Search NASA⌕ Search

SEARCH · Search NASA

Results for “Discriminant Analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Investigation of varying gray scale levels for remote manipulation

A study was conducted to investigate the effects of variant monitor gray scale levels and workplace illumination levels on operators' ability to discriminate between different colors on a monochrome monitor. It was determined that 8-gray scale viewing resulted in significantly worse discrimination performance compared to 16- and 32-gray scale viewing and that there was only a negligible difference found between 16 and 32 shades of gray. Therefore, it is recommended that monitors used while performing remote manipulation tasks have 16 or above shades of gray since this evaluation has found levels lower than this to be unacceptable for color discrimination task. There was no significant performance difference found between a high and a low workplace illumination condition. Further analysis was conducted to determine which specific combinations of colors can be used in conjunction with each other to ensure errorfree color coding/brightness discrimination performance while viewing a monochrome monitor. It was found that 92 three-color combination and 9 four-color combinations could be used with 100 percent accuracy. The results can help to determine which gray scale levels should be provided on monochrome monitors as well as which colors to use to ensure the maximal performance of remotely-viewed color discrimination/coding tasks.

Bierschwale, John M.↗
NASA NTRS1978

Some observations about LANDSAT digital analysis

Several hypotheses concerning LANDSAT data are analyzed. These hypotheses are: (1) LANDSAT does not discriminate vegetation types, but mostly sees chlorophyl and canopy cover. (2) A majority of the features in the ground scene possess linearly proportional amounts of color from each spectral band. (3) The data are continuous and as a result there is no true separability of ground scene features in the data, but some features possess an excess of color in a particular band pair. (4) There are relatively few features present in the spectral data, and these do not correspond to the conventional definitions that are used. (5) Aside from seasonal effects, in a distributional sense all LANDSAT data are essentially the same. The only difference is the way the data are spatially arranged in the image.

Jayroe, R. R., Jr.↗
NASA NTRS1983

Interpretation of radar returns from clear air: Discrimination against clutter

Different kinds of inteference may cause problems to the proper detection and analysis of the atmospheric signals, when using VHF and UHF radars. These are separated into passive and active contributions. Passive contributions are existent in the receiving system without the radar transmitter switched on. Active contributions are due to scatter and reflection of the own transmitted radar signal from unwanted targets, which are called clutter. Of major importance to radar systems are active interference contributions. Different methods can be applied for elimination or at least suppressing unwanted effects. These are; (1) Directional filtering, i.e., applying optimum suppression of antenna sidelobes, (2) Range filtering, i.e., suppressing unwanted signals only in affected range gates, (3) selection by amplitude distributions, (4) Temporal filtering, i.e., recognizing typical temporal variations of the clutter signals, through spectral characteristics, and applying matched filters.

Rottger, J.↗
NASA NTRS1984

Analysis of the Gran Desierto, Pinacte Region, Sonora, Mexico, via shuttle imaging radar

The radar discriminability of geolian features and their geological setting as imaged by the SIR-A experiment is examined. The Gran Desierto and Pincate volcanio field of Sonora, Mexico was used to analyze the radar characteristics of the interplay of aeolian features and volcano terrain. The area in the Gran Desierto covers 4000 sq. km. and contains sand dunes of several forms. The Pincate volcanio field covers more than 2.000 sq. km. and consists primarily of basaltic lavas. Margins of the field, especially on the western and northern sides, include several maar and maar-like craters; thus obtaining information on their radar characteristics for comparison with impact craters.

