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At least 865 records · Page 48

The 1950 sulfur flow of Mauna Loa: Considerations for Io

Some of the geological relationships observed in the Mauna Loa sulfur flow may apply in considering volcanic processes on Io. Given the presence of sulfur/sulfur compounds in the eruption plumes and on the surface of Io, it is likely that extensive secondary deposits of sulfur exist, some of which may be of fumarolic origin and analogous to the Mauna Loa deposit. Given the likelihood of silicate volcanism of Io based on the inferred material properties of some flows, and the attendant high temperatures for silicate volcanism, it is likely that the secondary surface deposits of sulfur would have been mobilized without being heated to the high viscosity stage. Mobilized sulfur flows on Io may flow long distances as a result of: (1) low viscosities in the melting range; (2) sustained effusion resulting from continued heating source area; (3) continued remobilization within the flow as a consequence of surges from the source; and (4) extension via lava tubes, or similar conduits through which there is little heat loss. Sulfur flows may form a relatively thin veneer over silicate flows and other surface units, given their fluidity and low mobilization temperature. Active splashing and splattering may spread sulfur over a wider area contributing the bright blooms observed in association with some Ionian flows.

Greeley, R.↗

Evaluation of entropy and JM-distance criterions as features selection methods using spectral and spatial features derived from LANDSAT images

A study area near Ribeirao Preto in Sao Paulo state was selected, with predominance in sugar cane. Eight features were extracted from the 4 original bands of LANDSAT image, using low-pass and high-pass filtering to obtain spatial features. There were 5 training sites in order to acquire the necessary parameters. Two groups of four channels were selected from 12 channels using JM-distance and entropy criterions. The number of selected channels was defined by physical restrictions of the image analyzer and computacional costs. The evaluation was performed by extracting the confusion matrix for training and tests areas, with a maximum likelihood classifier, and by defining performance indexes based on those matrixes for each group of channels. Results show that in spatial features and supervised classification, the entropy criterion is better in the sense that allows a more accurate and generalized definition of class signature. On the other hand, JM-distance criterion strongly reduces the misclassification within training areas.

Parada, N. D. J.↗

Forest inventory using multistage sampling with probability proportional to size

A multistage sampling technique, with probability proportional to size, for forest volume inventory using remote sensing data is developed and evaluated. The study area is located in the Southeastern Brazil. The LANDSAT 4 digital data of the study area are used in the first stage for automatic classification of reforested areas. Four classes of pine and eucalypt with different tree volumes are classified utilizing a maximum likelihood classification algorithm. Color infrared aerial photographs are utilized in the second stage of sampling. In the third state (ground level) the time volume of each class is determined. The total time volume of each class is expanded through a statistical procedure taking into account all the three stages of sampling. This procedure results in an accurate time volume estimate with a smaller number of aerial photographs and reduced time in field work.

Parada, N. D. J.↗

Spectral moment estimation in MST radars

Signal processing techniques used in Mesosphere-Stratosphere-Troposphere (MST) radars are reviewed. Techniques which produce good estimates of the total power, frequency shift, and spectral width of the radar power spectra are considered. Non-linear curve fitting, autocovariance, autocorrelation, covariance, and maximum likelihood estimators are discussed.

Woodman, R. F.↗

Scanning wind-vector scatterometers with two pencil beams

A scanning pencil-beam scatterometer for ocean windvector determination has potential advantages over the fan-beam systems used and proposed heretofore. The pencil beam permits use of lower transmitter power, and at the same time allows concurrent use of the reflector by a radiometer to correct for atmospheric attenuation and other radiometers for other purposes. The use of dual beams based on the same scanning reflector permits four looks at each cell on the surface, thereby improving accuracy and allowing alias removal. Simulation results for a spaceborne dual-beam scanning scatterometer with a 1-watt radiated power at an orbital altitude of 900 km is described. Two novel algorithms for removing the aliases in the windvector are described, in addition to an adaptation of the conventional maximum likelihood algorithm. The new algorithms are more effective at alias removal than the conventional one. Measurement errors for the wind speed, assuming perfect alias removal, were found to be less than 10%.

