Mineral mapping with airborne hyperspectral thermal infrared remote sensing at Cuprite, Nevada, USA

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Abstract

This is a case example of mineral mapping of unaltered and altered rocks at the Cuprite mining district, southwestern Nevada using the Spatially Enhanced Broadband Array Spectrograph System (SEBASS), a thermal infrared hyperspectral sensor that collects radiance measurements in the mid-wave infrared and thermal infrared portions of the electromagnetic spectrum. Cuprite, Nevada has been a test bed for a variety of multispectral and hyperspectral sensors that have predominantly covered the visible through short-wave infrared portion of the electromagnetic spectrum. In 2008, 20 SEBASS flight lines were collected at an average altitude of 4,735 m yielding an average 3.35 m ground sample distance (GSD). Rock forming and alteration minerals found in this mining district have reststrahlen features (emission minima due to fast changes in refractive index with wavelength) in the thermal infrared portion of the electromagnetic spectrum (7.5-13.5 µm). Mineral mapping with hyperspectral thermal infrared data provides unique and complementary information to visible-shortwave (0.4-2.5 µm) hyperspectral data. Mineral maps were produced using a spectral feature fitting algorithm with publicly available mineral spectral libraries containing signatures. These mineral maps were compared to the geological and alteration maps along with mineral maps generated by previous studies of visible-shortwave infrared hyperspectral sensors to assess some of the difference in mineral mapping with a hyperspectral thermal infrared sensor. This study shows that hyperspectral thermal infrared data can spectrally map rock forming minerals associated with unaltered rocks and alteration minerals associated with different phases of alteration in altered rocks at Cuprite, Nevada.

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Riley, D. N., & Hecker, C. A. (2013). Mineral mapping with airborne hyperspectral thermal infrared remote sensing at Cuprite, Nevada, USA. In Remote Sensing and Digital Image Processing (Vol. 17, pp. 495–514). Springer International Publishing. https://doi.org/10.1007/978-94-007-6639-6_24

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