114,621 research outputs found

    Computer analysis and mapping of gypsy moth levels in Pennsylvania using LANDSAT-1 digital data

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    The effectiveness of using LANDSAT-1 multispectral digital data and imagery, supplemented by ground truth and aerial photography, was investigated as a new method of surveying gypsy moth (Porthetria dispar (L.)) (Lepidoptera; Lymantriidae) defoliation, which has greatly increased in Pennsylvania in recent years. Since the acreage and severity of gypsy moth defoliation reaches a peak from mid-June through the first few days of July, the July 8, 1973, LANDSAT-1 scene was chosen for analysis. Results indicate that LANDSAT-1 data can be used to discriminate between defoliated and healthy vegetation in Pennsylvania and that digital processing methods can be used to map the extent and degree of defoliation

    Monitoring forest canopy alteration around the world with digital analysis of LANDSAT imagery

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    There are no author-identified significant results in this report

    A canopy-related stratification of a southern pine forest using LANDSAT digital data

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    An investigation was undertaken to determine if a consistent stratification of a Southern pine forest could be obtained by using LANDSAT multispectral scanner data to assess crown closure. Winter and summer LANDSAT scenes of the North Carolina coastal region were analyzed individually and then registered and merged to take advantage of temporal changes in the forest canopy. Three levels of pine crown closure were accurately delineated. The applicability of this stratification as supplemental input to a forest inventory system is also discussed

    High energy density electrochemical cell

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    Primary cell has an anode of lithium, a cathode containing dihaloisocyanuric acid, and a nonaqueous electrolyte comprised of a solution of lithium perchlorate in methyl formate. It produces an energy density of 213 watt hrs/lb and can achieve a high current density

    Limits on the Halo White Dwarf Component of Baryonic Dark Matter from the {\em Hubble Deep Field}

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    The MACHO collaboration lensing event statistics suggest that a significant fraction of the dark galactic halo can be comprised of baryonic matter in the form of white dwarf stars with masses between 0.1 and 1.0 \Msun . Such a halo white dwarf population, in order to have escaped detection by those who observe the white dwarf luminosity function of the disk, must have formed from an old population. The observations indicate that the number of halo white dwarfs per cubic parsec per unit bolometric magnitude is less than 10−510^{-5} at 10−4.510^{-4.5}\Lsun; the number must rise significantly at lower luminosities to provide the needed baryonic halo mass. Such white dwarfs may easily escape detection in most current and earlier surveys. Though it is limited in angular extent, the {\em Hubble Deep Field} (HDF) probes a sufficient volume of the galactic halo to provide interesting limits on the number of halo white dwarf stars, and on the fraction of the halo mass that they can make up. If the HDF field can be probed for stars down to V=29.8V=29.8 then the MACHO result suggests that there could be up to 12 faint halo white dwarfs visible in the HDF. Finding (or not finding) these stars in turn places interesting constraints on star formation immediately following the formation of the galaxy.Comment: 10 pages, AASTEX, 1 table, no figures, accepted for publication in Ap.J. Letter

    A Bayesian method for detecting stellar flares

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    We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model. This is required to fit underlying light curve variations that are expected in the data, which could otherwise partially mimic a flare. We characterise the false alarm probability and efficiency of this method and compare it with a simpler thresholding method based on that used in Walkowicz et al (2011). We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95% of flares with S/N less than ~20, as compared to S/N of ~25 for the simpler method. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have characterised their durations and and signal-to-noise ratios.Comment: Accepted for MNRAS. The code used for the analysis can be found at https://github.com/BayesFlare/bayesflare/releases/tag/v1.0.

    Development of the dry tape battery concept Quarterly report no. 4, 9 Mar. - 9 Jun. 1966

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    Aqueous and nonqueous electrolytic actions, and energy density measurements for dry tape batter

    Utilization of LANDSAT imagery for mapping vegetation on the millionth scale

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    A series of test sites were examined to determine if the information content of the LANDSAT imagery that may be obtained of these sites is sufficient to permit their mapping according to the vegetation classification system recently published by Unesco. These sites include examples from the humid tropics, arid and semi-arid subtropics and temperature zones: Western Highlands of Papua New Guinea, Mindoro Island in the Philippines, Great Smoky Mountains of the southeastern United States, East Tennessee Valley, interior of Western Australia, northeastern Uganda, and south-central Kansas. The results of the experiment were presented in the form of vegetation maps and annotated images which serve to illustrate the detectability of various formations. It was concluded that, for the test sites examined, the formations of the Unesco vegetation classification can be satisfactorily distinguished on LANDSAT MSS images, especially when used as color composites and judiciously chosen as to season
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