![rs=w_1280 Spectralucation July Using Spectral Composition Data](https://lkiconsulting.com/wp-content/uploads/2023/01/rsw_1280.webp)
If you are unaware, hyperspectral data is renown for producing mineral data; biotite, white mica, tourmaline, sulfates, carbonates, Fe-oxides… the list is long and diverse. However, spectral datasets also yield “composition” data, namely crystallinity and wavelength data. In this post we’re going to focus on some of the more common features and mineral groups they are associated with so that you can utilize these features in your data interpretations and models with confidence. Crystallinity (X) In reflectance spectroscopy, crystallinity is defined as the relative degree of structural order of a mineral. In practice, crystallinity is commonly used as a temperature of formation proxy. Caution, however, should be applied before labeling low crystallinity as “supergene” and high crystallinity as “hypogene” – understanding the paragenesis of a deposit is essential before allocating labels. Wavelength (L) In reflectance spectroscopy, the wavelength of absorption features for certain minerals is used to determine the speciation or chemistry of the mineral species. Minerals have diagnostic absorption features that are used to “fingerprint” them, the minimum of some of these absorption features will change with cation substitution in the mineral’s structure. These wavelength shifts provide information about what specific mineral species we are looking at in a mineral group; e.g., white mica -> paragonite, muscovite, phengite. Common Compositional Features Alunite 1480L: Alunite group minerals have a diagnostic absorption feature at 1480nm that varies with K-Na content, whereby at shorter wavelengths alunite is more K-rich (i.e., alunite) and at longer wavelength it is more Na-rich (i.e., natroalunite). Carbonate 2340L: variations in this feature can map variations in Ca-Mg (i.e., calcite-dolomite) within carbonates. This feature is also helpful in identifying rhodochrosite. Shortest wavelengths trend towards dolomite (~2317nm) and longer wavelengths are calcite (~2340nm) and rhodochrosite (~2369nm). Used in conjunction with a large absorption doublet at 1000nm and 1400nm helps to identify the presence of Fe in carbonates. Chlorite 2250/2350L: the diagnostic features of the spectral signature of chlorite group minerals are at 2250nm and 2350nm. These features are associated with Fe-OH and Mg-OH bonds. The shape and position of these features vary with mineral composition (i.e., Fe-Mg substitution) with shorter wavelengths reflecting an increase in Mg (i.e., clinochlore) and longer wavelengths an increase in Fe (i.e., chamosite). Iron Oxide 900L: there is a continuum between hematite and goethite spectra, whereby a crystal field absorption feature in the Fe-oxide varies between 865nm (hematite end-member) to 930nm (goethite end-member). Kaolinite 2165X: this is a crystallinity feature that looks at the relative degree of structural order in kaolinite. It is commonly used as a temperature proxy. Correctly applying this data can help highlight textural or paragenetic characteristics of the sample. White Mica 2200X: there are multiple methods to calculate white mica crystallinity, but correctly applying this data can help highlight textural or paragenetic characteristics of the sample. White Mica 2200L: chemical variations in white mica group minerals can be tracked using the 2200nm absorption feature. The minimum wavelength of this feature is positively correlated with Fe (+Mg+Mn) content and negatively correlated with total Al in both muscovite and illite. There is a range of white mica minerals from the shortest wavelength paragonite (Na ~2185-2192nm) to muscovite (K/Al ~2192-2212nm) to phengite (Fe ~2212-2225nm). |