Greeley, R.↗
NASA NTRS1991

Multi-frequency and polarimetric radar backscatter signatures for discrimination between agricultural crops at the Flevoland experimental test site

We describe the calibration and analysis of multi-frequency, multi-polarization radar backscatter signatures over an agriculture test site in the Netherlands. The calibration procedure involved two stages: in the first stage, polarimetric and radiometric calibrations (ignoring noise) were carried out using square-base trihedral corner reflector signatures and some properties of the clutter background. In the second stage, a novel algorithm was used to estimate the noise level in the polarimetric data channels by using the measured signature of an idealized rough surface with Bragg scattering (the ocean in this case). This estimated noise level was then used to correct the measured backscatter signatures from the agriculture fields. We examine the significance of several key parameters extracted from the calibrated and noise-corrected backscatter signatures. The significance is assessed in terms of the ability to uniquely separate among classes from 13 different backscatter types selected from the test site data, including eleven different crops, one forest and one ocean area. Using the parameters with the highest separation for a given class, we use a hierarchical algorithm to classify the entire image. We find that many classes, including ocean, forest, potato, and beet, can be identified with high reliability, while the classes for which no single parameter exhibits sufficient separation have higher rates of misclassification. We expect that modified decision criteria involving simultaneous consideration of several parameters increase performance for these classes.

Freeman, A.↗
NASA NTRS2004

gyrB as a phylogenetic discriminator for members of the Bacillus anthracis-cereus-thuringiensis group

Bacillus anthracis, the causative agent of the human disease anthrax, Bacillus cereus, a food-borne pathogen capable of causing human illness, and Bacillus thuringiensis, a well-characterized insecticidal toxin producer, all cluster together within a very tight clade (B. cereus group) phylogenetically and are indistinguishable from one another via 16S rDNA sequence analysis. As new pathogens are continually emerging, it is imperative to devise a system capable of rapidly and accurately differentiating closely related, yet phenotypically distinct species. Although the gyrB gene has proven useful in discriminating closely related species, its sequence analysis has not yet been validated by DNA:DNA hybridization, the taxonomically accepted "gold standard". We phylogenetically characterized the gyrB sequences of various species and serotypes encompassed in the "B. cereus group," including lab strains and environmental isolates. Results were compared to those obtained from analyses of phenotypic characteristics, 16S rDNA sequence, DNA:DNA hybridization, and virulence factors. The gyrB gene proved more highly differential than 16S, while, at the same time, as analytical as costly and laborious DNA:DNA hybridization techniques in differentiating species within the B. cereus group.

Phylogeny↗
NASA NTRS1993

Mineralogic variability of the Kelso Dunes, Mojave Desert, California derived from Thermal Infrared Multispectral Scanner (TIMS) data

Mineral identification and mapping of alluvial material using thermal infrared (TIR) remote sensing is extremely useful for tracking sediment transport, assessing the degree of weathering and locating sediment sources. As a result of the linear relation between a mineral's percentage in a given area (image pixel) and the depth of its diagnostic spectral features, TIR spectra can be deconvolved in order to ascertain mineralogic percentages. Typical complications such as vegetation, particle size and thermal shadowing are minimized upon examination of dunes. Actively saltating dunes contain little to no vegetation, are very well sorted and lack the thermal shadows that arise from rocky terrain. The primary focus of this work was to use the Kelso Dunes as a test location for an accuracy analysis of temperature/emissivity separation and linear unmixing algorithms. Accurate determination of ground temperature and component discrimination will become key products of future ASTER data. A decorrelation stretch of the TIMS image showed clear color variations within the active dunes. Samples collected from these color units were analyzed for mineralogy, grain size, and separated into endmembers. This analysis not only revealed that the dunes contained significant mineralogic variation, but were more immature (low quartz percentage) than previously reported. Unmixing of the TIMS data using the primary mineral endmembers produced unique variations within the dunes and may indicate near, rather than far, source locales for the dunes. The Kelso Dunes lie in the eastern Mojave Desert, California, approximately 95 km west of the Colorado River. The primary dune field is contained within a topographic basin bounded by the Providence, Granite Mountains, with the active region marked by three northeast trending linear ridges. Although active, the dunes appear to lie at an opposing regional wind boundary which produces little net movement of the crests. Previous studies have estimated the dunes range from 70% to 90% quartz mainly derived from a source 40 km to the west. The dune field is assumed to have formed in a much more arid climate than present, with the age of the deposit estimated at greater than 100,000 years.

