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William R. Gnesda

Publications and source records attributed to William R. Gnesda.

2 recordsLinked to original sources

Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region

Multispectral remote sensing data acquired by the Landsat 8 Operational Land Imager (OLI) sensor were analyzed using a new, automated technique to generate a map of exposed mineral and vegetation groups in the western San Juan Mountains, Colo., and the Four Corners Region of the United States. Band ratio results were combined into displayed mineral and vegetation groups using Boolean algebra. New analysis logic has been implemented to exploit the coastal aerosol band in Landsat 8 OLI data and identify concentrations of iron sulfate minerals. These may indicate the presence of near-surface pyrite, which can be a potential nonpoint source of acid rock drainage. Zoned occurrences of iron sulfate minerals in areas surrounding and down gradient of known sources of pyrite have been mapped using this technique. They show high correlation with occurrences of jarosite-bearing mineral assemblages, as mapped using airborne imaging spectrometer data and supporting field verification surveys. Mapping the occurrence of iron sulfate minerals produced by the weathering and oxidation of pyrite in exposed hydrothermally altered rocks can also provide an important indicator of the genetic environment of alteration and the associated mineral deposit type. The automated analysis methodology is being employed to rapidly and cost-effectively generate maps of large regions of the United States in support of U.S. Geological Survey mineral resource and mineral-environmental assessments. This map, which includes the ERDAS IMAGINE thematic raster format in the data release, has been attributed by pixel value with mineral and vegetation group classification data, which can be queried in most image processing and GIS software packages.

Colorado, Utah↗

Imaging spectroscopy applied to mineral mapping over large areas: Impact of residual atmospheric artefacts in reflectance spectra on mineral identification and mapping

Around the world, imaging spectroscopy (hyperspectral imaging) has been successfully applied to mapping surface minerals over small areas. In this paper, we examine one challenge to reliably mapping surface mineral composition over large areas: the impacts of atmospheric artefacts in reflectance spectra on mineral identification. To examine these impacts, we use a set of Airborne Visible and Infrared Imaging Spectrometer-Classic (AVIRISc) data collected over ~30,000 sq. km of southern California (SoCal) in 2018. The AVIRISc2018 SoCal reflectance data showed residual atmospheric contamination in wavelength regions at the edges of strong water vapor absorption features: 1.44-1.5 µm, 1.75-1.8 µm, and 2.35-2.5 µm. These three regions of atmospheric residuals affect identification and discrimination of mineral absorption features, especially when mineral abundances are low and spectral features are weak. Of these three regions, improving atmospheric correction of imaging spectrometer data in the 2.35-2.5 µm region will result in the most enhancement in mineral identification, discrimination, and mapping. An additional region near 2.2 µm affects phyllosilicate mineral identification. The cause of the distorted reflectance in this region is still being investigated.

Conference Paper↗