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NASA NTRS1986

Information extraction from multivariate images

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

Park, S. K.↗

NASA NTRS1987

Engima of a thermal anomaly - A TM/AVHRR study of the volcanic Arabian highlands

Discovery of a large thermal anomaly in the western Arabian highlands on Landsat TM imagery is reported. The anomaly, 15 C warmer than surroundings, forms a 2-km-wide arc around the southern flank of Jebel Chada, a volcano active in 1256 AD. It is recorded by AVHRR imagery as well, despite the 1.1-km spatial resolution of this sensor. Air photos and geologic maps show no bedrock unit that corresponds to the anomaly. Digital techniques were applied to the TM and AVHRR data, including contrast enhancement, density slicing, principal components analysis, and construction of multiband composite images. It is concluded that the anomaly results from a thin cover of volcanic ash or cinder that is optically indistinguishable from underlying basalt, rather than from internal (volcanic or hydrologic) heat sources.

Blodget, H. W.↗

NASA NTRS1988

Discrimination of hydrothermal alteration mineral assemblages at Virginia City, Nevada, using the airborne imaging spectrometer

The purpose of this study is to use airborne imaging spectrometer data to discriminate hydrothermal alteration mineral assemblages associated with silver and gold mineralization at Virginia City, NV. The data is corrected for vertical striping and sample gradients, and converted to flat-field logarithmic residuals. Log residual spectra from areas known to be altered are compared to field spectra for kaolinitic, illitic, sericitic, and propylitic alteration types. The areal distributions of these alteration types are estimated using a spectral matching technique. Both visual examination of spectra and the matching techniques are effective in distinguishing kaolinitic, illitic, and propylitic alteration types from each other. However, illitic and sericitic alteration cannot be separated using these techniques because the spectra of illite and sericite are very similar. A principal components analysis of 14 channels in the 2.14-2.38 micron wavelength region is also successful in discriminating and mapping illitic, kaolinitic, and propylitic alteration types.

Hutsinpiller, Amy↗

NASA NTRS1988

Comparison of techniques for discriminating hydrothermal alteration minerals with Airborne Imaging Spectrometer data

Hydrothermal alteration mineralogy in the Tybo mining district of Nevada has been mapped on the basis of high spectral and spatial resolution Airborne Imaging Spectrometer (AIS) data, using band ratios, principal component analysis, and a signature-matching algorithm to delineate the alteration zones and limestone foundations. The signature-matching algorithm is found to be the most effective method of discriminating alteration minerals, and is noted to be able to identify mineralogy by matching AIS image spectra with library reference spectra. AIS bands in the 2048-2337-nm portion of the spectrum accounted for the greatest amount of variance.

Feldman, Sandra C.↗

NASA NTRS1987

Multispectral geologic remote sensing of a suspected impact crater near Al Madafi, Saudi Arabia

A multispectral Landsat TM image of a 6-km-diameter circular formation at Al Madafi in NW Saudi Arabia is interpreted by means of color-band composites, band ratios, and principal-components analysis to determine the nature of this feature. The geological characteristics of impact craters are discussed, and the satellite-image analysis techniques are described. Disruptions in the pattern of spectral signatures are seen in the Al Madafi formation and shown to be consistent with an impact origin.

Garvin, J. B.↗

NASA NTRS1988

A Landsat Thematic Mapper investigation of the geobotanical relationships in the northern spruce-fir forest, Mt. Moosilauke, New Hampshire

This investigation, in the northern spruce-fir forest at Mt. Moosilauke, NH, indicates that Landsat TM data can be used to distinguish between and map major vegetation zones. Principal components analysis can be used to reduce the dimensionality of the TM data; and in this simpler spectral space, it is easier to visualize the discrimination between major vegetation zones: the northern hardwoods zone, spruce-fir zone, fir zone, and alpine tundra zone. The moisture stress index highlights areas of heavy forest damage (fir waves), but does not correlate with low levels of damage in the mixed, background forest at Mt. Moosilauke. Care must be taken to avoid confusion between high-elevation climatically-stressed vegetation (normal krummholz forest) and damaged lower elevation forests, both of which have similar TM5/TM4 ratio values.