Ramsey, Michael S.↗
DOE OSTI2024

Prediction challenge: First principles simulation of the ultrafast electron diffraction spectrum of cyclobutanone

Computer simulation has long been an essential partner of ultrafast experiments, allowing the assignment of microscopic mechanistic detail to low-dimensional spectroscopic data. However, the ability of theory to make a priori predictions of ultrafast experimental results is relatively untested. Herein, as a part of a community challenge, we attempt to predict the signal of an upcoming ultrafast photochemical experiment using state-of-the-art theory in the context of preexisting experimental data. Specifically, we employ ab initio Ehrenfest with collapse to a block mixed quantum–classical simulations to describe the real-time evolution of the electrons and nuclei of cyclobutanone following excitation to the 3s Rydberg state. The gas-phase ultrafast electron diffraction (GUED) signal is simulated for direct comparison to an upcoming experiment at the Stanford Linear Accelerator Laboratory. Following initial ring-opening, dissociation via two distinct channels is observed: the C3 dissociation channel, producing cyclopropane and CO, and the C2 channel, producing CH2CO and C2H4. Direct calculations of the GUED signal indicate how the ring-opened intermediate, the C2 products, and the C3 products can be discriminated in the GUED signal. We also report an a priori analysis of anticipated errors in our predictions: without knowledge of the experimental result, which features of the spectrum do we feel confident we have predicted correctly, and which might we have wrong?

Chemistry↗
NASA NTRS1973

Effects of changing canopy directional reflectance on feature selection

The use of a Monte Carlo model for generating sample directional reflectance data for two simplified target canopies at two different solar positions is reported. Successive iterations through the model permit the calculation of a mean vector and covariance matrix for canopy reflectance for varied sensor view angles. These data may then be used to calculate the divergence between the target distributions for various wavelength combinations and for these view angles. Results of a feature selection analysis indicate that different sets of wavelengths are optimum for target discrimination depending on sensor view angle and that the targets may be more easily discriminated for some scan angles than others. The time-varying behavior of these results is also pointed out.

Smith, J. A.↗
NASA NTRS1975

Computer analysis and mapping of gypsy moth levels in Pennsylvania using LANDSAT-1 digital data

The effectiveness of using LANDSAT-1 multispectral digital data and imagery, supplemented by ground truth and aerial photography, was investigated as a new method of surveying gypsy moth (Porthetria dispar (L.)) (Lepidoptera; Lymantriidae) defoliation, which has greatly increased in Pennsylvania in recent years. Since the acreage and severity of gypsy moth defoliation reaches a peak from mid-June through the first few days of July, the July 8, 1973, LANDSAT-1 scene was chosen for analysis. Results indicate that LANDSAT-1 data can be used to discriminate between defoliated and healthy vegetation in Pennsylvania and that digital processing methods can be used to map the extent and degree of defoliation.

Williams, D. L.↗
NASA NTRS1995

Vegetation species composition and canopy architecture information expressed in leaf water absorption measured in the 1000 nm and 2200 spectral region by an imaging spectrometer

Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring, and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local to regional and even synoptic scales. Classical approaches rely on vegetation indices such as the normalized difference vegetation index (NDVI) to estimate biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine-scale information about specific sites to larger areas of similar composition. Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and that may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some of this capability has been demonstrated through improved discrimination of vegetation, estimates of canopy biochemistry, and liquid water estimates from vegetation. We investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from two spectral regions, the 1000-nm region and the 2200-nm region. The study was conducted in the vicinity of Jasper Ridge, California, which is located on the San Francisco peninsula to the west of the Stanford University campus. AVIRIS data were acquired over Jasper Ridge, CA, on June 2, 1992, at 19:31 UTC. Spectra from three sites in this image were analyzed. These data are from an area of healthy grass, oak woodland, and redwood forest, respectively. For these analyses, the AVIRIS-measured upwelling radiance spectra for the entire Jasper Ridge scene were transformed to apparent surface reflectance using a radiative transfer code-based inversion algorithm.

