Corescan Hyperspectral Core Imager, Mark III system data collected for the characterization of mineral resources near Nabesna, Alaska, 2014-2016

• Main Authors: Hoefen, Todd M, Johnson, Michaela R, Kokaly, Raymond, Graham, Garth E, Kelley, Karen Duttweiler, Hubbard, Bernard E
• Format: Dataset
• Language: unknown
• Published: U.S. Geological Survey 2018
• Subjects: alaska range; Alaska
• Online Access: https://dx.doi.org/10.5066/f7057dwm; https://www.sciencebase.gov/catalog/item/59ef6726e4b0220bbd98d38c

Corescan Hyperspectral Core Imager Mark III (HCI-III) system data were acquired for hand samples, and subsequent billets made from the hand samples, collected during the U.S. Geological Survey (USGS) 2014, 2015, and 2016 field seasons in the Nabesna area of the eastern Alaska Range. This area contains exposed porphyry deposits and hand samples were collected throughout the region in support of the HyMap imaging spectrometer survey (https://doi.org/10.5066/F7DN435W) (Kokaly and others, 2017a). The HCI-III system consists of three different components. The first is an imaging spectrometer which collects reflectance data with a spatial resolution of approximately 500 nanometers (nm) for 514 spectral channels covering the 450-2,500 nm wavelength range of the electromagnetic spectrum (Martini and others, 2017). The second is a spectrally calibrated RGB camera that collects high resolution imagery of the samples with a 50 micrometer pixel size. The third component is a three-dimensional (3D) laser profiler that measures sample texture, surface features and shape with a vertical resolution of 20 micrometer (Martini and others, 2017). The imaging spectrometer raw data were collected with an average bandpass of approximately 6 nm across the Short Wave Infrared (SWIR) but smoothing functions applied by Corescan during the conversion of raw data to reflectance result in a relative bandpass of approximately 13 nm in the data delivered to the USGS. Wavelength evaluations of the imaging spectrometer data revealed that the supplied wavelength values should be shifted and, thus, adjustments were made to the wavelength positions (Kokaly and others, 2017c). The wavelength and bandpass evaluation results are provided in the 'Calibration' section of this data release and were used to adjust the Corescan reflectance data. The calibrated Corescan data were combined into a reflectance data cube mosaic and are provided in the 'HyperspectralCalibrated' section. Calibrated reflectance data from Corescan were processed using the Material Identification and Characterization Algorithm (MICA), a module of the USGS PRISM (Processing Routines in IDL for Spectroscopic Measurements) software (Kokaly, 2011). MICA identifies the spectrally predominant mineral(s) in each pixel of imaging spectrometer data by comparing continuum-removed spectral features in the pixel's reflectance spectrum to continuum-removed absorption features in reference spectra of minerals and other materials. For each pixel, the reference spectrum with the highest fit value identifies the predominant mineral class. White mica wavelength position was computed for each pixel with spectrally predominant muscovite or illite. The computation was made using a function of the USGS PRISM software (Kokaly, 2011). The white mica wavelength values were output as a classification image, with classes in 1 nm increments.