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dc.contributor.authorKruse, Fred A.
dc.contributor.authorTaranik, James V.
dc.contributor.authorCoolbaugh, Mark
dc.contributor.authorMichaels, Joshua
dc.contributor.authorLittlefield, Elizabeth F.
dc.contributor.authorCalvin, Wendy M.
dc.contributor.authorMartini, Brigette A.
dc.date2011
dc.date.accessioned2014-12-05T19:36:26Z
dc.date.available2014-12-05T19:36:26Z
dc.date.issued2011
dc.identifier.citationRemote Sensing, 2011, Volume 3, pp. 1584-1602
dc.identifier.urihttp://hdl.handle.net/10945/43861
dc.descriptionThe article of record as published may be located at http://dx.doi.org/10.3390/rs3081584en_US
dc.description.abstractThe Hyperspectral Infrared Imager (HyspIRI) is a proposed NASA satellite remote sensing system combining a visible to shortwave infrared (VSWIR) imaging spectrometer with over 200 spectral bands between 0.38 and 2.5 μm and an 8-band thermal infrared (TIR) multispectral imager, both at 60 m spatial resolution. Short Wave Infrared (SWIR) (2.0â 2.5 μm) simulation results are described here using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data in preparation for the future launch. The simulated data were used to assess the effect of the HyspIRI 60 m spatial resolution on the ability to identify and map minerals at hydrothermally altered and geothermal areas. Mineral maps produced using these data successfully detected and mapped a wide variety of characteristic minerals, including jarosite, alunite, kaolinite, dickite, muscovite-illite, montmorillonite, pyrophyllite, calcite, buddingtonite, and hydrothermal silica. Confusion matrix analysis of the datasets showed overall classification accuracy ranging from 70 to 92% for the 60 m HyspIRI simulated data relative to 15 m spatial resolution data. Classification accuracy was lower for similar minerals and smaller areas, which were not mapped well by the simulated 60 m HyspIRI data due to blending of similar signatures and spectral mixing with adjacent pixels. The simulations demonstrate that HyspIRI SWIR data, while somewhat limited by their relatively coarse spatial resolution, should still be useful for mapping hydrothermal/geothermal systems, and for many other geologic applications requiring mineral mapping.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.titleEffect of Reduced Spatial Resolution on Mineral Mapping Using Imaging Spectrometry - Examples Using Hyperspectral Infrared Imager (HyspIRI)-Simulated Dataen_US
dc.typeArticleen_US
dc.contributor.departmentPhysics
dc.subject.authorimaging spectrometryen_US
dc.subject.authorhyperspectralen_US
dc.subject.authorHSIen_US
dc.subject.authormineral mappingen_US
dc.subject.authorHyspIRI simulationen_US
dc.subject.authorspatial resolution modelingen_US
dc.description.funderThis research was partially sponsored by NASA under NASA Grant NNX10AF99G at the University of Nevada, Reno (UNR). Portions of this effort were also partially supported by the Arthur Brant Laboratory for Exploration Geophysics at UNR. Additional research and manuscript preparation was done after the corresponding author changed employment from UNR to the Naval Postgraduate School, Monterey, CA. Ormat Nevada Inc. provided access to their geothermal properties for reconnaissance, field verification, and field spectral measurements.en_US


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