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At least 1,675 records · Page 93

Validation and Improvement of SRTM Performance over Rugged Terrain

We have previously reported work related to basic technique development in phase unwrapping and generation of digital elevation models (DEM). In the final year of this work we have applied our technique work to the improvement of DEM's produced by SRTM. In particular, we have developed a rigorous mathematical algorithm and means to fill in missing data over rough terrain from other data sets. We illustrate this method by using a higher resolution, but globally less accurate, DEM produced by the TOPSAR airborne instrument over the Galapagos Islands to augment the SRTM data set in this area, We combine this data set with SRTM to use each set to fill in holes left over by the other imaging system. The infilling is done by first interpolating each data set using a prediction error filter that reproduces the same statistical characterization as exhibited by the entire data set within the interpolated region. After this procedure is implemented on each data set, the two are combined on a point by point basis with weights that reflect the accuracy of each data point in its original image. In areas that are better covered by SRTM, TOPSAR data are weighted down but still retain TOPSAR statistics. The reverse is true for regions better covered by TOPSAR. The resulting DEM passes statistical tests and appears quite feasible to the eye, but as this DEM is the best available for the region we cannot fully veri@ its accuracy. Spot checks with GPS points show that locally the technique results in a more comprehensive and accurate map than either data set alone.

Zebker, Howard A.↗

Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

Clark, J.↗

Direct cross-section measurement of the weak r -process Sr 88 ( α , n ) Zr 91 reaction in ν -driven winds of core-collapse supernovae

About half of the heavy elements beyond iron are known to be produced by the rapid neutron capture process, known as the r process. However, the astrophysical site producing the r process is still uncertain. Chemical abundances observed in several cosmic sites indicate that different mechanisms should be at play. For instance, the abundances around silver measured in a subset of metal-poor stars indicate the presence of a weak r process. This process may be active in neutrino-driven winds of core collapse supernovae where (α,n) reactions dominate the synthesis of Ζ ≈ 40 elements in the expelled materials. Scarcely measured, the rates of (α,n) reactions are determined from statistical Hauser-Feshbach calculations with α-optical-model potentials, which are still poorly constrained. Further, the uncertainties of the (α,n) reaction rates therefore make a significant contribution to the uncertainties of the abundances determined from stellar modeling. In this work, the 88 Sr (α,n)⁢ 91 Zr reaction which impacts the weak r-process abundances has been probed at astrophysics energy for the first time; directly measuring the total cross sections at astrophysical energies of 8.37–13.09 MeV in the center of mass (3.8–7.5 GK). Two measurements were performed at ATLAS with the electrically segmented ionization chamber MUSIC, in inverse kinematics, while following the active target technique. The cross sections of this α-induced reaction on 88 Sr, located at the shell closure N = 50, have been found to be lower than expected, by a factor of 3, despite recent statistical calculations validated by measurements on neighboring nuclei. This result encourages more experimental investigations of (α,n) reactions, at Ν = 50 and towards the neutron-rich side, to further test the predictive power and reliability of such calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Coherent Random Lasing in Subwavelength Quasi‐2D Perovskites

Abstract Quasi‐2D lead halide perovskites have garnered increasing interest as lasing gain media. Relatively simple fabrication, high refractive index, and unique quantum well structure encourage their use in traditional cavity lasers and cavity‐free systems called random lasers (RLs). Despite tremendous advances reported thus far, coherent random lasing in quasi‐2D perovskite subwavelength films has not been reported. Consequently, coherent optical feedback mechanisms in quasi‐2D perovskite systems are still unexplored. Here, this work reports the observation of coherent random lasing in subwavelength quasi‐2D perovskite films. Statistical analysis of spectral measurements reveals Lévy‐like intensity fluctuations, replica symmetry breaking confirms random lasing, and the coherent modes are studied with spectral and spatial correlation techniques. The observed coherent lasing modes are found to be extended states that arise from the random crystal grain structure during fabrication and span the entire pump volume. These modes out‐compete diffusive lasing due to their coherence.

47 OTHER INSTRUMENTATION↗

Chemomechanical weakening of muscovite quantified with in situ liquid nanoindentation

Abstract Chemomechanical weakening of layered phyllosilicate muscovite mica was studied as a function of chemical environment via in situ liquid-nanoindentation under four conditions (dry, deionized water, and two NaCl solutions of different pH). While traditional indentation analyses of layered materials with extreme mechanical anisotropy have been limited due to displacement bursts (pop-ins), here the bursts were used as proxies for delamination, fracture, and spalling events. Since displacement bursts during an indent represent a stochastic process, 120 indents were conducted for each condition to generate statistically significant amounts of data. In total, over 9000 bursts were assessed using a load–displacement threshold criterion, classifying this as a high-throughput nanoscale fracture technique. For each burst, initiation load, initiation displacement, plastic zone volume at initiation, and energy dissipation were analyzed. A power-law relationship between the burst load and burst energy was noted which separated the bursts into two continuous distributions: (1) bursts due only to the mechanics of the indent and (2) bursts due to both the mechanics of the indent and the environment. By using a cumulative probability distribution, it was found that the NaCl solutions decreased the minimum plastic zone volume necessary to initiate a displacement burst by an order of magnitude relative to the dry condition. Finally, the underlying mechanisms explaining the trends in initiation volume as a function of environment were discussed, with a focus on the chemomechanical degradation processes via chemical attack and cation exchange.

