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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Identification of phenological stages and vegetative types for land use classification

The author has identified the following significant results. A large grassland was located on the Kenai Peninsula which may be a potential grazing land. Two 1:250,000 vegetation maps were constructed from ERTS-1 scenes 1049-20505 and 1066-20453 using 70 mm MSS chips and black and white prints for an area of 3.5 million acres. Another area (464,000 acres) was mapped using digital data. The latter map is the most accurate and detailed vegetation map of that area produced to date. Areal extents of identified vegetation types were derived for the area mapped from digital data. Early spring (prior to leafing out of the deciduous trees) is suspected as being the best time for mapping Alaskan vegetation from MSS data due to the radiometrically distinctness of the vegetation communities at that time.

Branton, C. I.↗
NASA NTRS1973

Unsupervised classification and areal measurement of land and water coastal features on the Texas coast

Multispectral scanner (MSS) digital data from ERTS-1 was used to delineate coastal land, vegetative, and water features in two portions of the Texas Coastal Zone. Data (Scene ID's 1037-16244 and 1037-16251) acquired on August 29, 1972, were analyzed on NASA Johnson Space Center systems through the use of two clustering algorithms. Seventeen to 30 spectrally homogeneous classes were so defined. Many classes were identified as being pure features such as water masses, salt marsh, beaches, pine, hardwoods, and exposed soil or construction materials. Most classes were identified to be mixtures of the pure class types. Using an objective technique for measuring the percentage of wetland along salt marsh boundaries, an analysis was made of the accuracy of areal measurement of salt marshes. Accuracies ranged from 89 to 99 percent. Aircraft photography was used as the basis for determining the true areal size of salt marshes in the study sites.

Flores, L. M.↗
NASA NTRS1973

Identification of phenological stages and vegetative types for land use classification

The author has identified the following significant results. A large grassland was located on the Kenai Peninsula which may be a potential grazing land. Two 1:250 K vegetation maps were constructed from ERTS-1 scenes 1049-20505 and 1066-20453 using 70 mm MSS chips and black and white prints for an area of 3.5 million acres. Another area (464,000 acres) was mapped using digital data. The latter map is the most accurate and detailed vegetation map of that area produced to date. Areal extents of identified vegetation types were derived for the area mapped from digital data. Early spring (prior to leafing out of deciduous trees) is suspected as being the best time for mapping Alaskan vegetation from MSS data due to the best time for mapping Alaskan vegetation from MSS data due to the radiometrically distinctness of the vegetation communities at that time. Vegetative overlays produced at 1:250 K compare favorably with vegetative maps compiled by Lloyd A. Spetzman and assembled by the joint Federal-State Land Use Planning Commission for Alaska.

Branton, C. I.↗
NASA NTRS1972

Nearest Neighbor Algorithms for Pattern Classification

A solution of the discrimination problem is considered by means of the minimum distance classifier, commonly referred to as the nearest neighbor (NN) rule. The NN rule is nonparametric, or distribution free, in the sense that it does not depend on any assumptions about the underlying statistics for its application. The k-NN rule is a procedure that assigns an observation vector z to a category F if most of the k nearby observations x sub i are elements of F. The condensed nearest neighbor (CNN) rule may be used to reduce the size of the training set required categorize The Bayes risk serves merely as a reference-the limit of excellence beyond which it is not possible to go. The NN rule is bounded below by the Bayes risk and above by twice the Bayes risk.

Barrios, J. O.↗
NASA NTRS1973

Identification of phenological stages and vegetative types for land use classification

The author had identified the following significant results. Digital signatures derived from the CDU are comparable to those taken from the printouts. Therefore, using the CDU to derive signatures should be more efficient, since there is considerable time required in turn around with the computer and time required locating vegetation stands on the printout.

Mckendrick, J. D.↗
NASA NTRS1972

Apollo 14 breccias - General characteristics and classification.

The Apollo 14 breccias are complex and are characterized by a wide range of clast types and textures. The principal fragment types in the breccias are (1) hornfelsed noritic microbreccias; (2) micronorite hornfels; (3) devitrified glass; and (4) ophitic and other kinds of basalt. Based on fragment population, nature of the matrix, grain size and porosity, metamorphic history, and bulk chemical composition, the Apollo 14 breccias can be classified chiefly into regolith microbreccias, Fra Mauro breccias, and spherule-rich microbreccias. Further subdivisions are based principally on the interpretation of metamorphic history. Twenty-six Apollo 14 breccias have been so classified. The complex fragment types contained in Apollo 14 breccias represent multiple episodes of heating and fragmentation. They probably are pre-Imbrian and were not produced by the impact effects of a single event. The variability of their fragment populations is important in the interpretation of pre-Imbrian geologic history.

Chao, E. C. T.↗
NASA NTRS1973

Apollo 16 rocks - Petrology and classification.

The Apollo 16 rocks are classified in three broad intergradational groups: (1) crystalline rocks, subdivided into igneous rocks and metaclastic rocks, (2) glass, and (3) breccias, which are subdivided into five groups on the basis of clast and matrix colors. Most of the rocks were derived by impact brecciation of an anorthosite-norite suite but may represent ejecta from more than one major basin. First-cycle breccias are believed to have consisted of clasts of crushed anorthosite-norite in a fine-grained partly fused matrix with a chemical composition similar to that of the clasts. Most of the other recognized breccia types could have been produced by rebrecciation of first-cycle breccias.

Wilshire, H. G.↗
NASA NTRS1973

Classification and distribution of WR stars and an interpretation of the WN sequence.

New observational data for Wolf-Rayet stars are interpreted in areas of atmospheric abundances, absolute magnitudes, Galactic distribution, distribution in M33, and bolometric luminosities. The observational data are used in support of arguments (1) that WN stars are helium stars of eight to fourteen solar masses with atmospheres which contain only a very low proportion of hydrogen, (2) that the properties of the stars are very sensitive to this very small amount of hydrogen, and (3) that consequently this structure explains many of the general properties of the subclasses.

Smith, L. F.↗
NASA NTRS1974

Remote sensing in Iowa agriculture: Identification and classification of Iowa's crops, soils and forestry resources using ERTS-1 and complimentary underflight imagery

The author has identified the following significant results. Springtime ERTS-1 imagery covering pre-selected test sites in Iowa showed considerable detail with respect to broad soil and land use patterns. Additional imagery has been incorporated into a state mosaic. The mosaic was used as a base for soil association lines transferred from an existing map. The regions of greatest contrast are between the Clarion-Nicollet-Webster soil association area and adjacent areas. Landscape characteristics in this area result in land use patterns with a high percentage of pasture, hay, and timber. The soil association areas of the state that have patterns interpreted to be associated with intensive row crop production are: Moody, Galva-Primghar-Sac, Clarion-Nicollet-Webter, Tama-Muscatine, Dinsdale-Tama, Cresco-Lourdes, Clyde, Kenyon-Floyd-Clyde, and the Luton-Onawa-Salix area on the Missouri River floodplain. Forestland estimates have been attained for an area in central Iowa using wintertime ERTS-1 imagery. Visual analysis of multispectral, temporal imagery indicates that temporal analysis for cropland identification and acreage analyses procedures may be a very useful tool. Combinations of wintertime, springtime, and summertime ERTS-1 imagery separate most vegetation types. Timing can be critical depending upon crop development and harvesting times because of the dynamic nature of agricultural production.

Mahlstede, J. P.↗