{"refrec":{"BRefID":363580,"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>","BEntID":361298,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":1,"RefStringPartII":". <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>","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Vanhellemont, Q.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Vanhellemont, Q.","Englishabstract":"Planet’s SuperDove constellation is evaluated for remote sensing of water targets. SuperDoves are small satellites with on board eight band PlanetScope imagers that add four new bands compared to the previous generations of Doves. The Yellow (612 nm) and Red Edge (707 nm) bands are of particular interest to aquatic applications, for example in aiding the retrieval of pigment absorption. The dark spectrum fitting (DSF) algorithm is implemented in ACOLITE for processing of SuperDove data, and its outputs are compared to matchup data collected using an autonomous pan-and-tilt hyperspectral radiometer (PANTHYR) installed in the turbid waters of the Belgian Coastal Zone (BCZ). Results for 35 matchups from 32 unique SuperDove satellites indicate on average low differences with PANTHYR observations for the first seven bands (443–707 nm), with mean absolute relative differences (MARD) 15–20%. The mean average differences (MAD) are between -0.01 and 0 for the 492–666 nm bands, i.e. DSF results show a negative bias, while the Coastal Blue (444 nm) and Red Edge (707 nm) show a small positive bias (MAD 0.004 and 0.002). The NIR band (866 nm) shows a larger positive bias (MAD 0.01), and larger relative differences (MARD 60%). Root mean squared differences (RMSD) are rather flat at around 0.01 with peaks in the bands with highest water reflectance of around 0.015. The surface reflectance products as provided by Planet (PSR) show a similar average performance to DSF, with slightly larger and mostly positive biases, except in both Green bands, where the MAD is close to 0. MARD in the two Green bands is a bit lower for PSR (9.5–10.6%) compared to DSF (9.9–13.0%). Higher scatter is found for the PSR (RMSD 0.015–0.020), with some matchups showing large, spectrally mostly flat differences, likely due to the external aerosol optical depth (<i>τ</i> <i><sub>a</sub></i>) inputs not being representative for these particular images. Chlorophyll <i>a</i> absorption (<i>a</i> <i><sub>Chl</sub></i>) is retrieved from PANTHYR measurements, and the PANTHYR data are used to calibrate <i>a</i> <i><sub>Chl</sub></i> retrieval algorithms for SuperDove in the BCZ. Various Red band indices (RBI) and two neural networks are evaluated for <i>a</i> <i><sub>Chl</sub></i> estimation. The best performing RBI algorithm, i.e. the Red band difference (RBD), showed a MARD of 34% for DSF and 25% for PSR with positive biases of 0.11 and 0.03 <i>m</i> <sup>−1</sup> respectively for 24 PANTHYR <i>a</i> <i><sub>Chl</sub></i> matchups. The difference in RBD performance between DSF and PSR can be largely explained by their respective average biases in the Red and Red Edge bands, which are opposite signs for DSF (negative bias in the red), and positive for both bands for PSR. Mapping of turbid water <i>a</i> <i><sub>Chl</sub></i> and hence chlorophyll <i>a</i> concentration (<i>C</i>) using SuperDove is demonstrated for coastal bloom imagery, showing how SuperDove data can supplement monitoring programmes.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"Evaluation of eight band SuperDove imagery for aquatic applications","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2025-09-25 01:36:50.712317","timezone_type":1,"timezone":"+02:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"WATER-LEAVING REFLECTANCE;ATMOSPHERIC CORRECTION;CHLOROPHYLL-A;REMOTE ESTIMATION;SUN GLINT;INLAND WATERS;COASTAL;BATHYMETRY;ALGORITHM;LANDSAT","OtherDescriptors":null,"Notes":null,"AnaPub":2023,"MonPub":null,"DateUpdate":"2025-09-18","DateCreate":"2023-04-13","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:000988129200001","VABBcode":null,"OpenAcc":1,"DOI":"10.1364/oe.483418"},"refs":null,"anarec":{"AnaID":363580,"PubliDate":2023,"Pagination":"13851-13874","XtraPublOfAnaID":null,"ISBN":null,"Volume":"31","Issue":"9","BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":142420,"SerRR":"Optics Express. Optical Society of America: Washington.  ISSN 1094-4087; e-ISSN 1094-4087","StandardTitleSer":"Optics Express","ISSN":"1094-4087","AbbrevSer":null,"StandardTitleMon":null,"StartPage":13851,"Pages":24,"ToPubliDate":null,"BRefBibLvlCode":"S","SerNotes":null},"monrec":null,"serrec":null,"relations":null,"relationsRev":null,"addrec":null,"othpubs":null,"ownerships":null,"authors":[{"AutName":"Vanhellemont","Firstname":"Quinten","Initials":"Q.","Affiliation":"Royal Belgian Institute of Natural Sciences, Operational Directorate Natural Environments","Discriminator":null,"CorporateFlag":0,"BEntID":361298,"AutID":378785,"OrderNr":1,"DegrID":null,"EditorFlag":0,"CorrespFlag":0,"IllustratorFlag":0,"ReviserFlag":0,"TranslatorFlag":0,"InsAcronym":"OD Natuur","InsFSN":"Koninklijk Belgisch Instituut voor Natuurwetenschappen; Operationele Directie Natuurlijk Milieu","ORCID":"0000-0001-9195-6347","PersID":16635,"InsID":13002}],"mapdetails":null,"datasets":[{"DasID":8495,"Acronym":null,"Citation":"Vansteenwegen, D.; Vanhellemont, Q.; Flanders Marine Institute (VLIZ): Belgium; Royal Belgian Institute for Natural Sciences (RBINS): Belgium; (2024): PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2022. 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