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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

ROSAT PSPC observations of two X-ray-faint early-type galaxies: NGC 4365 and NGC 4382

We present the results of ROSAT Positive Sensitive Proportional Counter (PSPC) observations of the two early-type galaxies NGC 4365 and NGC 4382. These galaxies are among those observed with Einstein to have the lowest X-ray to optical flux ratios of early-type galaxies. The PSCP data show that for radii r greater than 50 arcsec the radial distributions of the X-ray surface brightness are consistent with the optical distributions of King (1978). We also find that these galaxies have X-ray spectra significantly different from those observed in X-ray-bright ellipticals, with a relative excess of counts detected in the softest spectral channels. This confirms earlier Einstein results. The characteristics of the ROSAT PSPC do not allow us to discriminate between possible spectral models. If we adopt a two-component thermal model on the grounds of physical plausibility, we find that the spectral data can be fitted with a very soft optically thin component, with kT approximately 0.2 keV, and a hard component with kT greater than (1.0-1.5) keV. The hard component has a luminosity consistent with that expected from the integrated emission of a population of low mass-X-ray binaries in these galaxies; the nature of the very soft component is more speculative. Candidates include the coronal emission of late-type stars, supersoft X-ray sources, RS CVn, and perhaps a hot Interstellar Medium (ISM). Alternatively, the spectal data may be fitted with a 0.6-1 keV bremsstrahlung spectrum (expontential plus Gaunt), and may suggest the presence of a totally new population of X-ray sources.

Fabbiano, G.↗
NASA NTRS2001

Spectral Classification of Similar Materials using the Tetracorder Algorithm: The Calcite-Epidote-Chlorite Problem

Recent work on automated spectral classification algorithms has sought to distinguish ever-more similar materials. From modest beginnings separating shade, soil, rock and vegetation to ambitious attempts to discriminate mineral types and specific plant species, the trend seems to be toward using increasingly subtle spectral differences to perform the classification. Rule-based expert systems exploiting the underlying physics of spectroscopy such as the US Geological Society Tetracorder system are now taking advantage of the high spectral resolution and dimensionality of current imaging spectrometer designs to discriminate spectrally similar materials. The current paper details recent efforts to discriminate three minerals having absorptions centered at the same wavelength, with encouraging results.

Dalton, J. Brad↗
NASA NTRS1983

Contribution of LANDSAT-4 thematic mapper data to geologic exploration

The increased number of carefully selected narrow spectral bands and the increased spatial resolution of thematic mapper data over previously available satellite data contribute greatly to geologic exploration, both by providing spectral information that permits lithologic differentiation and recognition of alteration and spatial information that reveals structure. As vegetation and soil cover increase, the value of spectral components of TM data decreases relative to the value of the spatial component of the data. However, even in vegetated areas, the greater spectral breadth and discrimination of TM data permits improved recognition and mapping of spatial elements of the terrain. As our understanding of the spectral manifestations of the responses of soils and vegetation to unusual chemical environments increases, the value of spectral components of TM data to exploration will greatly improve in covered areas.

Everett, J. R.↗
NASA NTRS1975

Plan for the uniform mapping of earth resources and environmental complexes from Skylab imagery. Assessment of natural vegetation, environmental, and crop analogs

The author has identified the following significant results. For interpreting a wide range of natural vegetation analogs, S-190A color infrared and the ERTS-1 color composite were consistently more useful than were conventional color or black and white photos. Color infrared was superior for five vegetation analogs while color was superior for only three. The errors in identification appeared to associate more with black and white single band images than with multiband color. For rice crop analogs, spectral and spatial discriminations both contribute to the usefulness of images for data collection. Tests and subjective analyses conducted in this study indicated that the spectral bands exploited in color infrared film were the most useful for agricultural crop analysis. Accuracy of crop identification on any single date of Skylab images was less than that of multidate analysis due to differences in crop calendar, cultural practices used, rice variety, planting date, planting method, water use, fertilization, disease, or mechanical problems.

