A classification of meteorite impact craters
Systematic classification of meteorite impact craters for lunar and planetary craters
Heorz, F.↗
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Some sequential, distribution free pattern classification procedures with applications
Sequential, distribution-free pattern classification procedures tested on Gaussian and EEG patterns
Poage, J. L.↗
Potential functions in pattern classification algorithms
Pattern classification algorithms using potential functions to construct discriminant functions from sample points set
Meisel, W. S.↗
The chemical classification of iron meteorites. V - Groups IIIC and IIID and other irons with germanium concentrations between 1 and 25 ppm
Iron and stony iron meteorites chemical classification, noting Ni, Ga, Ge and Ir concentrations and metal phases
Schaudy, R.↗
A classification of impact craters
Planetary and lunar meteorite craters classification according to radius logarithm to base ten, covering diameter size from 2 microns to 2000 km
Hoerz, F.↗
Lunar rilles: A catalog and method of classification
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.
Oberbeck, V. R.↗
Classification of radiating compact stars
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.
Coppi, B.↗
Classification of spatially unresolved objects
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.
Nalepka, R. F.↗
A study and classification of non-linear high frequency ionospheric instabilities by coupled mode theory.
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.
Harker, K. J.↗
Classification of ERTS-1 MSS data by canonical analysis
Classification of ERTS-1 MSS data by canonical analysis
Lachowski, H. M.↗
Change in Land Use in the Phoenix (1:250000) Quadrangle, Arizona Between 1970 and 1972: Successful Use of a Proposed Land Use Classification System
Change in land use in the Phoenix Quadrangle, Arizona between 1970 and 1972 - successful use of a proposed land use classification system
Place, J. L.↗
Land Use Classification and Change Analysis Using ERTS-1 Imagery in CARETS
Land use classification and change analysis using ERTS-1 imagery in Central Atlantic Research Test Site
Alexander, R. H.↗
Automatic Land Use Classification in Minnesota
Automatic land use classification in Minnesota
Cheung, M.↗
Terrain Classification Maps of Yellowstone National Park
Terrain classification maps of Yellowstone National Park
Thomson, F. J.↗
Identification of phenological stages and vegetative types for land use classification
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.
Branton, C. I.↗
Notes for the improvement of a remote sensing multispectral data non-supervised classification and mapping technique
Examined are: (1) the sequential clustering technique for the unsupervised automatic classification and mapping of earth resources satellite data, (2) theoretical analysis of the tests which were used, and (3) derivation of an alternative set of tests and their necessary algorithm.
Dalton, C. C.↗
Change in land use in the Phoenix (1:250,000) Quadrangle, Arizona between 1970 and 1972: Successful use of proposed land use classification system
Changes in land use in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a land use classification system proposed for use with ERTS images. The period of change investigated was from November 1970 to late summer or early fall, 1972. Seasonal changes also were studied using successive ERTS images. Types of equipment used to aid interpretation included a color additive viewer, a twenty-power magnifier, a density slicer, and a diazo copy machine for making ERTS color composites in hard copy. Types of changes detected have been: (1) cropland or rangeland developed for new residential areas; (2) rangeland converted to new cropland; and (3) possibly new areas of industrial or commercial development. A map of land use previously compiled from air photos was updated in this manner.
Place, J. L.↗
Land use classification and change analysis using ERTS-1 imagery in CARETS
Land use detail in the CARETS area obtainable from ERTS exceeds the expectations of the Interagency Steering Committee and the USGS proposed standardized classification, which presents Level 1 categories for ERTS and Level 2 for high altitude aircraft data. Some Levels 2 and 3, in addition to Level 1, categories were identified on ERTS data. Significant land use changes totaling 39.2 sq km in the Norfolk-Portsmouth SMSA were identified and mapped at Level 2 detail using a combination of procedures employing ERTS and high altitude aircraft data.
Alexander, R. H.↗