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Journal Article

Automatic element and mineral detection in thin sections using hyperspectral transmittance imaging microscopy (HyperTIM)

Authors
/persons/resource/hdaemp

Daempfling,  Helge L. C.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/chmielke

Mielke,  Christian
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/nicolek

Koellner,  Nicole
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/melorenz

Lorenz,  Melanie
5.1 Library and Information Services, 5.0 Geoinformation, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Rogass,  Christian
External Organizations;

Altenberger,  Uwe
External Organizations;

/persons/resource/dharlov

Harlov,  D. E.
3.6 Chemistry and Physics of Earth Materials, 3.0 Geochemistry, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Knoper,  Michael
External Organizations;

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Fulltext (public)

5011965.pdf
(Publisher version), 6MB

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Citation

Daempfling, H. L. C., Mielke, C., Koellner, N., Lorenz, M., Rogass, C., Altenberger, U., Harlov, D. E., Knoper, M. (2022): Automatic element and mineral detection in thin sections using hyperspectral transmittance imaging microscopy (HyperTIM). - European Journal of Mineralogy, 34, 3, 275-284.
https://doi.org/10.5194/ejm-34-275-2022


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5011965
Abstract
In this study we present a novel method for the automatic detection of minerals and elements using hyperspectral transmittance imaging microscopy measurements of complete thin sections (HyperTIM). This is accomplished by using a hyperspectral camera system that operates in the visible and near-infrared (VNIR) range with a specifically designed sample holder, scanning setup, and a microscope lens. We utilize this method on a monazite ore thin section from Steenkampskraal (South Africa), which we analyzed for the rare earth element (REE)-bearing mineral monazite ((Ce,Nd,La)PO4), with high concentrations of Nd. The transmittance analyses with the hyperspectral VNIR camera can be used to identify REE minerals and Nd in thin sections. We propose a three-point band depth index, the Nd feature depth index (NdFD), and its related product the Nd band depth index (NdBDI), which enables automatic mineral detection and classification for the Nd-bearing monazites in thin sections. In combination with the average concentration of the relative Nd content, it permits a destruction-free, total concentration calculation for Nd across the entire thin section.