Poulton, C. E.↗
NASA NTRS1986

Lithologic discrimination of volcanic and sedimentary rocks by spectral examination of Landsat TM data from the Puma, Central Andes Mountains

The Central Andes are widely used as a modern example of noncollisional mountain-building processes. The Puna is a high plateau in the Chilean and Argentine Central Andes extending southward from the altiplano of Bolivia and Peru. Young tectonic and volcanic features are well exposed on the surface of the arid Puna, making them prime targets for the application of high-resolution space imagery such as Shuttle Imaging Radar B and Landsat Thematic Mapper (TM). Two TM scene quadrants from this area are analyzed using interactive color image processing, examination, and automated classification algorithms. The large volumes of these high-resolution datasets require significantly different techniques than have been used previously for the interpretation of Landsat MSS data. Preliminary results include the determination of the radiance spectra of several volcanic and sedimentary rock units and the use of the spectra for automated classification. Structural interpretations have revealed several previously unknown folds in late Tertiary strata, and key zones have been targeted to be investigated in the field. The synoptic view of space imagery is already filling a critical gap between low-resolution geophysical data and traditional geologic field mapping in the reconnaissance study of poorly mapped mountain frontiers such as the Puna.

Fielding, E. J.↗
NASA NTRS1976

Comparison of Skylab and LANDSAT images for geologic mapping in Northern Arizona

The author has identified the following significant results. It was found that based on resolution, the Skylab S190A products were superior to LANDSAT images. Based on measurements of shoreline features in Lake Mead S190A images had 1.5 - 3 times greater resolution than LANDSAT. In general, the higher resolution of the Skylab data yielded better discrimination among rock units, but in the case of structural features, lower sun angle LANDSAT images (50 deg) were superior to higher sun angle Skylab images (77 deg). The most valuable advantage of the Skylab over the LANDSAT image products is the capability of producing stereo images. Field spectral reflectance measurements on the Coconino Plateau were made in an effort to determine the best spectral band for discrimination of the six geologic units in question, and these bands were 1.3, 1.2, 1.0, and 0.5 microns. The EREP multispectral scanner yielded data with a low signal to noise ratio which limited its usefulness for image enhancement work. Sites that were studied in Arizona were Shivwits Plateau, Verde Valley, Coconino Plateau, and Red Lake. Thematic maps produced by the three classification algorithms analyzed were not as accurate as the maps produced by photointerpretation of composites of enhanced images.

Goetz, A. F. H.↗
NASA NTRS1995

Using foreground/background analysis to determine leaf and canopy chemistry

Spectral Mixture Analysis (SMA) has become a well established procedure for analyzing imaging spectrometry data, however, the technique is relatively insensitive to minor sources of spectral variation (e.g., discriminating stressed from unstressed vegetation and variations in canopy chemistry). Other statistical approaches have been tried e.g., stepwise multiple linear regression analysis to predict canopy chemistry. Grossman et al. reported that SMLR is sensitive to measurement error and that the prediction of minor chemical components are not independent of patterns observed in more dominant spectral components like water. Further, they observed that the relationships were strongly dependent on the mode of expressing reflectance (R, -log R) and whether chemistry was expressed on a weight (g/g) or are basis (g/sq m). Thus, alternative multivariate techniques need to be examined. Smith et al. reported a revised SMA that they termed Foreground/Background Analysis (FBA) that permits directing the analysis along any axis of variance by identifying vectors through the n-dimensional spectral volume orthonormal to each other. Here, we report an application of the FBA technique for the detection of canopy chemistry using a modified form of the analysis.

Pinzon, J. E.↗
NASA NTRS1987

A spectral-knowledge-based approach for urban land-cover discrimination

A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was developed that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.

Wharton, Stephen W.↗
DOE OSTI2022

QUBIC II: Spectral polarimetry with bolometric interferometry

Bolometric interferometry is a novel technique that has the ability to perform spectral imaging. A bolometric interferometer observes the sky in a wide frequency band and can reconstruct sky maps in several sub-bands within the physical band in post-processing of the data. This provides a powerful spectral method to discriminate between the cosmic microwave background (CMB) and astrophysical foregrounds. In this paper, the methodology is illustrated with examples based on the Q & U Bolometric Interferometer for Cosmology (QUBIC) which is a ground-based instrument designed to measure the B-mode polarization of the sky at millimeter wavelengths. We consider the specific cases of point source reconstruction and Galactic dust mapping and we characterize the point spread function as a function of frequency. We study the noise properties of spectral imaging, especially the correlations between sub-bands, using end-to-end simulations together with a fast noise simulator. Finally, we conclude showing that spectral imaging performance are nearly optimal up to five sub-bands in the case of QUBIC.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Spectral response curve models applied to forest cover-type discrimination

The potential of remote sensing systems to provide a cost-effective inventory tool in the case of forest resources is currently of interest to a variety of natural resources management agencies. A number of studies have been performed regarding the use of Landsat data for mapping forest resources in Michigan. The present paper is concerned with current research, which has been directed toward the development and evaluation of computer-implemented classifications for the identification and characterization of coniferous forest types in Michigan's northern Lower Peninsula. Attention is given to the characteristic response curves from Landsat MSS data, spectral response curve models, and forest cover-type discrimination. It is found that spectral response curve models can be used to evaluate and explain the characteristic spectral responses of coniferous forest types on a snow-covered, winter Landsat scene.

