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At least 145 records · Page 8

The continuum spectral characteristics of gamma ray bursts observed by BATSE

Distributions of the continuum spectral characteristics of 260 bursts in the first Burst and Transient Source Experiment (BATSE) catalog are presented. The data are derived from flux ratios calculated from the BATSE Large Area Detector (LAD) four channel discriminator data. The data are converted from counts to photons using a direct spectral inversion technique to remove the effects of atmospheric scattering and the energy dependence of the detector angular response. Although there are intriguing clusterings of bursts in the spectral hardness ratio distributions, no evidence for the presence of distinct burst classes based on spectral hardness ratios alone is found. All subsets of bursts selected for their spectral characteristics in this analysis exhibit spatial distributions consistent with isotropy. The spectral diversity of the burst population appears to be caused largely by the highly variable nature of the burst production mechanisms themselves.

Pendleton, Geoffrey N.↗

Investigation of spectral analysis techniques for randomly sampled velocimetry data

It is well known that velocimetry (LV) generates individual realization velocity data that are randomly or unevenly sampled in time. Spectral analysis of such data to obtain the turbulence spectra, and hence turbulence scales information, requires special techniques. The 'slotting' technique of Mayo et al, also described by Roberts and Ajmani, and the 'Direct Transform' method of Gaster and Roberts are well known in the LV community. The slotting technique is faster than the direct transform method in computation. There are practical limitations, however, as to how a high frequency and accurate estimate can be made for a given mean sampling rate. These high frequency estimates are important in obtaining the microscale information of turbulence structure. It was found from previous studies that reliable spectral estimates can be made up to about the mean sampling frequency (mean data rate) or less. If the data were evenly samples, the frequency range would be half the sampling frequency (i.e. up to Nyquist frequency); otherwise, aliasing problem would occur. The mean data rate and the sample size (total number of points) basically limit the frequency range. Also, there are large variabilities or errors associated with the high frequency estimates from randomly sampled signals. Roberts and Ajmani proposed certain pre-filtering techniques to reduce these variabilities, but at the cost of low frequency estimates. The prefiltering acts as a high-pass filter. Further, Shapiro and Silverman showed theoretically that, for Poisson sampled signals, it is possible to obtain alias-free spectral estimates far beyond the mean sampling frequency. But the question is, how far? During his tenure under 1993 NASA-ASEE Summer Faculty Fellowship Program, the author investigated from his studies on the spectral analysis techniques for randomly sampled signals that the spectral estimates can be enhanced or improved up to about 4-5 times the mean sampling frequency by using a suitable prefiltering technique. But, this increased bandwidth comes at the cost of the lower frequency estimates. The studies further showed that large data sets of the order of 100,000 points, or more, high data rates, and Poisson sampling are very crucial for obtaining reliable spectral estimates from randomly sampled data, such as LV data. Some of the results of the current study are presented.

Sree, Dave↗

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↗

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Sabol, Donald E., Jr.↗

The Benard problem: A comparison of finite difference and spectral collocation eigen value solutions

The application of spectral methods, using a Chebyshev collocation scheme, to solve hydrodynamic stability problems is demonstrated on the Benard problem. Implementation of the Chebyshev collocation formulation is described. The performance of the spectral scheme is compared with that of a 2nd order finite difference scheme. An exact solution to the Marangoni-Benard problem is used to evaluate the performance of both schemes. The error of the spectral scheme is at least seven orders of magnitude smaller than finite difference error for a grid resolution of N = 15 (number of points used). The performance of the spectral formulation far exceeded the performance of the finite difference formulation for this problem. The spectral scheme required only slightly more effort to set up than the 2nd order finite difference scheme. This suggests that the spectral scheme may actually be faster to implement than higher order finite difference schemes.

Skarda, J. Raymond Lee↗

Determination of the in-flight spectral calibration of AVIRIS using atmospheric absorption features

Spectral calibration of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) as data are acquired in flight is essential to quantitative analysis of the measured upwelling spectral radiance. In each spectrum measured by AVIRIS in flight, there are numerous atmospheric gas absorption bands that drive this requirement for accurate spectral calibration. If the surface and atmospheric properties are measured independently, these atmospheric absorption bands may be used to deduce the in-flight spectral calibration of an imaging spectrometer. Both the surface and atmospheric characteristics were measured for a calibration target during an in-flight calibration experiment held at Lunar Lake, Nevada on April 5, 1994. This paper uses upwelling spectral radiance predicted for the calibration target with the MODTRAN radiative transfer code to validate the spectral calibration of AVIRIS in flight.

