Solar coronal streamers. I - Observed locations, general evolution, and classification
Solar coronal streamers, considering disk locations, evolution, classification and morphological model
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Solar coronal streamers, considering disk locations, evolution, classification and morphological model
Classification and signal analysis of pulse width modulated amplifiers
Classification and survey of computer system performance evaluation techniques
Systematic classification of meteorite impact craters for lunar and planetary craters
Sequential, distribution-free pattern classification procedures tested on Gaussian and EEG patterns
Pattern classification algorithms using potential functions to construct discriminant functions from sample points set
Iron and stony iron meteorites chemical classification, noting Ni, Ga, Ge and Ir concentrations and metal phases
Planetary and lunar meteorite craters classification according to radius logarithm to base ten, covering diameter size from 2 microns to 2000 km
A representative sample of lunar rilles observed on Lunar Orbiter 4 and 5 photographs is presented. A method of classification of rilles is described which will provide a means of quantitatively grouping rilles of similar planemetric shape. The method is based on a finite Fourier approximation of the edge of the rille. It provides an adequate approximation to all planemetric characteristics of the rille except rille recurvature.
A classification of compact stars, depending on the electron distribution in velocity space and the density profiles characterizing their magnetospheric plasma, is proposed. Fast pulsars, such as NP 0532, X-ray sources such as Sco-X1, and slow pulsars are suggested as possible evolutionary stages of similar objects. The heating mechanism of Sco-X1 is discussed in some detail.
A proportion estimation technique for classification of multispectral scanner images is reported that uses data point averaging to extract and compute estimated proportions for a single average data point to classify spatial unresolved areas. Example extraction calculations of spectral signatures for bare soil, weeds, alfalfa, and barley prove quite accurate.
Two basic high-frequency ionospheric instabilities are discussed - i.e., the three-wave parametric interaction, and the oscillating two-stream instability. In the parametric instability, the ion-acoustic wave has a complex frequency, whereas in the oscillating two-stream instability the ion-acoustic frequency is purely imaginary. The parametric instability is shown to be the only one whose threshold depends on the ion collision frequency. A coupled-mode theory is proposed which permits study and classification of high-frequency instabilities on a unified basis.
Classification of ERTS-1 MSS data by canonical analysis
Change in land use in the Phoenix Quadrangle, Arizona between 1970 and 1972 - successful use of a proposed land use classification system
Land use classification and change analysis using ERTS-1 imagery in Central Atlantic Research Test Site
Automatic land use classification in Minnesota
Terrain classification maps of Yellowstone National Park
The author has identified the following significant results. Multispectral reflectance signatures have been obtained from computer printouts from scene 1049-20505. Those signatures have been grouped for 13 dominant physical features in the Matanuska Susitna Valley area of Alaska. The derived signatures will be validated and tested by requesting another symbol-coded computer printout for the same area. It is expected that ERTS-1 imagery collected during late autumn and early spring will provide separations of signatures that are confounded in the 1049-20505 scene. Separating bogs and forests should be much improved when either snow covered or when grasses are brown. Photographs have been made of projections on the color additive viewer, each scene being projected with six different filter combinations. The products will be analyzed and those best suited used for producing color transparencies at a scale of 1:250,000 for overlaying on standard quadrangle maps. Color prints will be processed for use in the field. From digital MSS signatures derived to date, identification has been made of which bands are the most powerful for automated classification of dominant physical features. It has been found that separations among density ranges increase with longer wavelengths. Deriving MSS digital signatures has proven valuable to both digital and visual processing of ERTS-1 data.