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  • 1990-1994  (5)
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  • 1990-1994  (5)
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  • 1
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    In:  Automated Patter Analysis in Petroleum Exploration, London, Geological Society, vol. 17, no. 16, pp. 223-248, (ISBN 0080419208)
    Publication Date: 1992
    Keywords: Data analysis / ~ processing ; Borehole Televiewer ; Borehole geophys. ; Borehole breakouts
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  • 2
    Publication Date: 2013-08-29
    Description: The optical constants of samples of six different metals (Al, Cu, Ni, Ta, W, and Zr) exposed to space on the Long Duration Exposure Facility (LDEF) were studied by variable angle spectroscopic ellipsometry. Measurements were also carried out on portions of each sample which were shielded from direct exposure by a metal bar. A least-squares fit of the data using an effective medium approximation was then carried out, with thickness and composition of surface films formed on the metal substrates as variable parameters. The analysis revealed that exposed portions of the Cu, Ni, Ta, and Zr samples are covered with porous oxide films ranging in thickness from 500 to 1000 A. The 410 A thick film of Al2O3 on the exposed Al sample is practically free of voids. Except for Cu, the shielded portions of these metals are covered by thin non-porous oxide films characteristic of exposure to air. The shielded part of the Cu sample has a much thicker porous coating of Cu2O. The tungsten data could not be analyzed.
    Keywords: NONMETALLIC MATERIALS
    Type: NASA. Langley Research Center, LDEF: 69 Months in Space. First Post-Retrieval Symposium, Part 2; p 1005-1021
    Format: text
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  • 3
    Publication Date: 2019-07-12
    Description: A semiautomated methodology is developed for estimating cumulus cloud base heights on the basis of high spatial resolution Landsat MSS data, using various image-processing techniques to match cloud edges with their corresponding shadow edges. The cloud base height is then estimated by computing the separation distance between the corresponding generalized Hough transform reference points. The differences between the cloud base heights computed by these means and a manual verification technique are of the order of 100 m or less; accuracies of 50-70 m may soon be possible via EOS instruments.
    Keywords: METEOROLOGY AND CLIMATOLOGY
    Type: IEEE Transactions on Geoscience and Remote Sensing (ISSN 0196-2892); 30; 3 Ma
    Format: text
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  • 4
    Publication Date: 2019-07-12
    Description: Six Advanced Very High-Resolution Radiometer local area coverage (AVHRR LAC) arctic scenes are classified into ten classes. Three different classifiers are examined: (1) the traditional stepwise discriminant analysis (SDA) method; (2) the feed-forward back-propagation (FFBP) neural network; and (3) the probabilistic neural network (PNN). More than 200 spectral and textural measures are computed. These are reduced to 20 features using sequential forward selection. Theoretical accuracy of the classifiers is determined using the bootstrap approach. Overall accuracy is 85.6 percent, 87.6 percent, and 87.0 percent for the SDA, FFBP, and PNN classifiers, respectively, with standard deviations of approximately 1 percent.
    Keywords: GEOSCIENCES (GENERAL)
    Type: Journal of Applied Meteorology (ISSN 0894-8763); 31; 5 Ma; 405-420
    Format: text
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  • 5
    Publication Date: 2019-07-12
    Description: This paper investigates the automated detection of jet contrails using data from the Advanced Very High Resolution Radiometer. A preliminary algorithm subtracts the 11.8-micron image from the 10.8-micron image, creating a difference image on which contrails are enhanced. Then a three-stage algorithm searches the difference image for the nearly-straight line segments which characterize contrails. First, the algorithm searches for elevated, linear patterns called 'ridges'. Second, it applies a Hough transform to the detected ridges to locate nearly-straight lines. Third, the algorithm determines which of the nearly-straight lines are likely to be contrails. The paper applies this technique to several test scenes.
    Keywords: METEOROLOGY AND CLIMATOLOGY
    Type: International Journal of Remote Sensing (ISSN 0143-1161); 13; 8 Ma
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