Green, Robert O.↗

Magnetic spectral signatures in the Earth's magnetosheath and plasma depletion layer

Correlations between plasma properties and magnetic fluctuations in the sub-solar magnetosheath downstream of a quasi-perpendicular shock have been found and indicate that mirror and ion cyclotronlike fluctuations correlate with the magnetosheath proper and plasma depletion layer, respectively (Anderson and Fueselier, 1993). We explore the entire range of magnetic spectral signatures observed from the Active Magnetospheric Particle Tracer Explorers/Charge Composition Explorer (AMPTE/CCE)spacecraft in the magnetosheath downstream of a quasi-perpendicular shock. The magnetic spectral signatures typically progress from predominantly compressional fluctuations,delta B(sub parallel)/delta B perpendicular to approximately 3, with F/F (sub p) less than 0.2 (F and F (sub p) are the wave frequency and proton gyrofrequency, respectively) to predominantly transverse fluctuations, delta B(sub parallel)/delta B perpendicular to approximately 0.3, extending up to F(sub p). The compressional fluctuations are characterized by anticorrelation between the field magnitude and electron density, n(sub e), and by a small compressibility, C(sub e) identically equal to (delta n(sub e)/n(sub e)) (exp 2) (B/delta B(sub parallel)) (exp 2) approximately 0.13, indicative of mirror waves. The spectral characteristics of the transverse fluctuations are in agreement with predictions of linear Vlasov theory for the H(+) and He(2+) cyclotron modes. The power spectra and local plasma parameters are found to vary in concert: mirror waves occur for beta(s ub parallel p) (beta (sub parallel p) identically = 2 mu(sub zero) n(sub p) kT (sub parallel p) / B(exp 2) approximately = 2, A(sub p) indentically = T(sub perpendicular to p)/T(sub parallel p) - 1 approximately = 0.4, whereas cyclotron waves occur for beta (sub parallel p) approximately = 0.2 and A(sub p) approximately = 2. The transition from mirror to cyclotron modes is predicted by linear theory. The spectral characteristics overlap for intermediate plasma parameters. The plasma observations are described by A(sub p) = 0.85 beta(sub parallel P) (exp - 0.48) with a log regression coefficient of -0.74. This inverse A(sub p) - beta(sub parallel p) correlation corresponds closely to the isocontours of maximum ion anisotropy instability growth, gamma (sub m)/omega(sub p) = 0.01, for the mirror and cyclotron modes. The agreement of observed properties and predictions of local theory suggests that the spectral signatures reflect the local plasma environment and that the anisotropy instabilities regulate A(sub p). We suggest that the spectral characteristics may provide a useful basis for ordering observations in the magnetosheath and that the A(sub p) - beta(sub parallel p) inverse correlation may be used as a beta-dependent upper limit on the proton anisotropy to represent kinetic effects.

Anderson, Brian J.↗

The continuum spectral characteristics of gamma-ray bursts observed by BATSE

Distributions of the continuum spectral characteristics of 260 bursts in the first Burst And Transient Source Experiement (BATSE) catalog are presented. The data are derived from flux calculated from BATSE Large Area Detector (LAD) four-channel discriminator data. The data are converted from counts to protons using a direct spectral inversion technique to remove the effects of atmospheric scattering and the energy dependence of the detector angular response. Although there are intriguing clusters of bursts in the spectral hardness ratio distributions, no evidence for the presence of distinct burst classes based in spectral hardness ratios alone is found. All subsets of bursts selected for their spectral characteristics in this analysis exhibit spatial distributions consistent with isotropy. The spectral diversity of the burst population appears to be caused largely by the highly variable nature of the burst production mechanisms themselves.

Pendleton, Geoffrey N.↗

Low mass companions to nearby stars: Spectral classification and its relation to the stellar/substellar break

The relationship between mass and spectral class for main-sequence stars has never been obtained for dwarfs cooler than M6; currently, the true nature of objects classified as M7, M8, M9, or later (be they stellar or substellar) is not known. In this paper, spectral types for the components in five low mass binary systems are estimated based on previously published infrared speckle measurements, red/infrared photometry, and parallax data, together with newly acquired high signal-to-noise composite spectra of the systems and revised magnitude difference relations for M dwarfs. For two of these binaries, the secondary has a smaller mass (less than 0.09 solar mass) than any object having a dynamically measured mass and a known spectral type, thus extending the spectral class/mass relation to lower masses than has previously been possible. Data from the higher mass components (0.09 solar mass less than M less than 0.40 solar mass) are consistent with earlier results; the two lowest mass objects -- though having mass errors which could place them on either side of the M dwarf/brown dwarf dividing line (Mass is about 0.08 solar mass) -- are found to have spectral types no cooler than M6.5 V. An extrapolation of the updated spectral class/mass relation to the hydrogen-burning limit suggests that objects of type M7 and later may be substellar. Direct confirmation of this awaits the discovery of a close, very late-type binary for which dynamical masses can be measured.