Torcoletti, Paul J.↗

NASA NTRS1990

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

Crane, Robert G.↗

NASA NTRS1990

Land use change detection based on multi-date imagery from different satellite sensor systems

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Stow, Douglas A.↗

NASA NTRS1990

Use of polarization methods in earth resources investigations

The use of polarized light image pairs to investigate earth resources and to make meteorological and oceanographic observations is discussed. The differences between the pairs are found to contain a significant amount of information on contrast, contrast boundaries, shadow, and such terrestrial features as rivers. Combinations of the polarization images were used as input to a principal component analysis, which provided some useful pictorial information not contained in any of the input images. Differencing the Fourier spectra of the polarization image pair showed that significant differences exist between the images in the population, azimuthal distribution, and spatial frequency distribution of contrast boundaries.

Duggin, M. J.↗

NASA NTRS1990

The relationship of extratropical outgoing longwave radiation to monthly geopotential teleconnection patterns

The relationship between low frequency variations in extratropical fields of outgoing longwave radiation (OLR) and geopotential teleconnection patterns as determined by rotated principal components analysis of the NMC 500-mb heights is investigated in the Northern Hemisphere. The monthly broadband OLR is obtained from the Nimbus-6 and Nimbus-7 Wide-Field-Of-View radiometer record. Each of the main 500-mb teleconnection patterns has a characteristic signal in the OLR field for the month in which the 500-mb pattern occurs. The OLR signals mark cloud and diabatic heating events that are associated with the teleconnection patterns. A demonstration is given of correlation between extratropical monthly OLR and geopotential height. Coupled with the expected tropospheric response to radiation on monthly time scale. This demonstration stresses the importance of the radiation simulation in model studies of the low frequency variability of atmospheric circulation. The extratropical OLR does not appear to be a useful predictor for the 500-mb teleconnection patterns on a monthly time scale.

Charlock, Thomas P.↗

NASA NTRS1991

Synergism between NOAA-AVHRR and Meteosat data for studying vegetation development in semi-arid West Africa

Rainfall estimates, based on cold cloud duration estimated from Meteosat data, are compared with vegetation development depicted by data of the normalized difference vegetation index (NDVI) from the NOAA AVHRR for part of the Sahel. Decadal data from the 1985 and 1986 growing seasons are examined to determine the synergism of the datasets for rangeland monitoring. There is a general correspondence between the two datasets with a marked lag between rainfall and NDVI of between 10 and 20 days. This time lag is particularly noticeable at the beginning of the rainy season and in the more northern areas where rainfall is the limiting factor for growth. Principal component analysis was used to examine deviations from the general relationship between rainfall and the NDVI. Areas of low NDVI values for a given input of rainfall were identified: at a regional scale, they give an indication o areas of low production potential and possible degradation of ecosystems.

Justice, C. O.↗

NASA NTRS1991

Psychophysical evaluation of three-dimensional auditory displays

Work during this reporting period included the completion of our research on the use of principal components analysis (PCA) to model the acoustical head related transfer functions (HRTFs) that are used to synthesize virtual sources for three dimensional auditory displays. In addition, a series of studies was initiated on the perceptual errors made by listeners when localizing free-field and virtual sources. Previous research has revealed that under certain conditions these perceptual errors, often called 'confusions' or 'reversals', are both large and frequent, thus seriously comprising the utility of a 3-D virtual auditory display. The long-range goal of our work in this area is to elucidate the sources of the confusions and to develop signal-processing strategies to reduce or eliminate them.

Wightman, Frederic L.↗

NASA NTRS1992

Modes of interannual variability in the stratosphere

During 1964-91, stratospheric temperature and circulation in Northern Hemisphere winter varied interannually on time scales from 2 to about 12 years. A substantial percentage of December-February interannual variance was correlated with the quasi-biennial oscillation (QBO). Additional monthly variance could be accounted for by quasi-decadal oscillation and QBO/low-frequency modulation. The QBO was the largest and most consistent of these signals, and its decadal modulation explains an apparent correlation with the solar cycle depending on the sign of the QBO - an interpretation supported by principal component analysis.

