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At least 73 records · Page 4

Spectral constraints on models of gas in clusters of galaxies

The HEAO 1A2 spectra of clusters of galaxies are used to determine the temperature profile which characterizes the X-ray emitting gas. Strong evidence of nonisothermality is found for the Coma, A85, and A1795 clusters. Properties of the cluster potential which binds the gas are calculated for a range of model parameters. The typical binding mass, if the gas is adiabatic, is 2-4E14 solar masses and is quite centrally concentrated. In addition, the Fe abundance in Coma is .26 + or - .06 solar, less than the typical value (.5) found for rich clusters. The results for the gas in Coma may imply a physical description of the cluster which is quite different from what was previously believed.

Henriksen, M. J.↗

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95 percent), and progress is being made towards identifying the mapped spectral classes.

Messmore, J.↗

Joint Classification and Data Compression of multidimensional information sources - Application to ERTS

This paper describes a concept of Joint Classification and Data Compression of multidimensional information sources in the context of applications to Earth Resources Technology Satellites. The concept is used to define an Information Extraction System intended to remove data redundancy early in the sensor to user link in both classification and film interpretation applications. The approach uses cascaded partially supervised clustering to extract spectral intensity features from spatially local sources. Data compression is then used to efficiently represent spatial features within the spectral intensity feature map.

Hilbert, E. E.↗

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95%), and progress is being made towards identifying the mapped spectral classes.

Messmore, J.↗

Land-cover classification of California using mosaicking and high-speed processing

A land cover classification of Landsat MSS data has been made for the entire state of California. Digital mosaicking of 32 Landsat scenes with registered digital elevation, slope, and aspect was prepared. Stratified unsupervised clustering generated the spectral classes which were identified into 16 categories, mostly forest types, using U-2 CIR photos. A verification using 81 primary sample units resulted in a forest/nonforest accuracy of 80.2% and a commercial conifer and hardwood accuracy of 75.1%. The results are now being used in many projects throughout the state.

Peterson, D. L.↗

Procedure 1 and forestland classification using Landsat data

Procedure 1 (P-1) was developed for the Large Area Crop Inventory Experiment (LACIE) and has been used extensively to develop land-use classification of agricultural areas. The P-1 approach requires that pixels (also called dots) of known identity must be located in the study scene. The entire area is clustered and the spectral classes formed are identified using the dots. The analyst need only locate and identify the dots. The rest of the work is done by the computer. The objective of the reported study was to evaluate the effectiveness of P-1's automated approach in a complex forest-land situation. The study site was located in the eastern half of the San Juan National Forest in southwestern Colorado. The study showed that P-1 performed as well as the Multicluster Blocks approach on the rugged study area.

Nelson, R. F.↗

Analysis of the Tanana River Basin using LANDSAT data

Digital image classification techniques were used to classify land cover/resource information in the Tanana River Basin of Alaska. Portions of four scenes of LANDSAT digital data were analyzed using computer systems at Ames Research Center in an unsupervised approach to derive cluster statistics. The spectral classes were identified using the IDIMS display and color infrared photography. Classification errors were corrected using stratification procedures. The classification scheme resulted in the following eleven categories; sedimented/shallow water, clear/deep water, coniferous forest, mixed forest, deciduous forest, shrub and grass, bog, alpine tundra, barrens, snow and ice, and cultural features. Color coded maps and acreage summaries of the major land cover categories were generated for selected USGS quadrangles (1:250,000) which lie within the drainage basin. The project was completed within six months.

Morrissey, L. A.↗

The Einstein soft X-ray survey of the Pleiades

The results of a 0.1-4.5-keV X-ray survey of a 2 x 2-deg area centered on the Pleiades open cluster, performed using the imaging proportional counter and high-resolution imager of the Einstein Observatory on four days in 1980-1981, are presented in extensive tables, graphs, maps, histograms, and finding charts and characterized. A total of 61 sources are detected, and 44 of these are identified with cluster members of spectral types B-M. Findings discussed include Lx/Lbol of 10 the -7th for early-type stars; F-star mean Lx like that of F stars in the Hyades and in the field (denying time evolution of Lx); mean G-star Lx = 3.7 x 10 to the 29th erg/sec; G-star activity decay more gradual than 1/sq rt t, with sharp fall for t greater than 1 Gyr; and no evidence for X-ray-emissivity/rotational-velocity correlation in a homogeneous sample of K dwarfs or a sample of K and M stars with established V sin i data.