Kirkpatrick, J. Davy↗

Augmentation of the IUE Ultraviolet Spectral Atlas

The IUE Ultraviolet Spectral Atlas and the first addendum were published by Wu et al. in printed and machine readable versions. This atlas and addendum contain UV spectra of 315 stars with spectral types ranging from O3 to M5 and many spectral type-luminosity class combinations. There were three criteria for selecting these stars: (1) they were not spectroscopic binaries or variables with significant changes in magnitude or color, (2) they must have well-determined spectral types (many are MK standards), and (3) the stars should not be heavily reddened. Further augmentation of the atlas is desirable to provide a more complete coverage of the spectral type-luminosity class combinations and more than one star per combination. The extra spectral type-luminosity class combinations reduce the need for interpolation. The extra stars within a given combination guard against variability and peculiarity, and allow for a finite range of temperature, metallicity and gravity. The previous atlas and addendum presented data that were obtained through the eleventh episode under IUE programs with C.-C. Wu and D. Burstein as principal investigators. In this second addendum, we present the spectra obtained by Wu's programs during the twelfth through seventeenth episodes: SALCW, SAMCW, SANCW, SAOCW, SAPCW and SAQCW. During the period between July 1989 and September 1994, Wu observed 183 stars under these programs. Most of these observations are high quality trails or pseudo-trails (multiple exposures in the large aperture).

Wu, Chi-Chao↗

Understanding the Long-Term Spectral Variability of Cygnus X-1 from BATSE and ASM Observations

We present a spectral analysis of observations of Cygnus X-1 by the RXTE/ASM (1.5-12 keV) and CGRO/BATSE (20-300 keV), including about 1200 days of simultaneous data. We find a number of correlations between intensities and hardnesses in different energy bands from 1.5 keV to 300 keV. In the hard (low) spectral state, there is a negative correlation between the ASM 1.5-12 keV flux and the hardness at any energy. In the soft (high) spectral state, the ASM flux is positively correlated with the ASM hardness (as previously reported) but uncorrelated with the BATSE hardness. In both spectral states, the BATSE hardness correlates with the flux above 100 keV, while it shows no correlation with the flux in the 20-100 keV range. At the same time, there is clear correlation between the BATSE fluxes below and above 100 keV. In the hard state, most of the variability can be explained by softening the overall spectrum with a pivot at approximately 50 keV. The observations show that there has to be another, independent variability pattern of lower amplitude where the spectral shape does not change when the luminosity changes. In the soft state, the variability is mostly caused by a variable hard (Comptonized) spectral component of a constant shape superimposed on a constant soft blackbody component. These variability patterns are in agreement with the dependence of the rms variability on the photon energy in the two states. We interpret the observed correlations in terms of theoretical Comptonization models. In the hard state, the variability appears to be driven mostly by changing flux in seed photons Comptonized in a hot thermal plasma cloud with an approximately constant power supply. In the soft state, the variability is consistent with flares of hybrid, thermal/nonthermal, plasma with variable power above a stable cold disk. Also, based on broadband pointed observations simultaneous with those of the ASM and BATSE, we find the intrinsic bolometric luminosity increases by a factor of approximately 3-4 from the hard state to the soft one, which supports models of the state transition based on a change of the accretion rate.

