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Outline

Title
Abstract
Introduction
Background
Materials and Methods
XRFS, RS, and Libs Analysis
Data Processing
Classification for Multianalyzer Data Fusion
Results and Discussion
Multianalyzer Data Fusion Results
Summary and Future Prospects
References

Multianalyzer Spectroscopic Data Fusion for Soil Characterization

Profile image of Richard HarkRichard Hark

Applied Sciences

https://doi.org/10.3390/APP10238723
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19 pages

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Abstract

The ability to rapidly conduct in-situ chemical analysis of multiple samples of soil and other geological materials in the field offers many advantages over a traditional approach that involves collecting samples for subsequent examination in the laboratory. This study explores the application of complementary spectroscopic analyzers and a data fusion methodology for the classification/discrimination of >100 soil samples from sites across the United States. Commercially available, handheld analyzers for X-ray fluorescence spectroscopy (XRFS), Raman spectroscopy (RS), and laser-induced breakdown spectroscopy (LIBS) were used to collect data both in the laboratory and in the field. Following a common data pre-processing protocol, principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA) were used to build classification models. The features generated by PLSDA were then used in a hierarchical classification approach to assess the relative advantage o...

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