Hudson, W. D.↗
DOE OSTI2024

Spatially Dependent Seismic Wavefield Scattering from an Underground Chemical Explosion: Analysis of the Source Physics Experiment Dry Alluvium Geology Large- N Array

Explosion sources have been observed to generate significant shear‐wave energy despite their isotropic nature. To investigate this phenomenon, we conduct an analysis of the seismic data collected as part of the Source Physics Experiment (SPE): Dry Alluvium Geology (DAG) and investigate the generation of shear‐wave energy via scattering. The data were produced by three underground chemical explosions and consist of three‐component seismograms, which were recorded by the DAG Large‐N array. Synthetic tests suggest that for the DAG experiments, small‐scale stochastic heterogeneities, defined as features with correlation lengths of 10–100s of meters, are more effective than large‐scale geologic structure (scales >1–10 km) at reproducing the scattering of explosion generated wavefields observed at DAG. We analyze the seismic data for spatially variable ratios between transversely and radially polarized seismic energy, and then estimate the mean free path of P and S waves. All analyses are conducted within a frequency band of 5–50 Hz. The ratio of transversely to radially polarized energy is the highest in the east and west portion of the Large‐N array. In addition, the magnitude of the estimated S‐wave mean free path is shorter in the eastern portion of the Large‐N array. This variation indicates that the eastern area of the DAG array is where more scattering is occurring, suggesting azimuthal dependence of P‐to‐P and P‐to‐S scattering. Furthermore, this azimuthal dependence of P‐to‐S scattering can have implications for explosion discrimination based on spectral ratios of seismic wave types, because the general assumption is that explosions do not generate shear‐wave energy. Synthetic tests modeling only larger‐scale geologic structure had lower transversely polarized energy (only four stations showing a transversely to radially polarized energy ratio greater than 1) and fewer stations (<10) displaying shorter (<300 m) mean free paths than what was observed in the DAG data results.

Darrh, Andréa Nicole↗
NASA NTRS1980

Remote sensing of surface mines - A comparative study of sensor systems

The application of remote sensing to the inventory of coal surface mines and to the monitoring of mine reclamation in the eastern United States was investigated. Data were acquired during spring and autumn by several sensor systems over study areas located within the bituminous coal fields of Pennsylvania. Data sources were the Landsat MSS, an airborne multispectral scanner (Daedalus DS-1260), the airborne Thematic Mapper Simulator, and high-altitude color and color infrared aerial photography. A comparison of the data sets was conducted by a quantitative assessment of area measurement accuracy. Landsat data were found most suitable for a synoptic inventory of mines on a regional basis. High-altitude aerial photography was considered the best source of the detailed information required for reclamation monitoring. Nine channels of data from the airborne scanner were evaluated to select the most useful spectral bands for discriminating among the land cover types associated with surface mines. Four bands were selected in the following order by a stepwise linear discriminant procedure: 0.60-0.65 micron, 0.92-1.10 microns, 0.80-0.89 micron, and 8-14 microns. The data corresponding to these four bands were used for the thematic mapping of land cover.

Irons, J. R.↗
NASA NTRS1990

Radiobrightness of diurnally heated, freezing soil

Freezing and thawing soils exhibit unique radiometric characteristics. To examine these characteristics, diurnal insolation is modeled as one-dimensional heating of a moist soil half-space during a typical fall at a northern Great Plains site. The one-dimensional heat flow equation is nonlinear because both the enthalpy (the change in internal energy with temperature at constant pressure) and the thermal conductivity of freezing soils are nonlinear functions of temperature. The problem is particularly difficult because phase boundaries propagate in time, and because soils, particularly clay-rich soils, freeze over a range of temperatures rather than at 0 C. Diurnal radiobrightness curves at 10.7, 18.0, and 37.0-GHz were computed for each month. The 37.0-GHz radiobrightness best tracks soil surface temperature; the 10.7-37.0-GHz spectral gradient of thawed soils is strongly positive; the spectral gradient of frozen soils is slightly negative; and the midnight-to-noon spectral gradient is shifted by approximately +0.1 K/GHz by diurnal changes in the surface temperature and the thermal gradient. These observations support the use of the scanning multichannel microwave radiometer 37.0-GHz radiobrightness and its 10.7-37.0-GHz spectral gradient as discriminants in a frozen soil classifier for high-latitude prairie.

