Scientific Data (Feb 2023)

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

  • Moritz K. Lehmann,
  • Daniela Gurlin,
  • Nima Pahlevan,
  • Krista Alikas,
  • Ted Conroy,
  • Janet Anstee,
  • Sundarabalan V. Balasubramanian,
  • Cláudio C. F. Barbosa,
  • Caren Binding,
  • Astrid Bracher,
  • Mariano Bresciani,
  • Ashley Burtner,
  • Zhigang Cao,
  • Arnold G. Dekker,
  • 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,
  • Dalin Jiang,
  • 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,
  • Evangelos Spyrakos,
  • Elinor Tessin,
  • Hendrik J. van der Woerd,
  • Andrea Vander Woude,
  • Ryan A. Vandermeulen,
  • Vincent Vantrepotte,
  • Marcel R. Wernand,
  • Mortimer Werther,
  • Kyana Young,
  • Linwei Yue

DOI
https://doi.org/10.1038/s41597-023-01973-y
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 14

Abstract

Read online

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.