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Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy

One of the strengths of laser-induced breakdown spectroscopy (LIBS) is that a large amount of data can be measured relatively easily in a short time, which makes LIBS interesting in many areas, from geomaterial analysis with portable handheld instruments to applications for the exploration of planet...

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Autores principales: Rammelkamp, Kristin, Schröder, Susanne, Pisello, Alessandro, Ortenzi, Gianluigi, Sohl, Frank, Unnithan, Vikram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346995/
https://www.ncbi.nlm.nih.gov/pubmed/37448057
http://dx.doi.org/10.3390/s23136208
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author Rammelkamp, Kristin
Schröder, Susanne
Pisello, Alessandro
Ortenzi, Gianluigi
Sohl, Frank
Unnithan, Vikram
author_facet Rammelkamp, Kristin
Schröder, Susanne
Pisello, Alessandro
Ortenzi, Gianluigi
Sohl, Frank
Unnithan, Vikram
author_sort Rammelkamp, Kristin
collection PubMed
description One of the strengths of laser-induced breakdown spectroscopy (LIBS) is that a large amount of data can be measured relatively easily in a short time, which makes LIBS interesting in many areas, from geomaterial analysis with portable handheld instruments to applications for the exploration of planetary surfaces. Statistical methods, therefore, play an important role in analyzing the data to detect not only individual compositions but also trends and correlations. In this study, we apply two approaches to explore the LIBS data of geomaterials measured with a handheld device at different locations on the Aeolian island of Vulcano, Italy. First, we use the established method, principal component analysis (PCA), and second we adopt the principle of the interesting features finder (IFF), which was recently proposed for the analysis of LIBS imaging data. With this method it is possible to identify spectra that contain emission lines of minor and trace elements that often remain undetected with variance-based methods, such as PCA. We could not detect any spectra with IFF that were not detected with PCA when applying both methods to our LIBS field data. The reason for this may be the nature of our field data, which are subject to more experimental changes than data measured in laboratory settings, such as LIBS imaging data, for which the IFF was introduced first. In conclusion, however, we found that the two approaches complement each other well, making the exploration of the data more intuitive, straightforward, and efficient.
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spelling pubmed-103469952023-07-15 Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy Rammelkamp, Kristin Schröder, Susanne Pisello, Alessandro Ortenzi, Gianluigi Sohl, Frank Unnithan, Vikram Sensors (Basel) Article One of the strengths of laser-induced breakdown spectroscopy (LIBS) is that a large amount of data can be measured relatively easily in a short time, which makes LIBS interesting in many areas, from geomaterial analysis with portable handheld instruments to applications for the exploration of planetary surfaces. Statistical methods, therefore, play an important role in analyzing the data to detect not only individual compositions but also trends and correlations. In this study, we apply two approaches to explore the LIBS data of geomaterials measured with a handheld device at different locations on the Aeolian island of Vulcano, Italy. First, we use the established method, principal component analysis (PCA), and second we adopt the principle of the interesting features finder (IFF), which was recently proposed for the analysis of LIBS imaging data. With this method it is possible to identify spectra that contain emission lines of minor and trace elements that often remain undetected with variance-based methods, such as PCA. We could not detect any spectra with IFF that were not detected with PCA when applying both methods to our LIBS field data. The reason for this may be the nature of our field data, which are subject to more experimental changes than data measured in laboratory settings, such as LIBS imaging data, for which the IFF was introduced first. In conclusion, however, we found that the two approaches complement each other well, making the exploration of the data more intuitive, straightforward, and efficient. MDPI 2023-07-07 /pmc/articles/PMC10346995/ /pubmed/37448057 http://dx.doi.org/10.3390/s23136208 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rammelkamp, Kristin
Schröder, Susanne
Pisello, Alessandro
Ortenzi, Gianluigi
Sohl, Frank
Unnithan, Vikram
Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy
title Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy
title_full Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy
title_fullStr Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy
title_full_unstemmed Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy
title_short Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy
title_sort explorative data analysis methods: application to laser-induced breakdown spectroscopy field data measured on the island of vulcano, italy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346995/
https://www.ncbi.nlm.nih.gov/pubmed/37448057
http://dx.doi.org/10.3390/s23136208
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