Caillault, J.-P.↗

Ultraviolet and X-ray observations of NGC 2264

An IUE satellite search is reported for chromospheric emission in the UV spectra of the brightest pre-main sequence stars the open cluster NGC 2264. Einstein X-ray observations to search for variability of the bright O7 V ((f)) star S Mon = W131, which may be the most massive member of the cluster, are also reported. Fifteen cluster members of spectral type B-K, ranging in age from a million to ten million yr, were observed in the ultraviolet. The only star exhibiting chromospheric emission is W79, a faint, heavily veiled T Tauri star that lies below the main sequence of NGC 2264. The observations are consistent with the generally accepted idea that chromospheric activity of late-type stars subsides with age.

Simon, T.↗

An absorption event in 4U/MXB 1820 - 30

A search of the HEAO A-2 low-energy detector data base for absorption-like events from X-ray bulge sources and bursters has been performed. Only one event was found, from the burster 4U 1820 - 30, which is located in the globular cluster NGC 6624. Spectral analysis indicates an increase in equivalent column density accompanied by a decrease in the overall intensity. This is similar to previous spectral results for 4U 1915 - 05 and MXB 1659 - 29. The low-mass binary model is discussed in the context of these new observations.

Cominsky, L.↗

Rotation and kinematics of the premain-sequence stars in Taurus-Auriga with Ca II emission

Radial velocities and v sin i values for the stars in the Taurus-Auriga region that were found to have strong Ca II H and K emission by Herbig, Vrba, and Rydgren 'HVR', (1986) are reported. Most of the velocities are determined to better than 2 km/s precision. The kinematic properties of the Ca II emission stars with strong Li are found to be indistinguishable from conventional T Tauris in Taurus-Auriga, contrary to HVR. These Li-rich stars also rotate like T Tauris. Most of the stars that lack Li are probable or possible members of the Hyades, in the foreground, and are among the brightest and most active stars in that cluster for their spectral types. It is suggested following Jones and Herbig (1979), that the apparent absence of low-mass stars older than 10 Myr in Taurus-Auriga is real, and is due to the finite lifetime of the cloud.

Hartmann, Lee W.↗

Applications of wavelet-based compression to multidimensional Earth science data

A data compression algorithm involving vector quantization (VQ) and the discrete wavelet transform (DWT) is applied to two different types of multidimensional digital earth-science data. The algorithms (WVQ) is optimized for each particular application through an optimization procedure that assigns VQ parameters to the wavelet transform subbands subject to constraints on compression ratio and encoding complexity. Preliminary results of compressing global ocean model data generated on a Thinking Machines CM-200 supercomputer are presented. The WVQ scheme is used in both a predictive and nonpredictive mode. Parameters generated by the optimization algorithm are reported, as are signal-to-noise (SNR) measurements of actual quantized data. The problem of extrapolating hydrodynamic variables across the continental landmasses in order to compute the DWT on a rectangular grid is discussed. Results are also presented for compressing Landsat TM 7-band data using the WVQ scheme. The formulation of the optimization problem is presented along with SNR measurements of actual quantized data. Postprocessing applications are considered in which the seven spectral bands are clustered into 256 clusters using a k-means algorithm and analyzed using the Los Alamos multispectral data analysis program, SPECTRUM, both before and after being compressed using the WVQ program.

Bradley, Jonathan N.↗

Investigation of correlation classification techniques

A two-step classification algorithm for processing multispectral scanner data was developed and tested. The first step is a single pass clustering algorithm that assigns each pixel, based on its spectral signature, to a particular cluster. The output of that step is a cluster tape in which a single integer is associated with each pixel. The cluster tape is used as the input to the second step, where ground truth information is used to classify each cluster using an iterative method of potentials. Once the clusters have been assigned to classes the cluster tape is read pixel-by-pixel and an output tape is produced in which each pixel is assigned to its proper class. In addition to the digital classification programs, a method of using correlation clustering to process multispectral scanner data in real time by means of an interactive color video display is also described.

Haskell, R. E.↗

Mg II Spectral Atlas and Flux Catalog for Late-Type Stars in the Hyades Cluster

In the course of a long-running IUE Guest Observer program, UV spectral images were obtained for more than 60 late-type members of the Hyades Cluster in order to investigate their chromospheric emissions. The emission line fluxes extracted from those observations were used to study the dependence of stellar dynamo activity upon age and rotation (IUE Observations of Rapidly Rotating Low-Mass Stars in Young Clusters: The Relation between Chromospheric Activity and Rotation). However, the details of those measurements, including a tabulation of the line fluxes, were never published. The purpose of the investigation summarized here was to extract all of the existing Hyades long-wavelength Mg II spectra in the IUE public archives in order to survey UV chromospheric emission in the cluster, thereby providing a consistent dataset for statistical and correlative studies of the relationship between stellar dynamo activity, rotation, and age over a broad range in mass.