Kirimoto, T.↗

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Logan, T. L.↗

Impact of Thematic Mapper Sensor Characteristics on Classification Accuracy

A three factor (spectral, spatial, and radiometric resolution), two level (TM and MSS) analysis of variance (ANOVA) approach allowed evaluation of the effects of each factor individually and in all possible combinations. Digital classification accuracy was used as the figure of merit. Nine study sites in Washington, D.C. each of approximately 256 x 256 TM pixels, were randomly selected from the full scene for analysis. These results strongly suggest that the quantization level improvements and the addition of new spectral bands in the visible and middle IR regions (both afforded by the TM sensor design) can result in improved capabilities to accurately delineate land cover categories using a per point Gaussian maximum likelihood classifier. On the other hand, results indicate that the increase in spatial resolution to 30m does not significantly enhance classification accuracy. The spatial result points to an inherent limitation of a per point classifier and to the need to improve data analysis techniques to handle high spatial resolution data.

Williams, D. L.↗

Use of multi-frequency, multi-polarization, multi-angle airborne radars for class discrimination in a southern temperature forest

The utility of radar scatterometers for discrimination and characterization of natural vegetation was investigated. Backscatter measurements were acquired with airborne multi-frequency, multi-polarization, multi-angle radar scatterometers over a test site in a southern temperate forest. Separability between ground cover classes was studied using a two-class separability measure. Very good separability is achieved between most classes. Longer wavelength is useful in separating trees from non-tree classes, while shorter wavelength and cross polarization are helpful for discrimination among tree classes. Using the maximum likelihood classifier, 50% overall classification accuracy is achieved using a single, short-wavelength scatterometer channel. Addition of multiple incidence angles and another radar band improves classification accuracy by 20% and 50%, respectively, over the single channel accuracy. Incorporation of a third radar band seems redundant for vegetation classification. Vertical transmit polarization is critically important for all classes.

Mehta, N. C.↗

Statistical severe storm nowcasting comparison of VAS and Rawinsonde soundings

The statistical severe storm nowcasting technique using upper air soundings (VAS or radiosonde) is translated to the IBM McIDAS system. The severe storm information content of Visible infrared spin scan radiometer Atmospheric Sounder (VAS) and rawinsonde sounding data is compared. The contours of the likelihood of severe storms based only upon upper air VAS and rawinsonde data are shown, as well as the outlook based upon surface data, radar, operational computer models, and other data sources.

Keller, D. L.↗

Preliminary evaluation of thematic mapper sensor characteristics relative to land cover/land use discrimination

Preliminary experimental results of airborne thematic mapper (TM) data taken to quantify the effect of three major TM sensor parameters, spectral, spatial, and radiometric resolution, six months after launch of Landsat-4 are reported. The flight took place on Nov. 2, 1982 over Washington, D.C., and data gathered were compared with ground reference data from color airborne photography on a 1:40,000 scale. Analyses proceeded by deleting one band from each of four data sets, thus making the data equivalent to MSS data. Attention was directed to land cover/use classes in a quick-look format. A per-pixel maximum likelihood scheme was found to increase the recognition and dicrimination categorization capabilities. Finer spatial resolution, however, impeded classification due to increased within-class variability of the field-center pixels, which also incresed class overlap in the spectral data base. Improved data analyses techniques are therefore needed to exploit the available higher spatial resolution of the TM.

Williams, D. L.↗

A note on the composition and structure of interstellar grains

The plausibility of relatively pure diatomic oxide crystals forming in the expanding atmospheres of cool stars is commented on, and the likelihood of SiO grains condensing is discussed on the basis of laboratory nucleation experiments. Results of annealing experiments are used to consider the further evolution of silicon oxide and silicate grains. The evidence shows that SiO solids form only when SiO condenses directly onto surfaces, and that the probability of pure crystalline SiO grains forming is rather small.

