GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

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dc.contributor.authorLehmann, Moritz K.
dc.contributor.authorGurlin, Daniela
dc.contributor.authorPahlevan, Nima
dc.contributor.authorAlikas, Krista
dc.contributor.authorConroy, Ted
dc.contributor.authorAnstee, Janet
dc.contributor.authorBalasubramanian, Sundarabalan V.
dc.contributor.authorBarbosa, Cláudio C. F.
dc.contributor.authorBinding, Caren
dc.contributor.authorBracher, Astrid
dc.contributor.authorBresciani, Mariano
dc.contributor.authorBurtner, Ashley
dc.contributor.authorCao, Zhigang
dc.contributor.authorDekker, Arnold G.
dc.contributor.authorDi Vittorio, Courtney
dc.contributor.authorDrayson, Nathan
dc.contributor.authorErrera, Reagan M.
dc.contributor.authorFernandez, Virginia
dc.contributor.authorFicek, Dariusz
dc.contributor.authorFichot, Cédric G.
dc.contributor.authorGege, Peter
dc.contributor.authorGiardino, Claudia
dc.contributor.authorGitelson, Anatoly A.
dc.contributor.authorGreb, Steven R.
dc.contributor.authorHenderson, Hayden
dc.contributor.authorHiga, Hiroto
dc.contributor.authorRahaghi, Abolfazl Irani
dc.contributor.authorJamet, Cédric
dc.contributor.authorJiang, Dalin
dc.contributor.authorJordan, Thomas
dc.contributor.authorKangro, Kersti
dc.contributor.authorKravitz, Jeremy A.
dc.contributor.authorKristoffersen, Arne S.
dc.contributor.authorKudela, Raphael
dc.contributor.authorLi, Lin
dc.contributor.authorLigi, Martin
dc.contributor.authorLoisel, Hubert
dc.contributor.authorLohrenz, Steven
dc.contributor.authorMa, Ronghua
dc.contributor.authorMaciel, Daniel A.
dc.contributor.authorMalthus, Tim J.
dc.contributor.authorMatsushita, Bunkei
dc.contributor.authorMatthews, Mark
dc.contributor.authorMinaudo, Camille
dc.contributor.authorMishra, Deepak R.
dc.contributor.authorMishra, Sachidananda
dc.contributor.authorMoore, Tim
dc.contributor.authorMoses, Wesley J.
dc.contributor.authorNguyễn, Hà
dc.contributor.authorNovo, Evlyn M. L. M.
dc.contributor.authorNovoa, Stéfani
dc.contributor.authorOdermatt, Daniel
dc.contributor.authorO'Donnell, David M.
dc.contributor.authorOlmanson, Leif G.
dc.contributor.authorOndrusek, Michael
dc.contributor.authorOppelt, Natascha
dc.contributor.authorOuillon, Sylvain
dc.contributor.authorFilho, Waterloo Pereira
dc.contributor.authorPlattner, Stefan
dc.contributor.authorRuiz Verdú, Antonio
dc.contributor.authorSalem, Salem I.
dc.contributor.authorSchalles, John F.
dc.contributor.authorSimis, Stefan G. H.
dc.contributor.authorSiswanto, Eko
dc.contributor.authorSmith , Brandon
dc.contributor.authorSomlai-Schweiger, Ian
dc.contributor.authorSoppa, Mariana A.
dc.contributor.authorSpyrakos, Evangelos
dc.contributor.authorTessin, Elinor
dc.contributor.authorvan der Woerd, Hendrik J.
dc.contributor.authorVander Woude, Andrea
dc.contributor.authorVandermeulen, Ryan A.
dc.contributor.authorVantrepotte, Vincent
dc.contributor.authorWernand, Marcel R.
dc.contributor.authorWerther, Mortimer
dc.contributor.authorYoung, Kyana
dc.contributor.authorYue, Linwei
dc.contributor.departmentEarth and Environmental Sciences, School of Science
dc.date.accessioned2024-10-04T19:44:01Z
dc.date.available2024-10-04T19:44:01Z
dc.date.issued2023-02
dc.description.abstractThe development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.
dc.eprint.versionFinal published version
dc.identifier.citationLehmann, M. K., Gurlin, D., Pahlevan, N., Alikas, K., Conroy, T., Anstee, J., Balasubramanian, S. V., Barbosa, C. C. F., Binding, C., Bracher, A., Bresciani, M., Burtner, A., Cao, Z., Dekker, A. G., Di Vittorio, C., Drayson, N., Errera, R. M., Fernandez, V., Ficek, D., … Yue, L. (2023). GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality. Scientific Data, 10(1), 100. https://doi.org/10.1038/s41597-023-01973-y
dc.identifier.urihttps://hdl.handle.net/1805/43797
dc.language.isoen
dc.publisherNature
dc.relation.isversionof10.1038/s41597-023-01973-y
dc.relation.journalScientific Data
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.sourcePublisher
dc.subjectenvironmental impact
dc.subjectlimnology
dc.subjectGLORIA
dc.titleGLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality
dc.typeArticle
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