Green, Robert O.↗
NASA NTRS2000

Discriminating Type 1a and 1b PSCs in Satellite Data

We explore the use of satellite observations in discriminating types of PSCs and their ramifications. Polar Stratospheric Clouds (PSCs), which form in the winter polar vortex, have been identified as effecting ozone loss. One major result from the recent SOLVE mission is in-situ evidence of the existence of very large particles that contain nitric acid. These particles are consistent with Type la PSCs. The significance of this finding is that these large particles will have appreciable sedimentation velocities, taking nitric acid out of the stratospheric regions, causing denitrification. Since nitric acid typically mitigates ozone loss, denitrification leads to increased ozone loss. Type lb PSCs are smaller and do not sediment to any appreciable degree. Satellite measurements are made continuously throughout the winter, and offer more global coverage than in situ measurements. Thus, it would very useful to be able to discriminate PSC types from satellite measurements. Our long-term goals are to better understand the formation mechanisms and effects of PSCs. Discriminating PSC type using satellite data will give us a very important tool in this effort. A multi-wavelength analysis of POAM aerosol extinction during SOLVE has revealed differences in the radiative characteristics of PSC events. We explore the use of POAM observations to discriminate between Type la and lb Pscs. A trajectory model is used to simulate PSC la and lb particles. Calculated radiative properties act as a guide for discriminating the satellite occultation measurements. Aircraft based PSC observations are-used as confirmation of these observations.

Strawa, Anthony W.↗
NASA NTRS1980

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 2 of 2

A generalized four-channel hyperplane to discriminate water from non-water was developed using LANDSAT-3 multispectral scanner (MSS) scences and matching same/next-day color infrared aerial photography. The MSS scenes over upstate New York, eastern Washington, Montana and Louisiana taken between May and October 1978 varied in Sun elevation angle from 40 to 58 degrees. The 28 matching air photo frames selected for analysis 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. Approximately 1300 pixels, half of them non-edge water pixels and half non-water pixels spectrally close to water, were labelled. A linear discriminant was iteratively fitted to the labelled pixels, giving more weight to those pixels that were difficult to discriminate. This discriminant correctly classified 98.7 percent of the water pixels and 98.6 percent of the non-water pixels.

Schlosser, E. H.↗
NASA NTRS1990

X-ray spectral signatures of photoionized plasmas

Plasma emission codes have become a standard tool for the analysis of spectroscopic data from cosmic X-ray sources. However, the assumption of collisional equilibrium, typically invoked in these codes, renders them inapplicable to many important astrophysical situations, particularly those involving X-ray photoionized nebulae. This point is illustrated by comparing model spectra which have been calculated under conditions appropriate to both coronal plasmas and X-ray photoionized plasmas. It is shown that the (3s-2p)/(3d-2p) line ratios in the Fe L-shell spectrum can be used to effectively discriminate between these two cases. This diagnostic will be especially useful for data analysis associated with AXAF and XMM, which will carry spectroscopic instrumentation with sufficient sensitivity and resolution to identify X-ray photoionized nebulae in a wide range of astrophysical environments.

Liedahl, Duane A.↗
NASA NTRS2008

Mapping Snow Grain Size over Greenland from MODIS

This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than MODIS-derived SGS. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the first melting period in mid-June. Following detailed time series analysis of SGS for four permanent sites, the paper presents SGS maps over the Greenland ice sheet for the March-September period of 2004.

Lyapustin, Alexei↗
NASA NTRS1973

Temporal analysis of multispectral scanner data.

Multispectral scanner reflectance data were sampled for bare soil, cotton, sorghum, corn, and citrus at four dates during a growing season (April, May, June, and July 1969) to develop a time-dependent signature for crop and soil discrimination. Discrimination tests were conducted for single-date and multidate formats using training and test data sets. For classifications containing several crops, the multidate or temporal approach improved discrimination compared with the single-date approach. The multidate approach also preserved recognition accuracy better in going from training fields to test fields than the single-date analysis. The spectral distinctiveness of bare soil versus vegetation resulted in essentially equal discrimination using single-date versus multidate data for those two categories.

Richardson, A. J.↗
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.↗