Zdziarski, Andrzej A.↗

Spectral Re-Growth Reduction for CCSDS 8-D 8-PSK TCM

This report presents a study on the CCSDS recommended 8-dimensional 8 PSK Trellis Coded Modulation (TCM) scheme. The important steps of the CCSDS scheme include: conversion of serial data into parallel form, differential encoding, convolutional encoding, constellation mapping, and filtering the 8-PSK symbols using the square root raised cosine (SRRC) pulses. The last step, namely the filtering of the 8 PSK symbols using SRRC pulses, significantly affects the bandwidth of the signal. If a nonlinear power amplifier is used, the SRRC filtered signal creates spectral regrowth. The purpose of this report is to investigate a technique, called the smooth phase interpolated keying (SPIK), that can provide an alternative to SRRC filtering so that good spectral as well as power efficiencies can be obtained with the CCSDS encoder. The results of this study show that the CCSDS encoder does not affect the spectral shape of the SRRC filtered signal or the SPIK signal. When a nonlinear traveling wave tube amplifier (TWTA) is used, the spectral performance of the SRRC signal degrades significantly while the spectral performance of SPIK remains unaffected. The degrading effect of a nonlinear solid state power amplifier (SSPA) on SRRC is found to be less than that due to a nonlinear TWTA. However, in both cases, the spectral performance of the SRRC modulated signal is worse than that of the SPIK signal. The bit error rate (BER) performance of the SRRC signal in a linear amplifier environment is about 2.5 dB better than that of the SPIK signal when both the receivers use algorithms of similar complexity. In a nonlinear TWTA environment, the SRRC signal requires accurate phase tracking since the TWTA introduces additional phase distortion. This problem does not arise with SPIK signal due to its constant envelope property. When a nonlinear amplifier is used, the SRRC method loses nearly 1 dB in the bit error rate performance. The SPIK signal does not lose any performance. Thus the performance gap between SRRC and SPIK reduces. The BER performance of SPIK can be improved even further by using a more optimal receiver. A similar optimal receiver for SRRC is quite complex since the amplifier distorts the pulse shape. However, this requires further investigation and is not covered in this report.

Borah, Deva K.↗

Understanding the Long-Term Spectral Variability of Cygnus X-1 with Burst and Transient Source Experiment and All-Sky Monitor Observations

We present a comprehensive analysis of all observations of Cyg X-1 by the Compton Gamma Ray Observatory Burst and Transient Source Experiment (BATSE; 20-300 keV) and by the Rossi X-Ray Timing Explorer all-sky monitor (ASM; 1.5-12 keV) until 2002 June, including approximately 1200 days of simultaneous data. We find a number of correlations between fluxes and hardnesses in different energy bands. In the hard (low) spectral state, there is a negative correlation between the ASM 1.5-12 keV flux and the hardness at any energy. In the soft (high) spectral state, the ASM flux is positively correlated with the ASM hardness but uncorrelated with the BATSE hardness. In both spectral states, the BATSE hardness correlates with the flux above 100 keV, while it shows no correlation with the 20-100 keV flux. At the same time, there is clear correlation between the BATSE fluxes below and above 100 keV. In the hard state, most of the variability can be explained by softening the overall spectrum with a pivot at approximately 50 keV. There is also another, independent variability pattern of lower amplitude where the spectral shape does not change when the luminosity changes. In the soft state, the variability is mostly caused by a variable hard (Comptonized) spectral component of a constant shape superposed on a constant soft blackbody component. These variability patterns are in agreement with the dependencies of the rms variability on the photon energy in the two states. We also study in detail recent soft states from late 2000 until 2002. The last of them has lasted thus far for more than 200 days. Their spectra are generally harder in the 1.5-5 keV band and similar or softer in the 3-12 keV band than the spectra of the 1996 soft state, whereas the rms variability is stronger in all the ASM bands. On the other hand, the 1994 soft state transition observed by BATSE appears very similar to the 1996 one. We interpret the variability patterns in terms of theoretical Comptonization models. In the hard state, the variability appears to be driven mostly by changing flux in seed photons Comptonized in a hot thermal plasma cloud with an approximately constant power supply. In the soft state, the variability is consistent with flares of hybrid, thermal/nonthermal, plasma with variable power above a stable cold disk. The spectral and timing differences between the 1996 and 2000-2002 soft states are explained by a decrease of the color disk temperature. Also, on the basis of broadband pointed observations simultaneous with those of the ASM and BATSE, we find the intrinsic bolometric luminosity increases by a factor of approximately 3-4 from the hard state to the soft one, which supports models of the state transition based on a change of the accretion rate.

