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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Fluctuation statistics of outgoing longwave radiation in a general circulation model and in satellite data

Fluctuation statistics of Northern-Hemisphere-winter outgoing longwave radiation (OLR) obtained from data collected by Nimbus 7 and NOAA AVHRR are compared with those computed by a general circulation model (GCM). It was found that the GCM OLR has more variance than does the satellite, but that the GCM clear-sky OLR has less variance than the satellite OLR. The variance of the GCM outgoing full-sky OLR was found to be forced by clouds. While the standard deviation of the GCM full OLR is larger than that of the satellite OLR, the geographical patterns of both are similar. The autocorrelations of the modeled and the observed OLR also display similar geographical distributions, and they are in turn correlated with the dynamics.

Charlock, Thomas P.↗
NASA NTRS1970

Statistical complex fatigue data for SAE 4340 steel and its use in design by reliability

A brief description of the complex fatigue machines used in the test program is presented. The data generated from these machines are given and discussed. Two methods of obtaining strength distributions from the data are also discussed. Then follows a discussion of the construction of statistical fatigue diagrams and their use in designing by reliability. Finally, some of the problems encountered in the test equipment and a corrective modification are presented.

Kececioglu, D.↗
NASA NTRS1952

Preliminary Survey of Icing Conditions Measured During Routine Transcontinental Airline Operation

Icing data collected on routine operations by four DC-4-type aircraft equipped with NACA pressure-type icing-rate meters are presented as preliminary information obtained from a statistical icing data program sponsored by the NACA with the cooperation of many airline companies and the United States Air Force. The program is continuing on a much greater scale to provide large quantities of data from many air routes in the United States and overseas. Areas not covered by established air routes are also being included in the survey. The four aircraft which collected the data presented in this report were operated by United Air Lines over a transcontinental route from January through May, 1951. An analysis of the pressure-type icing-rate meter was satisfactory for collecting statistical data during routine operations. Data obtained on routine flight icing encounters from.these four instrumented aircraft, although insufficient for a conclusive statistical analysis, provide a greater quantity and considerably more realistic information than that obtained from random research flights. A summary of statistical data will be published when the information obtained daring the 1951-52 icing season and that to be obtained during the 1952-53 season can be analyzed and assembled. The 1951-52 data already analyzed indicate that the quantity, quality, and range of icing information being provided by this expanded program should afford a sound basis for ice-protection-system design by defining the important meteorological parameters of the icing cloud.

Perkins, Porter J.↗
NASA NTRS1987

Continental land cover assessment using Landsat MSS data

A statistical procedure to assess level-II continental resources using Landsat MSS digital data is presented. The statistical procedure involves a two-stage cluster sample within a stratified random sample. The utility of this procedure is assessed by using it to estimate the areal extent of the conifer and hardwood resources of the continental U.S. National estimates of conifer and hardwood derived using this sampling procedure were within 3 percent of U.S. Forest Service (USFS) figures. According to the Landsat-based study, 11 percent of the country is conifer forest and 12 percent is hardwood. The corresponding USFS figures are 13 and 15 percent, respectively. Comparison of the MSS classification products and airphotos showed that the conifer cover class was correctly identified 74 percent of the time and hardwood 80 percent of the time. The average classification accuracy countrywide for the four cover types considered (conifer, hardwood, water, and 'other') is 74 percent, and the overall accuracy is 85 percent. The statistical procedure provides a method of incorporating Landsat MSS digital data as a second state for level-II continental resource assessment. Alternate data sources, e.g., satellite and aircraft photographic imagery, may also be used in conjunction with this statistical model.

