Sedimentary structure discrimination with hyperspectral imaging in sediment cores
Creators
- 1. Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, EDYTEM, 73000 Chambéry, France
- 2. Univ. Savoie Mont Blanc, LISTIC, 74000 Annecy, France
- 3. Institute for Geosciences and Environmental Research, University Grenoble Alpes, CNRS, IRD, Grenoble, France
- 4. Univ. Rouen Normandie, Univ. Caen, CNRS, M2C, 76821 Mont-Saint-Aignan, France
Description
The LDB17_P11Ax (IGSN: TOAE0000000243); Datation Age 1040 +/- 30 to 2017 CE by core correlation, 14C, lamina counting) core from the Bourget Lake (France) was analyzed in 2018 by hyperspectral imaging. We studied the potential of hyperspectral sensor to image a sediment cores and created machine learning models. The hyperspectral images were acquired in order to develop quantitative (estimating particle size and loss on ignition) and qualitative (detection of instantaneous events or lamina) methods.
All these methods allow to reconstruct the past environment and climate at high resolution (pixel size: 50-250 microns) and without destroying the sample for archiving for future analysis.
These images have been valorized in publications for the detection of instantaneous events with hyperspectral and combined with XRF data, for the combination of the two images into a composite image.
image (.hdr, .dat, .jpg)
Files
swir_LDB17_P11Ax_2018-10-02_10-22-36.zip
Files
(8.0 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:c4726e1bf6bf79564fd270e7fa4a5017
|
1.1 GB | Preview Download |
|
md5:42219c015c29680729975edffe8d2c03
|
6.9 GB | Preview Download |
Additional details
Related works
- Is supplemented by
- Journal article: 10.1016/j.scitotenv.2021.152018 (DOI)