Zdziarski, Andrzej A.↗

Comprehensive Analysis of RXTE Data from Cyg X-1. Spectral Index-Quasi-Periodic Oscillation Frequency-Luminosity Correlations

We present timing and spectral analysis of approx. 2.2 Ms of Rossi X-ray Time Explorer (RXTE) archival data from Cyg X-1. Using the generic Comptonization model we reveal that the spectrum of Cyg X-1 consists of three components: a thermal seed photon spectrum, a Comptonized part of the seed photon spectrum and the iron line. We find a strong correlation between 0.1-20 Hz frequencies of quasiperiodic oscillations (QPOs) and the spectral power-law index. Presence of two spectral phases (states) are clearly seen in the data when the spectral indices saturate at low and high values of QPO frequencies. This saturation effect was discovered earlier in a number of black hole candidate (BHC) sources and now we strongly confirm this phenomenon in Cyg X-1. In the soft state this index- QPO frequency correlation shows a saturation of the photon index Gamma approx. 2.1 at high values of the low frequency upsilon(sub L). The saturation level of Gamma approx. 2.1 is the lowest value found yet in BHCs. The bolometric luminosity does not show clear correlation with the index. We also show that Fe K(sub alpha) emission line strength (equivalent width, EW) correlates with the QPO frequency. EW increases from 200 eV in the low/hard state to 1.5 keV in the high/soft state. The revealed observational correlations allow us to propose a scenario for the spectral transition and iron line formation which occur in BHC sources. We also present the spectral state (the power-law index) evolution for eight years of Cyg X-1 observations by RXTE.

Shaposhnikov, Nickolai↗

SHJAR Jet Noise Data and Power Spectral Laws

High quality jet noise spectral data measured at the Aeroacoustic Propulsion Laboratory at the NASA Glenn Research Center is used to examine a number of jet noise scaling laws. Configurations considered in the present study consist of convergent and convergent-divergent axisymmetric nozzles. The measured spectral data are shown in narrow band and cover 8193 equally spaced points in a typical Strouhal number range of 0.0 to 10.0. The measured data are reported as lossless (i.e., atmospheric attenuation is added to measurements), and at 24 equally spaced angles (50deg to 165deg) on a 100-diameter (200-in.) arc. Following the work of Viswanathan, velocity power factors are evaluated using a least squares fit on spectral power density as a function of jet temperature and observer angle. The goodness of the fit and the confidence margins for the two regression parameters are studied at each angle, and alternative relationships are proposed to improve the spectral collapse when certain conditions are met. As an immediate application of the velocity power laws, spectral density in shockcontaining jets are decomposed into components attributed to jet mixing noise and shock noise. From this analysis, jet noise prediction tools can be developed with different spectral components derived from different physics.

Khavaran, Abbas↗

NEOCAM: Near Earth Object Chemical Analysis Mission: Bridging the Gulf between Telescopic Observations and the Chemical and Mineralogical Compositions of Asteroids or Diogenes A: Diagnostic Observation of the Geology of Near Earth Spectrally-Classified Asteroids

Studies of meteorites have yielded a wealth of scientific information based on highly detailed chemical and isotopic studies possible only in sophisticated terrestrial laboratories. Telescopic studies have revealed an enormous (greater than 10(exp 5)) number of physical objects ranging in size from a few tens of meters to several hundred kilometers, orbiting not only in the traditional asteroid belt between Mars and Jupiter but also throughout the inner solar system. Many of the largest asteroids are classed into taxonomic groups based on their observed spectral properties and are designated as C, D. X, S or V types (as well as a wide range in sub-types). These objects are certainly the sources far the meteorites in our laboratories, but which asteroids are the sources for which meteorites? Spectral classes are nominally correlated to the chemical composition and physical characteristics of the asteroid itself based on studies of the spectral changes induced in meteorites due to exposure to a simulated space environment. While laboratory studies have produced some notable successes (e.g. the identification of the asteroid Vesta as the source of the H, E and D meteorite classes), it is unlikely that we have samples of each asteroidal spectral type in our meteorite collection. The correlation of spectral type and composition for many objects will therefore remain uncertain until we can return samples of specific asteroid types to Earth for analyses. The best candidates for sample return are asteroids that already come close to the Earth. Asteroids in orbit near 1 A.U. have been classified into three groups (Aten, Apollo & Amor) based on their orbital characteristics. These Near Earth Objects (NEOs) contain representatives of virtually all spectral types and sub-types of the asteroid population identified to date. Because of their close proximity to Earth, NEOs are prime targets for asteroid missions such as the NEAR-Shoemaker NASA Discovery Mission to Eros and the Japanese Hyabusa Mission to Itokawa. Also due to their close proximity to Earth, NEOs constitute the most likely set of celestial objects that will impact us in the relatively near future.

Nuth, Joseph A.↗

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Srivastava, Askok N.↗

Physical Interpretation of the Correlation Between Multi-Angle Spectral Data and Canopy Height

Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally

Schull, M. A.↗