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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Recession of Martian north polar cap - 1979-1980 Viking observations

The polar regression curve for the Martian northern polar cap, derived from Viking observations for the 1979-1980 regression, is discussed, and comparisons with previous regression curves are made. Differences in the curves may be due to dust storms affecting the deposition of the cap. It is not possible to unambiguously ascribe differences between the curves to dynamical effects, since detailed information on the longitudinal dependence, which was an uncontrolled variable, is not available.

James, P. B.↗
NASA NTRS1982

A multi-frequency measurement of thermal microwave emission from soils - The effect of soil texture and surface roughness

An experiment on remote sensing of soil moisture content was conducted over bare fields with microwave radiometers at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz during July September of 1981. Three bare fields with different surface roughneses and soil textures were prepared for the experiment. Ground truth acquisition of soil temperatures and moisture contents for 5 layers down to the depth of 15 cm was made concurrently with radiometric measurements. The experimental results show that the effect of surface roughness is to increase the soils' brightness temperature and to reduce the slope of regression between brightness temperature and moisture content. The slopes of regression for soils with different textures are found to be comparable, and the effect of soil texture is reflected in the difference of regression line intercepts at brightness temperature axis. The result is consistent with laboratory measurement of soils' dielectric permittivity. Measurements on wet smooth bare fields give lower brightness temperatures at 5 GHz than at 1.4 GHz. Previously announced in STAR as N82-24550

Wang, J. R.↗
NASA NTRS1984

Applications of cluster analysis to satellite soundings

The advantages of the use of cluster analysis in the improvement of satellite temperature retrievals were evaluated since the use of natural clusters, which are associated with atmospheric temperature soundings characteristic of different types of air masses, has the potential for improving stratified regression schemes in comparison with currently used methods which stratify soundings based on latitude, season, and land/ocean. The method of discriminatory analysis was used. The correct cluster of temperature profiles from satellite measurements was located in 85% of the cases. Considerable improvement was observed at all mandatory levels using regression retrievals derived in the clusters of temperature (weighted and nonweighted) in comparison with the control experiment and with the regression retrievals derived in the clusters of brightness temperatures of 3 MSU and 5 IR channels.

Munteanu, M. J.↗
NASA NTRS1984

Sampling system for wheat (Triticum aestivum L) area estimation using digital LANDSAT MSS data and aerial photographs

A procedure to estimate wheat (Triticum aestivum L) area using sampling technique based on aerial photographs and digital LANDSAT MSS data is developed. Aerial photographs covering 720 square km are visually analyzed. To estimate wheat area, a regression approach is applied using different sample sizes and various sampling units. As the size of sampling unit decreased, the percentage of sampled area required to obtain similar estimation performance also decreased. The lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation is 13.90% using 10 square km as the sampling unit. Wheat area estimation using only aerial photographs is less precise and accurate than those obtained by regression estimation.

Parada, N. D. J.↗
NASA NTRS1984

Effects of alloy composition on cyclic flame hot-corrosion attack of cast nickel-base superalloys at 900 deg C

The effects of Cr, Al, Ti, Mo, Ta, Nb, and W content on the hot corrosion of nickel base alloys were investigated. The alloys were tested in a Mach 0.3 flame with 0.5 ppmw sodium at a temperature of 900 C. One nondestructive and three destructive tests were conducted. The best corrosion resistance was achieved when the Cr content was 12 wt %. However, some lower-Cr-content alloys ( 10 wt%) exhibited reasonable resistance provided that the Al content alloys ( 10 wt %) exhibited reasonable resistance provided that the Al content was 2.5 wt % and the Ti content was Aa wt %. The effect of W, Ta, Mo, and Nb contents on the hot-corrosion resistance varied depending on the Al and Ti contents. Several commercial alloy compositions were also tested and the corrosion attack was measured. Predicted attack was calculated for these alloys from derived regression equations and was in reasonable agreement with that experimentally measured. The regression equations were derived from measurements made on alloys in a one-quarter replicate of a 2(7) statistical design alloy composition experiment. These regression equations represent a simple linear model and are only a very preliminary analysis of the data needed to provide insights into the experimental method.

