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Spectral mixture modeling: A new analysis of rock and soil types at the Lander 1 site
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Spectral reflectance response of big sagebrush to hydrocarbon-induced stress in the Bighorn Basin, Wyoming
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Characterization of radiometric calibration of Landsat-4 TM reflective bands
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An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data
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Ground water appraisal of Long Valley, White Pine and Elko Counties, Nevada
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Separation of soil-plant spectral mixtures by factor analysis
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Spectral characterization of the Landsat Thematic Mapper sensor
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The spectral response of sagebrush in areas of hydrocarbon production
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A fast algorithm for the decomposing of multispectral data into mixtures
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Calibration of Landsat data for sparsely vegetated semi-arid range- lands
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Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data
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Roberts, D.A., M.O. Smith, and J.B. Adams, 1993. Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data, Remote Sensing of Environment, 44:255-269.
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Computation with physical values from Landsat Digital Data
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The least-squares mixing models to generate fraction images derived from remote sensing multispectral data
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Shimabukuro, Y.E., and J.A. Smith, 1991. The least-squares mixing models to generate fraction images derived from remote sensing multispectral data, IEEE Transactions on Geoscience and Remote Sensing, 29(1):16-20.
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Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis
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Smith, M.O., P.E. Johnson, and J.B. Adams, 1985. Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis, Proceedings of the 5th Lunar and Planetary Science Conference, Part 2, Journal of Geophysical Research, Vol. 90, Supplement, pp. c797-c804.
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Vegetation in desert: I. A regional measure of abundance from multispectral image
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Smith, M.O., S.L. Ustin, J.B. Adams, and A.R. Gillespie, 1990. Vegetation in desert: I. A regional measure of abundance from multispectral image, Remote Sensing of Environment, 31:1-26.
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