Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/34958
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality
Author(s): Lehmann, Moritz K
Gurlin, Daniela
Pahlevan, Nima
Anstee, Janet
Balasubramanian, Sundarabalan V
Barbosa, Claudio C F
Binding, Caren
Bracher, Astrid
Bresciani, Mariano
Burtner, Ashley
Cao, Zhigang
Dekker, Arnold G
Jiang, Dalin
Spyrakos, Evangelos
Werther, Mortimer
Contact Email: evangelos.spyrakos@stir.ac.uk
Keywords: Library and Information Sciences
Statistics,
Probability and Uncertainty
Computer Science Applications
Education
Information Systems
Statistics and Probability
Issue Date: 2023
Date Deposited: 9-Mar-2023
Citation: Lehmann MK, Gurlin D, Pahlevan N, Anstee J, Balasubramanian SV, Barbosa CCF, Binding C, Bracher A, Bresciani M, Burtner A, Cao Z, Dekker AG, Jiang D, Spyrakos E & Werther M (2023) GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality. <i>Scientific Data</i>, 10 (1), Art. No.: 100. https://doi.org/10.1038/s41597-023-01973-y
Abstract: The 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.
DOI Link: 10.1038/s41597-023-01973-y
Rights: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Notes: Additional co-authors: Courtney Di Vittorio, Nathan Drayson, Reagan M. Errera, Virginia Fernandez, Dariusz Ficek, Cédric G. Fichot, Peter Gege, Claudia Giardino, Anatoly A. Gitelson, Steven R. Greb, Hayden Henderson, Hiroto Higa, Abolfazl Irani Rahaghi, Cédric Jamet, Thomas Jordan, Kersti Kangro, Jeremy A. Kravitz, Arne S. Kristoffersen, Raphael Kudela, Lin Li, Martin Ligi, Hubert Loisel, Steven Lohrenz, Ronghua Ma, Daniel A. Maciel, Tim J. Malthus, Bunkei Matsushita, Mark Matthews, Camille Minaudo, Deepak R. Mishra, Sachidananda Mishra, Tim Moore, Wesley J. Moses, Hà Nguyễn, Evlyn M. L. M. Novo, Stéfani Novoa, Daniel Odermatt, David M. O’Donnell, Leif G. Olmanson, Michael Ondrusek, Natascha Oppelt, Sylvain Ouillon, Waterloo Pereira Filho, Stefan Plattner, Antonio Ruiz Verdú, Salem I. Salem, John F. Schalles, Stefan G. H. Simis, Eko Siswanto, Brandon Smith, Ian Somlai-Schweiger, Mariana A. Soppa, Elinor Tessin, Hendrik J. van der Woerd, Andrea Vander Woude, Ryan A. Vandermeulen, Vincent Vantrepotte, Marcel R. Wernand, Kyana Young & Linwei Yue
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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