"8":null,"MonDate":null,"9":", <b><i>in</i></b>: Bostater, C.R. <i>et al.</i> <i>Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions, 2023, 3 - 6 September 2023, Amsterdam, Netherlands. Proceedings of SPIE, the International Society for Optical Engineering,</i> : pp. 1272804","":", <b><i>in</i></b>: Bostater, C.R. <i>et al.</i> <i>Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions, 2023, 3 - 6 September 2023, Amsterdam, Netherlands. Proceedings of SPIE, the International Society for Optical Engineering,</i> : pp. 1272804","10":null,"doi":null},{"0":363580,"BRefID":363580,"1":"Based on this dataset","Relation":"Based on this dataset","2":2,"RelationID":2,"3":"<b>Vanhellemont, Q.</b> (2023). Evaluation of eight band SuperDove imagery for aquatic applications. <i>Optics Express 31(9)</i>: 13851-13874. <a href=\"https://dx.doi.org/10.1364/oe.483418\" target=\"_blank\">https://dx.doi.org/10.1364/oe.483418</a>","RR":"<b>Vanhellemont, Q.</b> (2023). Evaluation of eight band SuperDove imagery for aquatic applications. <i>Optics Express 31(9)</i>: 13851-13874. <a href=\"https://dx.doi.org/10.1364/oe.483418\" target=\"_blank\">https://dx.doi.org/10.1364/oe.483418</a>","4":"Evaluation of eight band SuperDove imagery for aquatic applications","StT":"Evaluation of eight band SuperDove imagery for aquatic applications","5":"Vanhellemont, Q.","RSA":"Vanhellemont, Q.","6":"Gebaseerd op deze dataset","DutchTerm":"Gebaseerd op deze dataset","7":2023,"AnaDate":2023,"8":null,"MonDate":null,"9":". <i>Optics Express 31(9)</i>: 13851-13874. <a href=\"https://dx.doi.org/10.1364/oe.483418\" target=\"_blank\">https://dx.doi.org/10.1364/oe.483418</a>","":". <i>Optics Express 31(9)</i>: 13851-13874. <a href=\"https://dx.doi.org/10.1364/oe.483418\" target=\"_blank\">https://dx.doi.org/10.1364/oe.483418</a>","10":"https://dx.doi.org/10.1364/oe.483418","doi":"https://dx.doi.org/10.1364/oe.483418"},{"0":354251,"BRefID":354251,"1":"Based on this dataset","Relation":"Based on this dataset","2":2,"RelationID":2,"3":"<b>Dierssen, H.M. <i>et al.</i></b> (2022). QWIP: A quantitative metric for quality control of aquatic reflectance spectral shape using the Apparent Visible Wavelength. <i>Front. Remote Sens. 3</i>: 869611. <a href=\"https://dx.doi.org/10.3389/frsen.2022.869611\" target=\"_blank\">https://dx.doi.org/10.3389/frsen.2022.869611</a>","RR":"<b>Dierssen, H.M. <i>et al.</i></b> (2022). QWIP: A quantitative metric for quality control of aquatic reflectance spectral shape using the Apparent Visible Wavelength. <i>Front. Remote Sens. 3</i>: 869611. <a href=\"https://dx.doi.org/10.3389/frsen.2022.869611\" target=\"_blank\">https://dx.doi.org/10.3389/frsen.2022.869611</a>","4":"QWIP: A quantitative metric for quality control of aquatic reflectance spectral shape using the Apparent Visible Wavelength","StT":"QWIP: A quantitative metric for quality control of aquatic reflectance spectral shape using the Apparent Visible Wavelength","5":"Dierssen, H.M.; Vandermeulen, R.A.; Barnes, B.B.; Castagna, A.; Knaeps, E.; Vanhellemont, Q.","RSA":"Dierssen, H.M.; Vandermeulen, R.A.; Barnes, B.B.; Castagna, A.; Knaeps, E.; Vanhellemont, Q.","6":"Gebaseerd op deze dataset","DutchTerm":"Gebaseerd op deze dataset","7":2022,"AnaDate":2022,"8":null,"MonDate":null,"9":". <i>Front. Remote Sens. 3</i>: 869611. <a href=\"https://dx.doi.org/10.3389/frsen.2022.869611\" target=\"_blank\">https://dx.doi.org/10.3389/frsen.2022.869611</a>","":". <i>Front. Remote Sens. 3</i>: 869611. <a href=\"https://dx.doi.org/10.3389/frsen.2022.869611\" target=\"_blank\">https://dx.doi.org/10.3389/frsen.2022.869611</a>","10":"https://dx.doi.org/10.3389/frsen.2022.869611","doi":"https://dx.doi.org/10.3389/frsen.2022.869611"},{"0":356474,"BRefID":356474,"1":"Based on this dataset","Relation":"Based on this dataset","2":2,"RelationID":2,"3":"<b>Lavigne, H.; Ruddick, K.; Vanhellemont, Q.</b> (2022). Monitoring of high biomass <i>Phaeocystis globosa</i> blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry. <i>Remote Sens. Environ. 282</i>: 113270. <a href=\"https://dx.doi.org/10.1016/j.rse.2022.113270\" target=\"_blank\">https://dx.doi.org/10.1016/j.rse.2022.113270</a>","RR":"<b>Lavigne, H.; Ruddick, K.; Vanhellemont, Q.</b> (2022). Monitoring of high biomass <i>Phaeocystis globosa</i> blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry. <i>Remote Sens. Environ. 282</i>: 113270. <a href=\"https://dx.doi.org/10.1016/j.rse.2022.113270\" target=\"_blank\">https://dx.doi.org/10.1016/j.rse.2022.113270</a>","4":"Monitoring of high biomass <i>Phaeocystis globosa</i> blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry","StT":"Monitoring of high biomass <i>Phaeocystis globosa</i> blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry","5":"Lavigne, H.; Ruddick, K.; Vanhellemont, Q.","RSA":"Lavigne, H.; Ruddick, K.; Vanhellemont, Q.","6":"Gebaseerd op deze dataset","DutchTerm":"Gebaseerd op deze dataset","7":2022,"AnaDate":2022,"8":null,"MonDate":null,"9":". <i>Remote Sens. Environ. 282</i>: 113270. <a href=\"https://dx.doi.org/10.1016/j.rse.2022.113270\" target=\"_blank\">https://dx.doi.org/10.1016/j.rse.2022.113270</a>","":". <i>Remote Sens. 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