36 MATERIALS SCIENCE↗

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗

The first Hubble diagram and cosmological constraints using superluminous supernovae

In this work, we present the first Hubble diagram of superluminous supernovae (SLSNe) out to a redshift of two, together with constraints on the matter density, Ω M , and the dark energy equation-of-state parameter, w(≡p/ρ). We build a sample of 20 cosmologically useful SLSNe I based on light curve and spectroscopy quality cuts. We confirm the robustness of the peak–decline SLSN I standardization relation with a larger data set and improved fitting techniques than previous works. We then solve the SLSN model based on the above standardization via minimization of the χ2 computed from a covariance matrix that includes statistical and systematic uncertainties. For a spatially flat Λ cold dark matter (ΛCDM) cosmological model, we find $\Omega _{\rm M}=0.38^{+0.24}_{-0.19}$, with an rms of 0.27 mag for the residuals of the distance moduli. For a w 0 w a CDM cosmological model, the addition of SLSNe I to a ‘baseline’ measurement consisting of Planck temperature together with Type Ia supernovae, results in a small improvement in the constraints of w 0 and wa of 4 per cent. We present simulations of future surveys with 868 and 492 SLSNe I (depending on the configuration used) and show that such a sample can deliver cosmological constraints in a flat ΛCDM model with the same precision (considering only statistical uncertainties) as current surveys that use Type Ia supernovae, while providing a factor of 2–3 improvement in the precision of the constraints on the time variation of dark energy, w 0 and w a . This paper represents the proof of concept for superluminous supernova cosmology, and demonstrates they can provide an independent test of cosmology in the high-redshift (z > 1) universe.

79 ASTRONOMY AND ASTROPHYSICS↗

Developing and applying quantifiable metrics for diagnostic and experiment design on Z

This project applies methods in Bayesian inference and modern statistical methods to quantify the value of new experimental data, in the form of new or modified diagnostic configurations and/or experiment designs. We demonstrate experiment design methods that can be used to identify the highest priority diagnostic improvements or experimental data to obtain in order to reduce uncertainties on critical inferred experimental quantities and select the best course of action to distinguish between competing physical models. Bayesian statistics and information theory provide the foundation for developing the necessary metrics, using two high impact experimental platforms on Z as exemplars to develop and illustrate the technique. We emphasize that the general methodology is extensible to new diagnostics (provided synthetic models are available), as well as additional platforms. We also discuss initial scoping of additional applications that began development in the last year of this LDRD.

97 MATHEMATICS AND COMPUTING↗

Remote measurement of ocean temperature from depolarization in Raman scattering

Ocean temperatures may be mapped in three dimensions from an aircraft down to depths of 2 to 4 attenuation lengths by monitoring Raman radiation backscattered from a laser beam. This paper describes laboratory experiments on the temperature dependence of Raman spectra of saline solutions and calculations of the expected performance of a field system. The Raman technique is of greatest potential utility in coastal and estuarine waters where gradients are relatively high. It is estimated that seawater temperature may be measured to a statistical precision of 0.5 C at depths to four attenuation lengths in two meter water, using one Joule of transmitted laser energy.

Chang, C. H.↗

Areal extent of snow estimation in the Northern Sierra Nevada Mountains using LANDSAT-1 imagery

Quantification of the surface area of snow covering watersheds is believed to be a useful parameter in estimating snow water content for inclusion in water runoff prediction equations. An operational manual interpretation technique which allows fast and accurate estimates to be made of the areal extent of snow parameter using LANDSAT-1 imagery is documented. The analysis procedures, the statistical results, and the associated costs of this research are presented.

Katibah, E. F.↗

Processing laser velocimeter high-speed burst counter data

The statistical calculations of the mean and potential bias errors are considered with respect to their applicability to the randomly sampled velocity data obtained from a laser velocimeter. Techniques for displaying the resulting data in the form of arrow plots, flow streamline plots, and contour maps are also discussed. A description is presented of the operation of a new hardware interface between the signal processing electronics and the computer. The interface has been constructed to make it possible to use recently developed data processing techniques for obtaining turbulent power spectra from laser velocimeter data. Additional capabilities which were built into the interface allow the measurement of the velocity vector for each particle passing through the laser velocimeter sample window. By processing the data with extended versions of the turbulent power spectra techniques, cross spectra, interactions between velocity magnitude fluctuations, and flow angle fluctuations may be investigated.

