Dataset Information

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

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.

SUBMITTER: Lehmann MK

PROVIDER: S-EPMC9935528 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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

Lehmann Moritz K MK Gurlin Daniela D Pahlevan Nima N Alikas Krista K Conroy Ted T Anstee Janet J Balasubramanian Sundarabalan V SV Barbosa Cláudio C F CCF Binding Caren C Bracher Astrid A Bresciani Mariano M Burtner Ashley A Cao Zhigang Z Dekker Arnold G AG Di Vittorio Courtney C Drayson Nathan N Errera Reagan M RM Fernandez Virginia V Ficek Dariusz D Fichot Cédric G CG Gege Peter P Giardino Claudia C Gitelson Anatoly A AA Greb Steven R SR Henderson Hayden H Higa Hiroto H Rahaghi Abolfazl Irani AI Jamet Cédric C Jiang Dalin D Jordan Thomas T Kangro Kersti K Kravitz Jeremy A JA Kristoffersen Arne S AS Kudela Raphael R Li Lin L Ligi Martin M Loisel Hubert H Lohrenz Steven S Ma Ronghua R Maciel Daniel A DA Malthus Tim J TJ Matsushita Bunkei B Matthews Mark M Minaudo Camille C Mishra Deepak R DR Mishra Sachidananda S Moore Tim T Moses Wesley J WJ Nguyễn Hà H Novo Evlyn M L M EMLM Novoa Stéfani S Odermatt Daniel D O'Donnell David M DM Olmanson Leif G LG Ondrusek Michael M Oppelt Natascha N Ouillon Sylvain S Pereira Filho Waterloo W Plattner Stefan S Verdú Antonio Ruiz AR Salem Salem I SI Schalles John F JF Simis Stefan G H SGH Siswanto Eko E Smith Brandon B Somlai-Schweiger Ian I Soppa Mariana A MA Spyrakos Evangelos E Tessin Elinor E van der Woerd Hendrik J HJ Vander Woude Andrea A Vandermeulen Ryan A RA Vantrepotte Vincent V Wernand Marcel R MR Werther Mortimer M Young Kyana K Yue Linwei L

Scientific data 20230216 1

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 ch ...[more]

PMID: 36797273

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Project description:This article presents a dataset of hyperspectral images of handwriting samples collected from 54 individuals. The purpose of the presented dataset is to further explore the use of hyperspectral imaging in document image analysis and to benchmark the performance of forensic analysis methods for hyperspectral document images. Each hyperspectral cube in the dataset has a spatial resolution of 512 × 650 pixels and contains 149 spectral channels in the spectral range of 478-901 nm. All the individuals have different personalities and have their writing patterns. The information of age and gender of each individual is collected. Each subject has written twenty-eight sentences using 12 different varieties of pens from different brands in blue color, each approximately 9 words or 33 characters long, all English alphabets in capital and small cases, digits from 0 to 9. The previous methods use synthetic mixed samples created by joining different parts of the images from the UWA WIHSI dataset.Each document consists of real mixed samples written withdifferent pens and by different writers with a variety of mixing ratios of inks and writers for forensic analysis.The standard A4 pages, each weighing 70 gs and manufactured by "AA" company, are used for data collection. The handwritten notes written by each subject with different pens are annotated in rectangular boxes. This dataset can be used for several tasks related to hyperspectral document image analysis and document forensic analysis including, handwritten optical character recognition, ink mismatch detection, writer identification at sentence, word, and character-level, handwriting-based gender classification, handwriting-based age prediction, handwritten word segmentation, and word generation. This dataset was designed and collected by the research team at the Artificial intelligence and Computer Vision Lab (iVision), Institute of Space Technology, Pakistan, and the hyperspectral images were acquired through imaging spectroscopy in the visible wavelength range at Wageningen University & Research, the Netherlands.

Dataset Information

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

Publications

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

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