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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 73 records · Page 4
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NASA NTRS1997

Adaptive Optics Imaging of Solar System Objects

Most solar system objects have never been observed at wavelengths longer than the R band with an angular resolution better than 1 sec. The Hubble Space Telescope itself has only recently been equipped to observe in the infrared. However, because of its small diameter, the angular resolution is lower than that one can now achieved from the ground with adaptive optics, and time allocated to planetary science is limited. We have been using adaptive optics (AO) on a 4-m class telescope to obtain 0.1 sec resolution images solar system objects at far red and near infrared wavelengths (0.7-2.5 micron) which best discriminate their spectral signatures. Our efforts has been put into areas of research for which high angular resolution is essential, such as the mapping of Titan and of large asteroids, the dynamics and composition of Neptune stratospheric clouds, the infrared photometry of Pluto, Charon, and close satellites previously undetected from the ground.

Roddier, Francois↗
NASA NTRS1999

Adaptive Optics Imaging of Solar System Objects

Most solar system objects have never been observed at wavelengths longer than the R band with an angular resolution better than 1". The Hubble Space Telescope itself has only recently been equipped to observe in the infrared. However, because of its small diameter, the angular resolution is lower than that one can now achieved from the ground with adaptive optics, and time allocated to planetary science is limited. We have successfully used adaptive optics on a 4-m class telescope to obtain 0.1" resolution images of solar system objects in the far red and near infrared (0.7-2.5 microns), at wavelengths which best discriminate their spectral signatures. Our efforts have been put into areas of research for which high angular reso!ution is essential.

Roddier, Francois↗
NASA NTRS2017

Determining the Optimal Spectral Sampling Frequency and Uncertainty Thresholds for Hyperspectral Remote Sensing of Ocean Color

Using a modified geostatistical technique, empirical variograms were constructed from the first derivative of several diverse remote sensing reflectance and phytoplankton absorbance spectra to describe how data points are correlated with distance across the spectra. The maximum rate of information gain is measured as a function of the kurtosis associated with the Gaussian structure of the output, and is determined for discrete segments of spectra obtained from a variety of water types (turbid river filaments, coastal waters, shelf waters, a dense Microcystis bloom, and oligotrophic waters), as well as individual and mixed phytoplankton functional types (PFTs; diatoms, chlorophytes, cyanobacteria, coccolithophores). Results show that a continuous spectrum of 5 to 7 nm spectral resolution is optimal to resolve the variability across mixed reflectance and absorbance spectra. In addition, the impact of uncertainty on subsequent derivative analysis is assessed, showing that a limit of 3 Gaussian noise (SNR 66) is tolerated without smoothing the spectrum, and 13 (SNR 15) noise is tolerated with smoothing.

Noise in imaging systems↗
NASA NTRS1992

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

Kimes, D. S.↗
NASA NTRS1984

Evaluation of criteria for selecting the spectral attributes of digital LANDSAT MSS imagery for discriminating lithological units in the lower Curaca River Valley, Bahia

The use of spectral attributes criteria was investigated, based on measures of statistical distance of separability between thematic classes in MSS digital LANDSAT imagery, in order to select the best subsets of channels in composite colors for the detection and discrimination of lithological units in the lower valley of Curaca River, State of Bahia, Brazil. Three situations were investigated: (1) selection of the three best channels, considering all of the original bands (channels 4, 5, 6, and 7); (2) selection of the three best bands, considering the six MSS band-ratios (channels 4/5, 4/6. 4/7, 5/6, 5/7, and 6/7); and (3) selection of the three best bands in a hybrid approach (the four original bands and the six ratios). A visual analysis was done on color composite images using the selected sets. Results show that the hybrid product (bands 4, 5/7, and 7 with green, blue, and red respectively) and the Normal Color Composite (bands 4, 5, and 7 with blue, green, and red colors respectively) had the best performance.

Paradella, W. R.↗
NASA NTRS1982

The use of thermal infrared images in geologic mapping

Thermal infrared image data can be used as an aid to geologic mapping. Broadband thermal data between 8 and 13 microns is used to measure surface temperature, from which surface thermal properties can be inferred. Data from aircraft multispectral scanners at Pisgah, California which include a broadband thermal channel along with several visible and near-IR spectral channels permit better discrimination between rock type units than the same data set without the thermal data. Data from the HCMM satellite and from aircraft thermal scanners also make it possible to monitor moisture changes in Death Valley, California. Multispectral data in the same 8-13 micron wavelength range can be used to discriminate between surface materials with different spectral emission characteristics, as demonstrated with both aircraft scanner and ground spectrometer data.

Kahle, A. B.↗
NASA NTRS1988

Development of remote sensing techniques capable of delineating soils as an aid to soil survey

Eighty-one benchmark soils from Alabama, Georgia, Florida, Tennessee, and Mississippi were evaluated to determine the feasibility of spectrally differentiating among soil categories. Relationships among spectral properties that occur between soils and within soils were examined, using discriminant analysis. Soil spectral data were obtained from air-dried samples using an Exotech Model 20C field spectroradiometer (0.37 to 2.36 microns). Differentiating among the orders, suborders, great groups, and subgroups using reflectance spectra achieved varying percentages of accuracy. Six distinct reflectance curve forms were developed from the air-dried samples based on the shape and presence or absence of adsorption bands. Iron oxide and organic matter content were the dominant soil parameters affecting the spectral characteristics for differentiating among and between these soils.

Coleman, T. L.↗
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.↗
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.↗
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.↗