Simon, Theodore↗

Markov Chain Monte Carlo Joint Analysis of Chandra X-Ray Imaging Spectroscopy and Sunyaev-Zel'dovich Effect Data

X-ray and Sunyaev-Zel'dovich effect data can be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from Chandra, which provides both spatial and spectral information, and Sunyaev-Zel'dovich effect data were obtained from the BIMA and Owens Valley Radio Observatory (OVRO) arrays. We introduce a Markov Chain Monte Carlo procedure for the joint analysis of X-ray and Sunyaev- Zel'dovich effect data. The advantages of this method are the high computational efficiency and the ability to measure simultaneously the probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and also for derivative quantities such as the distance to the cluster. We demonstrate this technique by applying it to the Chandra X-ray data and the OVRO radio data for the galaxy cluster A611. Comparisons with traditional likelihood ratio methods reveal the robustness of the method. This method will be used in follow-up paper to determine the distances to a large sample of galaxy cluster.

Bonamente, Massimillano↗

Determination of Cluster Distances from Chandra Imaging Spectroscopy and Sunyaev-Zeldovich Effect Measurements: Analysis Methods and Initial Results - I

X-ray and Sunyaev-Zeldovich Effect data ca,n be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from the Chandra Observatory, which provides both spatial and spectral information, and interferometric radio measurements of the Sunyam-Zeldovich Effect are available from the BIMA and 0VR.O arrays. We introduce a Monte Carlo Markov chain procedure for the joint analysis of X-ray and Sunyaev-Zeldovich Effect data. The advantages of this method are the high computational efficiency and the ability to measure the full probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and the cluster distance. We apply this technique to the Chandra X-ray data and the OVRO radio data for the galaxy cluster Abell 611. Comparisons with traditional likelihood-ratio methods reveal the robustness of the method. This method will be used in a follow-up paper to determine the distance of a large sample of galaxy clusters for which high-resolution Chandra X-ray and BIMA/OVRO radio data are available.

Bonamente, Massimiliano↗

OSO-8 X-ray spectra of clusters of galaxies. 1. Observations of twenty clusters: Physical correlations

OSO-8 X-ray spectra from 2 to 20 keV were analyzed for 26 clusters of galaxies. Temperature, emission integrals, iron abundances, and low energy absorption measurements are given. Eight clusters have positive iron emission line detections at the 90% confidence level, and all twenty cluster spectra are consistent with Fe/H=0.000014 by number with the possible exception of Virgo. Physical correlations between X-ray spectral parameters and other cluster properties are examined. It is found that: (1) the X-ray temperature is approximately proportional to the square of the velocity dispersion of the galaxies; (2) the emission integral and therefore the bolometric X-ray luminosity is a strong function of the X-ray temperature; (3) the X-ray temperature and emission integral are better correlated with cluster central galaxy density than with richness; (4) temperature and emission integral are separately correlated with Rood-Sastry type; and (5) the fraction of galaxies which are spirals is correlated with the observed ram pressure in the cluster core.

Mushotzky, R. F.↗

Measuring the Redshift Dependence of The Cosmic Microwave Background Monopole Temperature With Planck Data

We study the capability of Planck data to constrain deviations of the cosmic microwave background (CMB) blackbody temperature from adiabatic evolution using the thermal Sunyaev-Zeldovich anisotropy induced by clusters of galaxies. We consider two types of data sets depending on how the cosmological signal is removed: using a CMB template or using the 217 GHz map. We apply two different statistical estimators, based on the ratio of temperature anisotropies at two different frequencies and on a fit to the spectral variation of the cluster signal with frequency. The ratio method is biased if CMB residuals with amplitude approximately 1 microK or larger are present in the data, while residuals are not so critical for the fit method. To test for systematics, we construct a template from clusters drawn from a hydro-simulation included in the pre-launch Planck Sky Model. We demonstrate that, using a proprietary catalog of X-ray-selected clusters with measured redshifts, electron densities, and X-ray temperatures, we can constrain deviations of adiabatic evolution, measured by the parameter α in the redshift scaling T (z) = T0(1 + z)(sup 1−alpha), with an accuracy of sigma(sub alpha) = 0.011 in the most optimal case and with sigma alpha = 0.018 for a less optimal case. These results represent a factor of 2-3 improvement over similar measurements carried out using quasar spectral lines and a factor 6-20 with respect to earlier results using smaller cluster samples.

cosmic background radiation↗