Nelson, Ross↗
NASA NTRS2010

Weighting Statistical Inputs for Data Used to Support Effective Decision Making During Severe Emergency Weather and Environmental Events

National Aeronautical and Space Administration (NASA) weather and atmospheric environmental organizations are insatiable consumers of geophysical, hydrometeorological and solar weather statistics. The expanding array of internet-worked sensors producing targeted physical measurements has generated an almost factorial explosion of near real-time inputs to topical statistical datasets. Normalizing and value-based parsing of such statistical datasets in support of time-constrained weather and environmental alerts and warnings is essential, even with dedicated high-performance computational capabilities. What are the optimal indicators for advanced decision making? How do we recognize the line between sufficient statistical sampling and excessive, mission destructive sampling ? How do we assure that the normalization and parsing process, when interpolated through numerical models, yields accurate and actionable alerts and warnings? This presentation will address the integrated means and methods to achieve desired outputs for NASA and consumers of its data.

Gardner, Adrian↗
NASA NTRS2004

Application of a Semiparametric Statistical Method to Spacecraft Sensor and Calibration Data

A semiparametric statistical method is applied to spacecraft sensor data and spacecraft sensor residual data. The method stipulates a reference distribution and deviations from it. The problem is to estimate the reference distribution and the distorted distributions from all available data from all the sources under consideration. The problem can be solved by assuming a distortion form and independent data.

Kedem, Benjamin↗
NASA NTRS1975

A statistical analysis of data extraction for land cover information from high-altitude and satellite images

Land cover information from a 10 by 30 km test site in eastern Wisconsin extracted using 70 mm positive LANDSAT transparencies in an additive color viewer at a scale of 1:500,000 was compared with land cover information extracted using LANDSAT 9 x 9 inch positive transparencies at a scale of 1:1,000,000. Color infrared photography (NASA RB-57) at a scale of 1:60,000 provided ground truth for each land cover type. Interpretations were made for four land cover classes: 1) forest-brushland; (2) structures-barren land; (3) surface water; and (4) agricultural-open land. Statistical comparisons showed that neither method for the extraction of this data was clearly superior.

Kiefer, R. W.↗
NASA NTRS1989

Calibration of quadpolarization SAR data using backscatter statistics

A new technique is described for calibration of complex multipolarization SAR imagery. Scatterer reciprocity and lack of correlation between like- and cross-polarized radar echoes for natural targets are used to remove cross-polarized contamination in the radar data channels without the use of known ground targets. If known targets are available, all data channels can be calibrated relative to one another and absolutely as well. The method is verified with airborne SAR data.

Klein, Jeffrey D.↗
NASA NTRS1997

Factor Analysis Applied the VFY-218 RCS Data

Present statistical factor analysis of computer simulations and measurement data for the VFY-218 configuration. Factor analysis try to quantify the statistical grouping of measurements and simulations.

Woo, Alex↗
NASA NTRS1988

Radiometric performance of AVIRIS: Assessment for an arid region geologic target

Data from several AVIRIS flight lines were examined to assess instrument stability and response. Both scene and in-flight calibration data were analyzed statistically. The data clearly indicates that, although the instrument output was noisy and unstable at the time of the data acquisition, valuable spectral signatures can still be extracted and analyzed. Some first order calibration corrections can be performed by forcing internal consistency within the data. AVIRIS data are delivered in band-interleaved-by-line format, but high efficiency routines were developed which access the data as either image or spectral planes and enable effective statistical and visual examination of both AVIRIS scenes and ancillary files. Two methods were used to extract spectral information from segment 4 of the Kelso Dunes flight. Both successfully identified at least three distinct spectral signatures, but neither has positively identified a specific material.

Kieffer, Hugh H.↗
NASA NTRS1985

Statistical methods for astronomical data with upper limits. I - Univariate distributions

The statistical treatment of univariate censored data is discussed. A heuristic derivation of the Kaplan-Meier maximum-likelihood estimator from first principles is presented which results in an expression amenable to analytic error analysis. Methods for comparing two or more censored samples are given along with simple computational examples, stressing the fact that most astronomical problems involve upper limits while the standard mathematical methods require lower limits. The application of univariate survival analysis to six data sets in the recent astrophysical literature is described, and various aspects of the use of survival analysis in astronomy, such as the limitations of various two-sample tests and the role of parametric modelling, are discussed.

Feigelson, E. D.↗
NASA NTRS1990

Neural network approaches versus statistical methods in classification of multisource remote sensing data

Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.

Benediktsson, Jon A.↗