Methods and Applications of Hyperspectral Imaging that Rapidly Identify and Differentiate Geological Minerals and Biominerals

Dear Colleagues,

Mineral identification and characterization work has benefited in recent years from advances in spectral and hyperspectral imaging methods that provide compositional information at high spatial resolution. Imaging methods based on Raman scattering, infrared and near infrared absorption and reflectance, and X-ray fluorescence have been used to study the mineral composition in both geological and biological samples. While these advances have been transformative, many challenges remain. For example, the complexity of spectral shape variation due to sample heterogeneity, nonuniform illumination, noise, and system-based artifacts make it difficult to quantitate sample composition. These same agents ultimately decrease the reliability of qualitative results. While many spectral imaging methods have the advantage of not requiring sample preparation, the development of training samples that adequately encompass the range of variation encountered in samples is exceedingly challenging. This Special Issue aims to bring together studies from all areas of spectral imaging of minerals. Novel instrumental and methodological approaches that expand the quantitative or qualitative capabilities of the technique for rapid mineral analysis are encouraged. Studies involving data processing and chemometric methods for image segmentation, pixel classification, data reduction, spatio-spectral pattern recognition, mineral identification, within mineral variability, visualization, and data rendering techniques are also sought. These include automated methods that remove or reduce the reliance on user assistance and training data, as well as methods that utilize machine learning and artificial intelligence. Applications in which spectral imaging has provided a new understanding regarding mineralization, mineral distribution or orientation, and mineral inclusions are also desired. The hope is that this Special Issue will bring together work that represents the latest advances in the spectral imaging field towards a better understanding of minerals and mineral ensembles.

Prof. Dr. John F Turner II
Guest Editor

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• hyperspectral and spectral imaging
• vibrational spectroscopy
• X-ray fluorescence
• mineral and biomineral identification
• mineral inclusions and crystallization
• multivariate analysis
• remote sensing
• standoff detection
• microscopy
• machine learning and deep learning
• artificial neural networks
• imaging instrumentation
• data visualization