Moritz K. Lehmann, Xerra Earth Observation Institute
Daniela Gurlin, Wisconsin Department Natural Resources
Nima Pahlevan, Science Systems and Applications, Inc. (SSAI)
Krista Alikas, Tartu Ülikool
Janet Anstee, Commonwealth Scientific and Industrial Research Organization
Sundarabalan V. Balasubramanian, GeoSensing and Imaging Consultancy
Cláudio C.F. Barbosa, Instituto Nacional de Pesquisas Espaciais
Caren Binding, Environment and Climate Change Canada
Astrid Bracher, Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
Mariano Bresciani, Consiglio Nazionale delle Ricerche, Institute for Electromagnetic Sensing of the Environment
Ashley Burtner, University of Michigan, Ann Arbor
Zhigang Cao, Nanjing Institute of Geography and Limnology Chinese Academy of Sciences
Arnold G. Dekker, SatDek Pty Ltd
Courtney Di Vittorio, Wake Forest University
Nathan Drayson, Commonwealth Scientific and Industrial Research Organization
Reagan M. Errera, NOAA Great Lakes Environmental Research Laboratory
Virginia Fernandez, Universidad de la Republica
Dariusz Ficek, Akademia Pomorska w Słupsku
Cédric G. Fichot, Boston University
Peter Gege, Deutsches Zentrum für Luft- und Raumfahrt (DLR)
Claudia Giardino, Consiglio Nazionale delle Ricerche, Institute for Electromagnetic Sensing of the Environment
Anatoly A. Gitelson, School of Natural Resources
Steven R. Greb, University of Wisconsin-Madison
Hayden Henderson, Michigan Technological UniversityFollow
Hiroto Higa, Yokohama National University
Abolfazl Irani Rahaghi, Eawag - Swiss Federal Institute of Aquatic Science and Technology
Cédric Jamet, Université du Littoral Côte d‘Opale
Dalin Jiang, University of Stirling
Thomas Jordan, Plymouth Marine Laboratory
Kersti Kangro, Tartu Ülikool
Jeremy A. Kravitz, NASA Ames Research Center

Document Type


Publication Date



Great Lakes Research Center


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.

Publisher's Statement

© The Author(s) 2023. Publisher’s version of record:

Publication Title

Scientific Data

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


Publisher's PDF

Included in

Life Sciences Commons



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.