Deadmore, D. L.↗
NASA NTRS1983

A sampling system for estimating the cultivation of wheat (Triticum aestivum L) from LANDSAT data

Using digitally processed MSS/LANDSAT data as auxiliary variable, a methodology to estimate wheat (Triticum aestivum L) area by means of sampling techniques was developed. To perform this research, aerial photographs covering 720 sq km in Cruz Alta test site at the NW of Rio Grande do Sul State, were visually analyzed. LANDSAT digital data were analyzed using non-supervised and supervised classification algorithms; as post-processing the classification was submitted to spatial filtering. To estimate wheat area, the regression estimation method was applied and different sample sizes and various sampling units (10, 20, 30, 40 and 60 sq km) were tested. Based on the four decision criteria established for this research, it was concluded that: (1) as the size of sampling units decreased the percentage of sampled area required to obtain similar estimation performance also decreased; (2) the lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation was 90% using 10 sq km s the sampling unit; and (3) wheat area estimation by direct expansion (using only aerial photographs) was less precise and accurate when compared to those obtained by means of regression estimation.

Parada, N. D. J.↗
NASA NTRS1983

Fitting of satellite and in-situ ocean surface temperatures Results for polymode during the winter of 1977-1978

For the period considered, December 1977 through February 1978, bivariate Gaussian discriminant function cloud identification revealed that more than 93 percent of the 8-km resolution GOES infrared pixels were cloud contaminated. Cloud-free in-situ calibration points were distributed in nonrandom groups; this resulted in systematic errors when using least squares techniques. Surfaces and regression lines were least squares fitted between satellite and in-situ data; use was also made of differences and ratios. The best results were achieved with a regression in the form of the infrared radiative transfer equation; but this was no better than + or - 0.9 K. Because of extensive cloudiness, the linear regressions were seldom useful, and temperature ratios with + or - 1.3 K experimental errors best represent the applicability of GEOS data to sea surface temperatures.

Maul, G. A.↗
NASA NTRS1985

Applications of Some Artificial Intelligence Methods to Satellite Soundings

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Munteanu, M. J.↗
NASA NTRS1984

Toward a balanced assessment of collinearity diagnostics

The present investigation is concerned with a review of the foundations upon which regression methodology is based, taking into account a study of regression diagnostics conducted by Belsey et al. (1980). It is found that one of the most difficult and controversial problems facing data analysts is related to redundant predictor variables in a regression analysis. Collinearity diagnostics are only meaningful when interpreted in terms of 'basic variables' which are 'structurally interpretable'. Conflicting perspectives are discussed, giving attention to the role of centering when diagnosing collinearity. The definition of collinearity and collinearity measures are considered along with questions regarding 'structural interpretability' as a universally accepted principle in model formulation, and the importance of the detection of collinearity with the constant term.

Gunst, R. F.↗
NASA NTRS1984

Remote sensing of near surface humidity over north Pacific

Humidity soundings at 12 midocean stations of small islands and weather ships in the north Pacific from 7 deg N to 57 deg N during a 9-year period from 1972 to 1980 were used to study the variation of columnar water vapor W (as measured by spaceborne sensors) in relation to the variation of surface level specific humidity Q (as required in the determination of air-sea moisture and latent heat exchanges). It was found that a simple regression can be used to specify monthly mean Q from W to an accuracy of about 0.0008, corresponding to about 20 W/sq m in latent heat flux. The regression accounts for both temporal and spatial variations of Q and W. Better accuracy can be achieved by using regional regressions. The study affirms the potential of spaceborne sensors in providing global monitoring of air-sea moisture and heat exchanges.

Liu, W. T.↗
NASA NTRS1985

Evaluation of crop acreage estimation methods using Landsat data as auxiliary input

The regression and ratio estimators are studied in the context of improving upon the ground survey estimates of crop acreages by utilizing Landsat data. The approach is to formulate analytically the estimation problem that utilizes ground survey data, as collected by the U.S. Department of Agriculture, and Landsat data, which provide a complete coverage for an area of interest, and then to conduct simulation studies. It is shown over a wide range of conditions that the regression estimator is the most efficient unless there is a low correlation between the actual and estimated crop acreages in the sampled area segments, in which case a ratio type estimator is superior. Estimation of the variance of the regression estimator is also investigated.

Chhikara, R. S.↗
NASA NTRS1986

Optimized retrievals of precipitable water fields from combinations of VAS satellite and conventional surface observations

VISSR (visible and infrared spin-scan radiometer) atmospheric sounder (VAS) radiances and conventional surface temperature and dewpoint data are used in several combinations within a regression approach to determine the optimum resolution and accuracy of precipitable water (PW) fields retrieved from satellite observations. Point retrievals at radiosonde stations are used to determine the numerical accuracy of each retrieval technique, and image sequences of the retrieved PW fields are used to determine the temporal stability and spatial coherence of mesoscale PW features. VAS channels 5, 6, 7, and 8 and the surface dewpoint contribute the most information to regression-based retrievals of PW. The most accurate PW retrievals are obtained when radiances are averaged to a resolution of 15 to 60 km. A physical 'split-window' approach provides better PW estimates than regression when only the 11- and 12-micron VAS channels are available or when radiosonde-based training is limited to only one time period.

