Cécile Pignol
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Cécile Pignol has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Bernard Fanget
Environnements, Dynamiques et Territoires de Montagne
1 shared publication - Didier Coquin
LISTIC, University Savoie Mont Blanc
1 shared publication - Fabien Arnaud
EDYTEM, Université Savoie Mont-Blanc, CNRS, Chambéry, France
1 shared publication - Kévin Jacq
Normandie Université, UNIROUEN, UNICAEN, CNRS, M2C, 76000 Rouen, France
1 shared publication - Maxime Debret
UMR 6143 M2C Laboratoire Morphodynamique Continentale et Côtière, Department of Geoscience, Université de Rouen Normandie, France
1 shared publication - Pierre Sabatier
EDYTEM, Université Savoie Mont Blanc, CNRS, Bâtiment Pôle Montagne, 5 bd de la mer Caspienne, Le Bourget du Lac, France
1 shared publication
Latest Publications
- Open Access
- 1 June 2022
- Published by MDPI AG in Quaternary
- Vol. 5 (2) , 28
Theoretical Principles and Perspectives of Hyperspectral Imaging Applied to Sediment Core Analysis
Hyperspectral imaging is a recent technology that has been gaining popularity in the geosciences since the 1990s, both in remote sensing and in the field or laboratory. Indeed, it allows the rapid acquisition of a large amount of data that are spatialized on the studied object with a low-cost, compact, and automatable sensor. This practical article aims to present the current state of knowledge on the use of hyperspectral imaging for sediment core analysis (core logging). To use the full potential of this type of sensor, many points must be considered and will be discussed to obtain reliable and quality data to extract many environmental properties of sediment cores. Hyperspectral imaging is used in many fields (e.g., remote sensing, geosciences and artificial intelligence) and offers many possibilities. The applications of the literature will be reviewed under five themes: lake and water body trophic status, source-to-sink approaches, organic matter and mineralogy studies, and sedimentary deposit characterization. Afterward, discussions will be focused on a multisensor core logger, data management, integrated use of these data for the selection of sample areas, and other opportunities. Through this practical article, we emphasize that hyperspectral imaging applied to sediment cores is still an emerging tool and shows many possibilities for refining the understanding of environmental processes.
- 1 June 2022
- Published by MDPI AG in Quaternary
- Vol. 5 (2) , 28
Open AccessTheoretical Principles and Perspectives of Hyperspectral Imaging Applied to Sediment Core Analysis
Hyperspectral imaging is a recent technology that has been gaining popularity in the geosciences since the 1990s, both in remote sensing and in the field or laboratory. Indeed, it allows the rapid acquisition of a large amount of data that are spatialized on the studied object with a low-cost, compact, and automatable sensor. This practical article aims to present the current state of knowledge on the use of hyperspectral imaging for sediment core analysis (core logging). To use the full potential of this type of sensor, many points must be considered and will be discussed to obtain reliable and quality data to extract many environmental properties of sediment cores. Hyperspectral imaging is used in many fields (e.g., remote sensing, geosciences and artificial intelligence) and offers many possibilities. The applications of the literature will be reviewed under five themes: lake and water body trophic status, source-to-sink approaches, organic matter and mineralogy studies, and sedimentary deposit characterization. Afterward, discussions will be focused on a multisensor core logger, data management, integrated use of these data for the selection of sample areas, and other opportunities. Through this practical article, we emphasize that hyperspectral imaging applied to sediment cores is still an emerging tool and shows many possibilities for refining the understanding of environmental processes.