England, Anthony W.↗
NASA NTRS1985

Remote sensing of wetland biomass and productivity for global biosystem research

The study of ecosystem function and the contributions of particular ecosystems to global elemental cycling will require data collection from orbital platforms. Presently used ground sampling techniques are not adequate for large area vegetation assessments. The research was directed toward an understanding of the relationship between spectral radiance and plant canopy biomass. Changes in the architecture of the canopy alters the observed spectral radiance patterns. The green components of a plant canopy interacts most strongly with incident radiation and usually reflect edaphic conditions as they relate to plant vigor. Plant biomass serves as an excellent integrator of the environmental factors encountered by the plant and can be used as an indicator for predicting soil redox, nutrient status, microbial activity, etc. The use was examined of TM spectral data to discriminate biomass classes and, in turn, to relate the biomass classes to the chemical status of the soil. Several preliminary studies have indicated that solar angle can be used to improve biomass predictions. This important observation also suggests that latitudinal extrapolation of the biomass predicting models will be possible if selected characteristics of the incident radiation are known.

Hardisky, M. A.↗
NASA NTRS1980

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 1

A generalized four channel hyperplane to discriminate water from nonwater was developed using LANDSAT-3 multispectral scaner (MSS) scenes and matching same/next day color infrared aerial photography. The MSS scenes varied in sun elevation angle from 40 to 58 deg. The 28 matching air photo frames contained over 1400 water bodies larger than one surface acre. A preliminary water discriminant, was used to screen the data and eliminate from further consideration all pixels distant from water in MSS spectral space. A linear discriminant was iteratively fitted to the labelled pixels. This discriminant correctly classified 98.7% of the water pixels and 98.6% of the nonwater pixels. The discriminant detected 91.3% of the 414 water bodies over 10 acres in surface area, and misclassified as water 36 groups of contiguous nonwater pixels.

Schlosser, E. H.↗
NASA NTRS1991

Inferring vegetation characteristics using a knowledge-based system

A knowledge-based system for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input is developed. A portion of this system has been developed to discriminate between user-defined vegetation classes using spectral and directional reflectance relationships. This discrimination program was used to classify targets into user-defined ground cover and plant height classes. The program learns class descriptors from samples (both positive and negative) of spectral, directional reflectance data of natural surfaces (bare soils, natural vegetation, and agricultural vegetation). The system is designed to handle any combination of directional view angles. The explicit relationships used in the class descriptions include greater-than relationships between combinations of two view angles and maximum and minimum value relationships. The class descriptions are used to classify an unknown target using the same directional views. The program was tested by learning class descriptions of various categories of percent ground cover and vegetation height.

Kimes, D. S.↗
NASA NTRS1972

Multispectral discrimination of possible Martian surface constituents.

In the 1970s attempts will be made to soft-land scientific instruments on the surface of Mars. The question of the employment of several spectral bands to improve discrimination is investigated. The studies conducted are concerned with the development of a technique for selecting color bands for a lander imaging system. Other study objects include the investigation of certain solid state detectors and the determination of the feasibility of minimizing the total number of telemetry bits from the lander by various means.

Klemas, V.↗
NASA NTRS1991

Discrimination of active and inactive sand from remote sensing - Kelso dunes, Mojave Desert, California

Landsat TM images, field data, and laboratoray reflectance spectra were examined for the Kelso dunes, Mojave Desert, California to assess the use of visible and near-infrared (VNIR) remote sensing data to discriminate aeolian sand populations on the basis of spectral brightness. Results show that areas of inactive sand have a larger percentage of dark, fine-grained materials compared to those composed of active sand, which contain less dark fines and a higher percentage of quartz sand-size grains. Both areas are spectrally distinct in the VNIR, suggesting that VNIR spectral data can be used to discriminate active and inactive sand populations in the Mojave Desert. Analysis of laboratory spectra was complicated by the presence of magnetite in the active sands, which decreases their laboratory reflectance values to those of inactive sands. For this application, comparison of TM and laboratory spectra suggests that less than 35 percent vegetation cover does not influence the TM spectra.

Paisley, Elizabeth C. I.↗