Meyers, J. F.↗

Remote sensing of sea state by analysis of backscattered microwave phase fluctuations

The relative phase of a normally incident microwave signal scattered off the sea surface is a random function of space and time. The statistics of these random phase fluctuations contain information about the wave-height statistics. This study demonstrates that the wave-height spectra can be deduced directly in terms of the spectra of the phase fluctuations without recourse to inversion techniques even when surface roughness exceeds many wavelengths of the incident signal. In the particular case of a nadir-directed satellite-mounted microwave source operating in the backscatter mode, the wave-height and phase spatial spectra are proportional with a constant proportionality of (2k0) squared, where k0 is the wavenumber of the scattered signal.

Clifford, S. F.↗

Model of aircraft passenger acceptance

A technique developed to evaluate the passenger response to a transportation system environment is described. Reactions to motion, noise, temperature, seating, ventilation, sudden jolts and descents are modeled. Statistics are presented for the age, sex, occupation, and income distributions of the candidates analyzed. Values are noted for the relative importance of system variables such as time savings, on-time arrival, convenience, comfort, safety, the ability to read and write, and onboard services.

Jacobson, I. D.↗

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.↗

Vegetation monitoring and classification using NOAA/AVHRR satellite data

A vegetation gradient model, based on a new surface hydrologic index and NOAA/AVHRR meteorological satellite data, has been analyzed along a 1300 km east-west transect across the state of Texas. The model was developed to test the potential usefulness of such low-resolution data for vegetation stratification and monitoring. Normalized Difference values (ratio of AVHRR bands 1 and 2, considered to be an index of greenness) were determined and evaluated against climatological and vegetation characteristics at 50 sample locations (regular intervals of 0.25 deg longitude) along the transect on five days in 1980. Statistical treatment of the data indicate that a multivariate model incorporating satellite-measured spectral greenness values and a surface hydrologic factor offer promise as a new technique for regional-scale vegetation stratification and monitoring.

Greegor, D. H., Jr.↗

Remote sensing for urban planning

Utility companies are challenged to provide services to a highly dynamic customer base. With factory closures and shifts in employment becoming a routine occurrence, the utility industry must develop new techniques to maintain records and plan for expected growth. BellSouth Telecommunications, the largest of the Bell telephone companies, currently serves over 13 million residences and 2 million commercial customers. Tracking the movement of customers and scheduling the delivery of service are major tasks for BellSouth that require intensive manpower and sophisticated information management techniques. Through NASA's Commercial Remote Sensing Program Office, BellSouth is investigating the utility of remote sensing and geographic information system techniques to forecast residential development. This paper highlights the initial results of this project, which indicate a high correlation between the U.S. Bureau of Census block group statistics and statistics derived from remote sensing data.

Davis, Bruce A.↗

Windowed and Wavelet Analysis of Marine Stratocumulus Cloud Inhomogeneity

To improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current method of modeling cloud inhomogeneity is through the use of fractal parameters. This method is based on the supposition that cloud inhomogeneity over a large range of scales is related. An analysis technique named wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, the authors discuss the analysis and modeling of cloud inhomogeneity through the use of wavelet analysis. Wavelet analysis as well as other windowed analysis techniques are used to study liquid water path (LWP) measurements obtained during the marine stratocumulus phase of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment. Statistics obtained using analysis windows, which are translated to span the LWP dataset, are used to study the local (small scale) properties of the cloud field as well as their time dependence. The LWP data are transformed onto an orthogonal wavelet basis that represents the data as a number of times series. Each of these time series lies within a frequency band and has a mean frequency that is half the frequency of the previous band. Wavelet analysis combined with translated analysis windows reveals that the local standard deviation of each frequency band is correlated with the local standard deviation of the other frequency bands. The ratio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect to time. This ratio defined as the variance coupling parameter is applicable to all of the frequency bands studied and appears to be related to the slope of the data's power spectrum. Similar analyses are performed on two cloud inhomogeneity models, which use fractal-based concepts to introduce inhomogeneity into a uniform cloud field. The bounded cascade model does this by iteratively redistributing LWP at each scale using the value of the local mean. This model is reformulated into a wavelet multiresolution framework, thereby presenting a number of variants of the bounded cascade model. One variant introduced in this paper is the 'variance coupled model,' which redistributes LWP using the local standard deviation and the variance coupling parameter. While the bounded cascade model provides an elegant two- parameter model for generating cloud inhomogeneity, the multiresolution framework provides more flexibility at the expense of model complexity. Comparisons are made with the results from the LWP data analysis to demonstrate both the strengths and weaknesses of these models.

Gollmer, Steven M.↗