Theoretical Principles and Perspectives of Hyperspectral Imaging Applied to Sediment Core Analysis

Abstract

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.

Localization and recognition of specific targets in land-based hyperspectral images based on combined spatial and spectral information

“…Therefore, the traditional hyperspectral imaging technology is also called hyperspectral remote sensing technology, and the hyperspectral images obtained based on the remote sensing platform are called hyperspectral remote sensing images. Because hyperspectral images contain rich spatial and spectral information, hyperspectral imaging has unique advantages in classification and detection of ground objects, and is widely used in agriculture, medicine, military and other fields [2][3][4][5][6][7]. In recent years, with the development of landbased imaging platforms and the continuous improvement of miniaturization and intelligence of imaging spectrometers, scholars have gradually attached importance to the study of land-based hyperspectral images [8].…”

A new index for the rapid generation of chlorophyll time series from hyperspectral imaging of sediment cores

“…Hyperspectral imaging is a method based on spectral reflectance remote sensing from the surface of sediment cores and is an emerging tool in paleolimnology because of its detailed representation of sediment cores (Ghanbari et al 2020; Jacq et al 2022; Zhang and Zhang 2022). This method shares similarities in its underlying principles with VRS, including capturing the reflectance properties of sediments, offering high spectral resolution, and identifying the spectral features associated with different components within the sediment.…”

“…Visible near‐infrared (VNIR) reflectance indices are a simple way of exploiting chlorophyll information, and so rigorous development of such indices will improve their prediction of chlorophyll concentrations. Recent progress has been made in model development for high‐resolution sediment core chlorophyll reconstruction by comparing laboratory analysis with remotely sensed hyperspectral data (Jacq et al 2022; Zhang and Zhang 2022), and several spectral indices have been used to estimate chlorophylls and their degradation products (Van Exem et al 2022). Non‐parametric models are usually applied, principally partial least squares regression, using a set of input–output training data to estimate absolute chlorophyll concentrations.…”

STLAR: A localization and authenticity recognition method for specific targets based on land‐based hyperspectral images

“…Introduction: Hyperspectral images contain rich spatial and spectral information, which gives hyperspectral imaging unique advantages in the classification and detection of ground objects. Hyperspectral imaging is widely used in agriculture, medicine, military and other fields [1][2][3][4]. In recent years, with the development of land-based imaging platforms and the continuous improvement of imaging spectrometers, scholars have gradually attached importance to the study of land-based hyperspectral images [5].…”