Dunkerton, Timothy J.↗

NASA NTRS1992

Landsat-TM identification of Amblyomma variegatum (Acari: Ixodidae) habitats in Guadeloupe

The feasibility of identifying specific habitats of the African bont tick, Amblyomma variegatum, from Landsat-TM images was investigated by comparing remotely sensed images of visible farms in Grande Terre (Guadeloupe) with field observations made in the same period of time (1986-1987). The different tick habitates could be separated using principal component analysis. The analysis clustered the sites by large and small variance of band values, and by vegetation and moisture indexes. It was found that herds in heterogeneous sites with large variances had more ticks than those in homogeneous or low variance sites. Within the heterogeneous sites, those with high vegetation and moisture indexes had more ticks than those with low values.

Hugh-Jones, M.↗

NASA NTRS1992

Regional climates in the GISS global circulation model - Synoptic-scale circulation

A major weakness of current general circulation models (GCMs) is their perceived inability to predict reliably the regional consequences of a global-scale change, and it is these regional-scale predictions that are necessary for studies of human-environmental response. For large areas of the extratropics, the local climate is controlled by the synoptic-scale atmospheric circulation, and it is the purpose of this paper to evaluate the synoptic-scale circulation of the Goddard Institute for Space Studies (GISS) GCM. A methodology for validating the daily synoptic circulation using Principal Component Analysis is described, and the methodology is then applied to the GCM simulation of sea level pressure over the continental United States (excluding Alaska). The analysis demonstrates that the GISS 4 x 5 deg GCM Model II effectively simulates the synoptic-scale atmospheric circulation over the United States. The modes of variance describing the atmospheric circulation of the model are comparable to those found in the observed data, and these modes explain similar amounts of variance in their respective datasets. The temporal behavior of these circulation modes in the synoptic time frame are also comparable.

Hewitson, B.↗

NASA NTRS1992

The effect of cloud type on earth's energy balance - Results for selected regions

International Satellite Cloud Climatology Project (ISCCP) C1 cloud information is compared with planetary albedo, outgoing longwave radiation (OLR), and net radiation measured at the top of the atmosphere by the Earth Radiation Budget Experiment (ERBE). Principal component analysis indicates that the day-to-day variations of the abundances of the 35 cloud types of the C1 data are correlated with each other, so that for many purposes the data set can be well represented by about five cloud types. Using stepwise multiple regression, the ISCCP C1 data can be used to predict the day-to-day variations of the energy balance measured by ERBE for 2.5-deg regions. Total fractional area coverage of cloudiness is a relatively poor predictor of radiation budget quantities. If the total fractional area coverage by clouds is divided into contributions from several distinct cloud types, the fractional coverages by these several cloud types will together form a much better prediction of radiation budget quantities than the single variable of total fractional-area cloud coverage. The regression equations can be used to estimate the net effect of clouds on the radiation balance and the contributions from particular types of clouds to albedo, OLR, and net radiation.

Ockert-Bell, Maureen E.↗

NASA NTRS1993

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↗

NASA NTRS1993

Optimal band selection for dimensionality reduction of hyperspectral imagery

Hyperspectral images have many bands requiring significant computational power for machine interpretation. During image pre-processing, regions of interest that warrant full examination need to be identified quickly. One technique for speeding up the processing is to use only a small subset of bands to determine the 'interesting' regions. The problem addressed here is how to determine the fewest bands required to achieve a specified performance goal for pixel classification. The band selection problem has been addressed previously Chen et al., Ghassemian et al., Henderson et al., and Kim et al.. Some popular techniques for reducing the dimensionality of a feature space, such as principal components analysis, reduce dimensionality by computing new features that are linear combinations of the original features. However, such approaches require measuring and processing all the available bands before the dimensionality is reduced. Our approach, adapted from previous multidimensional signal analysis research, is simpler and achieves dimensionality reduction by selecting bands. Feature selection algorithms are used to determine which combination of bands has the lowest probability of pixel misclassification. Two elements required by this approach are a choice of objective function and a choice of search strategy.

Stearns, Stephen D.↗