Linear Deconvolution Results For Site DS-2 (3-component-model-1)
Dates
Publication Date
2018-02-28
Time Period
2007-09-03
Citation
Hubbard, B.E., Hooper, D.M., Mars, J.C., and Solano, Federico, 2018, Linear Deconvolution Mineral Maps of Compositionally Variable Dune Fields in the Western United States and Alaska: U.S. Geological Survey data release, https://doi.org/10.5066/F7CC0XTR.
Summary
These geotiffs represent the raster GIS outputs of Linear Deconvolution (Linear Spectral Unmixing) analysis of ASTER image pixels covering various sand dune and sand sheet fields throughout the Western United States and Alaska. This particular dune field (DS-2) represents Big Dune, Nevada and the surrounding areas of alluvial fan sediments along the Amargosa River valley. The accompanying zip file contains linear deconvolution-derived mineral fractional abundance maps for a three-component mixture model of Quartz, Potassic Feldspars and "Andesitic Volcanic Glass", as well as RMS and residual errors. Each geotiff layer has an associated metadata file with further details.
Summary
These geotiffs represent the raster GIS outputs of Linear Deconvolution (Linear Spectral Unmixing) analysis of ASTER image pixels covering various sand dune and sand sheet fields throughout the Western United States and Alaska. This particular dune field (DS-2) represents Big Dune, Nevada and the surrounding areas of alluvial fan sediments along the Amargosa River valley. The accompanying zip file contains linear deconvolution-derived mineral fractional abundance maps for a three-component mixture model of Quartz, Potassic Feldspars and "Andesitic Volcanic Glass", as well as RMS and residual errors. Each geotiff layer has an associated metadata file with further details.
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DS2-qtz-kspar-glass.xml Original FGDC Metadata
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10.87 KB
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DS2-qtz-kspar-glass.zip
1.48 MB
application/zip
Related External Resources
Type: Related Primary Publication
Hubbard, B.E., Hooper, D.M., Solano, Federico, and Mars, J.C., 2018, Determining mineralogical variations of aeolian deposits using thermal infrared emissivity and linear deconvolution methods: Aeolian Research, v. 30, p. 54-96, https://doi.org/10.1016/j.aeolia.2017.12.001.
