Approximately 1,900 line square kilometers of imagery were collected using a HyMap™ sensor (Cocks and others, 1998) mounted on a modified Piper Navajo aircraft. The aircraft was flown at an altitude of approximately 5,050 m (3,480 m above the mean ground surface elevation of 1570 m) resulting in average ground spatial resolution of 6.7 m. Solar elevation and azimuth angles ranged from 42.0-48.3° (average 46.2°) and 134.2-182.4° (average 155°), respectively. HyMap measured reflected sunlight in 126 narrow channels that cover the wavelength region of 455 to 2,483 nm. Data were delivered by the operators of the sensor (HyVista Corp., Australia) in units of radiance (data are available in Kokaly and others, 2017). Radiance data were converted to reflectance with procedures adapted from Kokaly and others (2013). First, the radiance data were converted to apparent surface reflectance using a radiative transfer program, Atmospheric and Topographic Correction for airborne imagery (ATCOR-4), in rugged terrain mode (ReSe Applications, Zurich, Switzerland). The ATCOR-4 rugged terrain mode utilizes a surface elevation model to adjust illumination levels. Apparent surface reflectance values from the ATCOR-4 processing were empirically adjusted using ground-based reflectance measurements from calibration sites measured with an Analytical Spectral Devices FieldSpec® 4 (ASD FS4; ASD Inc., a Malvern PANalytical Company, Longmont, Colorado) standard resolution field spectrometer. Following the procedures adapted from Clark and others (2002), ASD FS4 data were collected from four sites in broad alluvial-fluvial gravel bars that were minimally vegetated and mostly lichen-free. The four sites covered areas of 0.31, 0.36, 0.51 and 0.76 hectares (ha). In the HyMap data, 86, 101, 143, and 210 HyMap pixels covered these areas, respectively. Although the rocks in these areas were mixed and varied at the fine spatial scale, at the HyMap 6 m pixel scale the calibration areas were spectrally homogeneous. The bare fiber optic of the ASD was held at shoulder height (~1.4 m) while walking around the calibration site and recording measurements of reflected sunlight relative to a Spectralon® white reference panel. The integration times for dark current and white reference panel were set to 10 and 24 seconds, respectively. The ASD was configured for 6 second averages for each recording of surface reflectance. A great number of ASD recordings were made in each calibration site: 455, 319, 420, and 310, respectively. Subsequently, the relative reflectance measurements at each site were averaged. The average relative reflectance was converted to absolute reflectance by correcting for the absorption properties of Spectralon (see the discussion of processing ASD spectra in Kokaly and Skidmore, 2015). Furthermore, offsets in reflectance between the three ASD detectors were rectified using a procedure in the USGS PRISM (Processing Routines in IDL for Spectroscopic Measurements) software (Kokaly, 2011) programmed in Interactive Data Language (IDL; Harris Geospatial Solutions, Broomfield, Colorado). PRISM functions were also used to compute multiplicative correction factors to convert HyMap apparent surface reflectance to ground-calibrated surface reflectance. Because flight lines were designed with substantial overlap, the four calibration sites could be used to directly calibrate eight of the nine flight lines. For the remaining flight line, the cross-calibration procedure of Kokaly and others (2013) was used to compute an empirical correction factor using a non-vegetated and topographically flat area overlapping with an adjacent flight line. Each flight line was geometrically-corrected using data provided by HyVista Corp. (see files provided in Kokaly and others, 2017). The images were mosaicked together using the mosaic function in ENVI (ENvironment for Visualizing Images; Harris Geospatial Solutions, Broomfield, Colorado). To improve the quality of the mosaic image, each flight line was subject to masking for clouds and cloud shadows as well as pixel averaging in areas of poorly illuminated steep terrain (steep slopes facing away from the sun’s postion in the sky). A pixel containing cloud or cloud shadow was determined by comparing radiance and reflectance levels for five HyMap channels (5, 40, 55, 74, and 105, corresponding to wavelength positions 515, 1020, 1238, 1547, and 2129 nm, respectively) against threshold values. In a pixel, if radiance or reflectance levels of any of these five channels exceeded the threshold values for cloud, the pixel was masked; thus, bright pixels were identified as cloud contaminated. If any of the these five channels were below the threshold values for cloud shadow, the pixel was masked; thus, dark pixels were identified as shadowed. The cloud and cloud shadow pixels were combined into a single mask for each flight line. Spatial filtering in ENVI was applied using clumping and sieving functions in order to add a buffer of 1 pixel around the identified cloud and cloud shadow pixels, thereby, masking out adjacent pixels that might also be affected by cloud or cloud shadowing. In the mosaicking procedure, the masked pixels are often filled in with non-masked data from adjacent flight lines because clouds and cloud shadows shifted in the time that elapsed between aircraft passes. In addition to masking for clouds and cloud shadows, flight lines were adjusted in areas of poorly illuminated terrain. Poorly-illuminated pixels were identified using the illumination output image (defining the local solar zenith angle of each pixel) of the ATCOR-4 program, which accounts for the angle of the sun at the time of the hyperspctral image collection and topographic slope and aspect to create an image of the relative illumination of each pixel. In areas with local solar zenith angles greater than 75.5 degrees, a 3x3 pixel averaging was applied to increase the signal-to-noise ratio of reflectance. As a result of the masking, pixel averaging, and mosaicking, the user may see some artifacts of the mosaic process, including: 1) areas of differening reflectance where cloud holes in one flight line were filled by data from an adjacent flight line, sometimes a single dark pixels can outline the filled-in cloud holes, and 2) areas that appear more “pixelized” (coarser spatial resolution) in regions where a steep slope was facing away from the sun’s position in the sky.