Mapping the wavelength position of mineral features in hyperspectral thermal infrared data

The Wavelength Mapper is an algorithm that searches for the deepest absorption feature in each pixel of a hyperspectral image. On a per pixel basis, it extracts the wavelength position, which serves as a proxy of the mineralogy and the feature depth as a proxy for the relative abundance. This algorithm has been used with near and shortwave infrared data, but has not yet been tested on hyperspectral thermal infrared images. It is unclear what results are expected when the Wavelength Mapper algorithm is applied to hyperspectral thermal infrared data since reststrahlen features characteristically overlap in emissivity spectra. In this paper, the Wavelength Mapper is tested on a multi-flightline airborne hyperspectral TIR dataset acquired over the Yerington Batholith, Nevada. Observations were made in the 8.05–11.65 μm wavelength range to include thermal spectral features of major rock-forming minerals, and a new color ramp is created to separate quartz-rich rocks from plagioclase-rich rocks. Our results indicate that the Wavelength Mapper creates coherent spatial patterns across flightlines. The results displayed represent different types of igneous and sedimentary rocks, as well as the products of hydrothermal alteration via different colors, mainly based on the relative abundance of quartz, feldspar and garnet, as well as mica and epidote. Comparison with published maps indicate that the Wavelength Mapper represents for each pixel a parameter value that can be linked to the spectrally dominate rock-forming mineral of that area, as mapped with traditional fieldwork methods. In conclusion, the Wavelength Mapper can be applied to airborne hyperspectral TIR data to achieve a simple, repeatable, per-pixel overview map of the dominating rock-forming mineral occurrences