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Results for “spectral selectivity”

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 19 records

Miniature spectrally selective dosimeter

A miniature spectrally selective dosimeter capable of measuring selected bandwidths of radiation exposure on small mobile areas is described. This is achieved by the combination of photovoltaic detectors, electrochemical integrators (E-cells) and filters in a small compact case which can be easily attached in close proximity to and substantially parallel to the surface being measured. In one embodiment two photovoltaic detectors, two E-cells, and three filters are packaged in a small case with attaching means consisting of a safety pin. In another embodiment, two detectors, one E-cell, three filters are packaged in a small case with attaching means consisting of a clip to clip over a side piece of an eye glass frame.

Adams, R. R.↗

PERFORMANCE OF SPECTRALLY SELECTIVE COLLECTOR SURFACES IN A SOLAR-DRIVEN CARNOT SPACE-POWER SYSTEM

A study was made of the theoretical performance of spectrally selective surfaces when used as the collectors of solar energy for driving heat engine cycles in space. Selective surfaces were considered for which the-monochromatic emissivity changed abruptly at specific wavelengths between 0.5 and 10 microns. The Carnot cycle was used as the heat engine, and waste heat was rejected from a black radiator. Systems using both focused and unfocused radiation were considered. It was found that spectrally selective surfaces hold considerable promise as collectors of solar energy in unfocused systems. The efficiency for these is several times greater than that obtainable from black or gray collectors. However, this advantage of spectral selectivity diminishes if the sunlight is focused on the collector. In highly focused systems, such as those using parabolic mirrors, black collectors give substantially the same efficiency as the most ideal spectrally selective surface.

SOLAR PROPULSION↗

Guided-wave approaches to spectrally selective energy absorption

Results of experiments designed to demonstrate spectrally selective absorption in dielectric waveguides on semiconductor substrates are reported. These experiments were conducted with three waveguides formed by sputtering films of PSK2 glass onto silicon-oxide layers grown on silicon substrates. The three waveguide samples were studied at 633 and 532 nm. The samples differed only in the thickness of the silicon-oxide layer, specifically 256 nm, 506 nm, and 740 nm. Agreement between theoretical predictions and measurements of propagation constants (mode angles) of the six or seven modes supported by these samples was excellent. However, the loss measurements were inconclusive because of high scattering losses in the structures fabricated (in excess of 10 dB/cm). Theoretical calculations indicated that the power distribution among all the modes supported by these structures will reach its steady state value after a propagation length of only 1 mm. Accordingly, the measured loss rates were found to be almost independent of which mode was initially excited. The excellent agreement between theory and experiment leads to the conclusion that low loss waveguides confirm the predicted loss rates.

Stegeman, G. I.↗

Gamma ray burst size-frequency distributions: Spectral selection effects

The effects of spectral variation on the detection of gamma ray bursts were investigated. Selection biases resulting from these effects can account for the reported deviation of the observed size-frequency distribution in peak energy flux from that expected for a simple uniform distribution of sources. Thus these observations as yet provide no clear evidence for structure in the burst source distribution. Because of selection biases, the intrinsic average temperature of the bursts is much harder (kT approximately MeV) than the observed average (approximately 200 KeV).

Higdon, J. C.↗

Low-reflectivity spectrally selective coating

Mirror, with area of low reflectivity, replaces neutral-density transmission filter in star-tracking system, increasing reliability. It may have applications in other optical systems.

Zaniewski, J. J.↗

Spectral band selection for classification of soil organic matter content

This paper describes the spectral-band-selection (SBS) algorithm of Chen and Landgrebe (1987, 1988, and 1989) and uses the algorithm to classify the organic matter content in the earth's surface soil. The effectiveness of the algorithm was evaluated comparing the results of classification of the soil organic matter using SBS bands with those obtained using Landsat MSS bands and TM bands, showing that the algorithm was successful in finding important spectral bands for classification of organic matter content. Using the calculated bands, the probabilities of correct classification for climate-stratified data were found to range from 0.910 to 0.980.

Henderson, Tracey L.↗

Solar vector magnetograph for Max 1991 programs

An instrument for measuring solar magnetic fields is under construction. Key requirements for any solar vector magnetograph are high spatial resolution, high optical throughput, fine spectral selectivity, and ultralow instrumental polarization. An available 25 cm Cassegrain telescope will provide 0.5 arcsec spatial resolution. Spectral selection will be accomplished with a 150 mA filter based on electrically tunable solid Fabry-Perot etalon. Filter and polarization analyzer design concepts for the magnetograph are described in detail. The instrument will be tested at JHU/APL, and then moved to the National Solar Observatory in late 1988. It will be available to support the Max 1991 program.

Rust, D. M.↗

A tool for manual endmember selection and spectral unmixing

Sampling a continuous radiance spectrum in many narrow contiguous spectral bands results in a high covariance between the bands. Hence, the true dimensionality of imaging spectrometer data is not determined by the number of spectral bands, but by the number of spectrally unique signatures whose mixtures reproduce the spectral variance observed in an image. Methods to unmix high dimensional multispectral data use principal components analysis to reduce the dimensionality. The variance of the spectral data is modeled as a linear combination of a finite set of endmembers in the space of the eigen-vectors that account for most of the variance. The number and characteristics of these endmembers are determined not only by the number and characteristics of the spectrally unique materials on the surface but also by processes (e.g., illumination, atmospheric scattering and absorption) affecting the signal received by the sensor. Selection of endmember spectra has typically been from a library. However, since most libraries are incomplete and do not account for the processes mentioned above, we have devised a computer display that allows researchers to explore interactively the eigenvector space of a representative and mean-corrected subset of the image data in search of extreme spectra to designate as endmembers. This display, which is based on parallel coordinates, is unique in the area of multidimensional visualization in that it includes not only a passive view of higher dimensional data but also the capability to interact and move geometrical objects in higher dimensional spaces.

Bateson, C. Ann↗

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.↗

Spectral signature selection for mapping unvegetated soils

Airborne multispectral scanner data covering the wavelength interval from 0.40-2.60 microns were collected at an altitude of 1000 m above the terrain in southeastern Pennsylvania. Uniform training areas were selected within three sites from this flightline. Soil samples were collected from each site and a procedure developed to allow assignment of scan line and element number from the multispectral scanner data to each sampling location. These soil samples were analyzed on a spectrophotometer and laboratory spectral signatures were derived. After correcting for solar radiation and atmospheric attenuation, the laboratory signatures were compared to the spectral signatures derived from these same soils using multispectral scanner data. Both signatures were used in supervised and unsupervised classification routines. Computer-generated maps using the laboratory and multispectral scanner derived signatures resulted in maps that were similar to maps resulting from field surveys. Approximately 90% agreement was obtained between classification maps produced using multispectral scanner derived signatures and laboratory derived signatures.

May, G. A.↗

Development of a quantitative basis for selection of spectral features in a vegetation monitoring system

The development of an objective methodology for evaluation of alternative Landsat data preprocessing options, spectral transform features for monitoring vegetation, and feature summarization algorithms is presented. Based on estimates of spectral separability between a target class and its confusion classes, analysis of variance techniques are used to evaluate potential design options for large scale vegetation monitoring systems. Case studies are presented for early season and through the season spring small grains separation and for barley/other spring small grains separation. It is concluded that a basis for efficient, objective selection among alternative feature extraction approaches has been established for the large scale vegetation mapping/inventory problem. Although the approach has been demonstrated for the unitemporal class separability case, extensions to the multitemporal case are under development.

Phinney, D. E.↗