Nuth, J. A.↗

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

Batista, G. T.↗

An evaluation of thematic mapper simulator data for mapping forest cover

Computer-aided analysis techniques applied to Thematic Mapper Simulator (TMS) data were evaluated for the purpose of mapping forest cover types. Classification results obtained using a supervised set of training statistics and various combinations of three and four channel subsets of the seven available TMS channels are compared for the L2 (Minimum Euclidean Distance), GML (Gaussian Maximum Likelihood), and SECHO (Supervised Extraction and Classification of Homogeneous Objects) classification algorithms. SECHO performed significantly better than either of the two per-point classifiers for the untransformed data. Overall classification results of the Karhunen-Loeve transformation increased for the L2 algorithm, but decreased for both the GML and SECHO algorithms.

Dean, M. E.↗

Estimating time and time-lag in time-of-flight velocimetry

Estimating time and time-lag in time-of-flight velocimeters is investigated. Statistics of a filtered Poisson point process is given. A Maximum Likelihood Estimator is compared with suboptimum estimators in terms of robustness. For a dominating background combined spatial and temporal processing can improve the robustness compared with purely temporal processing. Schemes for the spatial filters are given.

Lading, L.↗

Baseband processor development for the Advanced Communications Satellite Program

An onboard-baseband-processor concept for a satellite-switched time-division-multiple-access (SS-TDMA) communication system was developed for NASA Lewis Research Center. The baseband processor routes and controls traffic on an individual message basis while providing significant advantages in improved link margins and system flexibility. Key technology developments required to prove the flight readiness of the baseband-processor design are being verified in a baseband-processor proof-of-concept model. These technology developments include serial MSK modems, Clos-type baseband routing switch, a single-chip CMOS maximum-likelihood convolutional decoder, and custom LSL implementation of high-speed, low-power ECL building blocks.

Moat, D.↗

The filaments of NGC 1275 - A collision between a galaxy and an accretion flow?

Morphological evidence is presented (in the form of 3-A-bandpass Fabry-Perot images made with a CCD camera) that the two bright emission-line systems seen toward the galaxy NGC 1275 arise from a high-velocity impact of a foreground galaxy upon the accretion flow of gas cooling in the center of the Perseus cluster. The uniquely high optical-line luminosity of NGC 1275, in comparison with other central galaxies in clusters observed to have cooling flows, may be explained by energy deposited during the collision. Using additional information from 21-cm and extinction measurements, a rough model of the interaction is developed. Problems remain with this model - such as the likelihood of a gas-rich system penetrating to the cluster center. The kinematic structure of the optically emitting gas shows additional complex structure near the nucleus of NGC 1275.

Kaaret, P.↗

An improved push-pull voltage fed converter using a tapped output-filter inductor

A new concept of using a tapped output-filter inductor and an auxiliary commutating diode to reduce the likelihood of transformer core saturation in a push-pull, voltage-fed converter is presented. The linearized circuit model and transfer functions are derived with a hybrid approach using both state-space and circuit averaging. Operation of the new converter - including parasitic effects - is discussed, and a design equation for inductor tap ratio is established. It is predicted and experimentally confirmed that the new converter has more symmetrical transformer core operation, and the potential exits for lower transistor turnon current and reduced transistor voltage stress. These benefits reduce switching loss and enhance transistor reliability.

Wester, G. W.↗

Identification of multivariable high performance turbofan engine dynamics from closed loop data

The multivariable instrumental variable/approximate maximum likelihood (IV/AML) method of recursive time-series analysis is used to identify the multivariable (four inputs-three outputs) dynamics of the Pratt and Whitney F100 engine. A detailed nonlinear engine simulation is used to determine linear engine model structures and parameters at an operating point using open loop data. Also, the IV/AML method is used in a direct identification made to identify models from actual closed loop engine test data. Models identified from simulated and test data are compared to determine a final model structure and parameterization that can predict engine response for a wide class of inputs. The ability of the IV/AML algorithm to identify useful dynamic models from engine test data is assessed. Previously announced in STAR as N82-20339

Merrill, W.↗