The large-area material maps presented here were designed to aid in the identification of mineral groups in exposed rocks, soils, mine waste rock, and mill tailings on the Earth?s surface. Many man-made materials have spectral absorption features in the shortwave infrared region of the electromagnetic spectrum that can appear similar to those of various mineral groups at the spectral and spatial resolutions of Landsat and ASTER satellite data. For example, many plastics, asphalt, and other organic materials show deep absorption between 2.30 and 2.40 micrometers caused by a C-H combination band (Clark, 1999). This absorption can mimic those of the clay-sulfate-mica-marble mineral group detectable using Landsat Thematic Mapper (Rockwell, 2013a) and Operational Land Imager data, and the carbonate-propylitic mineral group detectable using the employed ASTER data analysis methodology (Rockwell, 2012). Some construction materials, including fine aggregates used in some asphalt shingles, have absorptions near 2.2 micrometers (Clark and others, 2007) that will be identified as the sericite-smectite mineral group in the ASTER-derived results. Therefore, mineral groups are often erroneously detected in built-up areas such as cities, towns, and along roadways. Reflections between man-made objects can also result in spurious spectral responses in such areas.
Scenes of Landsat and ASTER satellite data were selected based on several criteria, the most important of which are that the presence of clouds, smoke, haze, and snow is minimized, and that the scenes be acquired as close as possible to the northern hemisphere summer solstice in mid-June to insure maximal solar irradiance (solar elevation angle) and minimal terrain shadow. The number of scene acquisition dates was minimized by selecting as many high-quality scenes from a single satellite overpass (path, or swath) as possible (optimal scenes from a single swath acquired on the same day). Given these criteria, there may be substantial differences in scene acquisition date between scenes in a given swath and between those of adjacent swaths. The varying scene acquisition dates may result in seams of identified surface materials between scenes of the same and adjacent swaths, as the automated analysis methodologies utilize statistics generated from the data being processed, which are most often individual scenes. Most Landsat and ASTER scenes are analyzed individually and the resultant maps are then mosaicked into a single map. In rare cases, several scenes are mosaicked together prior to analysis. Variations in soil moisture and vegetation growth stage between scenes are another possible cause of seams in analysis results.
ASTER visible to near-infrared (VNIR) and short-wave infrared (SWIR) data are each collected by a unique telescope and detector array. In rare cases, the data in an ASTER scene collected by these two sensor systems are geometrically mis-registered to each other, resulting in corrupted pixel spectra. The VNIR data of one pixel will be combined with the SWIR data of another pixel located 30-100 meters away. For such scenes, the automated analysis methodology will result in an overabundance of pixels identified as ?advanced argillic +/- ferric iron? (assigned a color of red in the maps) in areas where clay, sulfate, and mica minerals are abundant. Examples of scenes with such erroneous results are in the Independence Range in northern Nevada, and the area surrounding the Tintic mining district in the East Tintic Mountains near Eureka, Utah.
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Comparison of ASTER- and AVIRIS-derived mineral and vegetation maps of the White Horse replacement alunite deposit and surrounding area, Marysvale volcanic field, Utah
Mineral and vegetation maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, generated from ASTER satellite data
Evaluation of detailed and automated methodologies for hydrothermal alteration mapping from space: application to geoenvironmental and mineral resource assessments at the scale of watersheds and permissive tracts (abstract and multimedia PowerPoint presentation)
Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado
Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado
Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data
Digital maps of hydrothermal alteration type, key mineral groups, and green vegetation of the western United States derived from automated analysis of ASTER satellite data
Preliminary materials mapping in the Park City region for the Utah USGS-EPA Imaging Spectroscopy Project using both high- and low-altitude AVIRIS data
Spectroscopic mapping of the White Horse alunite deposit, Marysvale volcanic field, Utah: evidence of a magmatic component
Identification of quartz and carbonate minerals across northern Nevada using ASTER thermal infrared emissivity data-Implications for geologic mapping and mineral resource investigations in well-studied and frontier areas
Remote detection of argillic alteration in quartzites and quartz arenites above and distal to porphyry Cu and Mo deposits: implications for assessments of concealed deposits
Mapping argillic and advanced argillic alteration in volcanic rocks, quartzites, and quartz arenites in the western Richfield 1° x 2° quadrangle, southwestern Utah, using ASTER satellite data
Remote sensing for environmental site screening and watershed evaluation in Utah mine lands: East Tintic Mountains, Oquirrh Mountains, and Tushar Mountains