Robinson, W. D.↗
NASA NTRS1986

Remote sensing of Spartina anglica biomass in five French salt marshes

The utilization of regression models to estimate Spartina anglica biomass in marshes is studied. Radiance data for five S. anglica plots located along the coast of Brittany, France at 48 deg 40 min N between 1 deg 30 min W- 4 deg 30 min W was collected with a hand-held radiometer. Biomass data is derived from the radiance data, and the radiance and biomass data are employed in the formulation of simple regression models. The models are applied to the radiance data from the other four marshes. It is observed that the models predicted the biomass for all four marshes, and for three of the four marshes the estimated leaf and live biomass are within 1-13 percent of the harvest values. The effects of slit and dead tissues on the radiance from the S. anglica canopies are analyzed. It is noted that simple regression models which correlate radiance data to S. Anglica biomass in one marsh can be applied to the accurate prediction of leaf and live S. anglica biomass in other marshes.

Gross, M. F.↗
NASA NTRS1987

Comparison of two numerical techniques for aerodynamic model identification

An algorithm, called the Minimal Residual QR algorithm, is presented to solve subset regression problems. It is shown that this scheme can be used as a numerically reliable implementation of the stepwise regression technique, which is widely used to identify an aerodynamic model from flight test data. This capability as well as the numerical superiority of this scheme over the stepwise regression technique is demonstrated in an experimental simulation study.

Verhaegen, M. H.↗
NASA NTRS1986

Optimum retrieval of precipitable water fields from VAS and surface data

The use of VAS radiances and conventional surface data to determine the optimum resolution and accuracy of low-level precipitable water fields retrieved from geosynchronous satellite observations is examined. VAS retrievals of precipitated water (PW) are compared with various channel selections in the regression algorithm and with the split window algorithm. The split window algorithm and the linear regression algorithm are described. Consideration is given to the sounding-field-of-view (SFOV) resolution; the data reveal that the optimum resolution for the split window algorithm is at 15-60 km resolution, and 30-60 km SFOV resolution is optimal for the regression method. Statistics and images from PW retrieval experiments conducted on July 13, 1981 are presented and utilized to determine optimum channel selection. A fast contouring method for VAS sounding images is proposed.

Chesters, Dennis↗
NASA NTRS1987

Soil moisture estimation using GOES-VISSR infrared data - A case study with a simple statistical method

Five days of clear sky observations of Kansas and Nebraska are used to examine the statistical relationship between soil moisture and infrared surface temperature observations taken from a geosynchronous satellite. Linear regression is used to relate soil moisture to surface temperature and other variables that represent wind speed, vegetation cover, and low-level temperature advection. Results show good agreement between estimated and observed soil moisture features on each of the 5 days. The average coefficient of determination for five pseudoindependent tests in which the test day is held out of the regression is 0.71. It is shown that a depletion coefficient of 0.92, when used to compute antecedent precipitation index (API), produces the best correlation between API and soil moisture as inferred from GOES thermal infrared data. By averaging daily predicted values over the 5-day rain-free case study period, 92 percent of the variance of the morning surface temperature change is explained by a simple multiple linear regression with all independent variables, or, alternatively, 85 percent of the observed variance in API is explained. It is concluded that this approach can distinguish at least four classes of soil wetness, but the necessity for measurement of surface advection may limit its usefulness in remote areas.

Wetzel, Peter J.↗
NASA NTRS1986

Estimation of left ventricular mass in conscious dogs

A method for the assessment of the development or the regression of left ventricular hypertrophy (LVH) in a conscious instrumented animal is described. First, the single-slice short-axis area-length method for estimating the left-ventricular mass (LVM) and volume (LVV) was validated in 24 formaldehyde-fixed canine hearts, and a regression equation was developed that could be used in the intact animal to correct the sonomicrometrically estimated LVM. The LVM-assessment method, which uses the combined techniques of echocardiography and sonomicrometry (in conjunction with the regression equation), was shown to provide reliable and reproducible day-to-day estimates of LVM and LVV, and to be sensitive enough to detect serial changes during the development of LVH.

Coleman, Bernell↗
NASA NTRS1987

Comparison of two numerical techniques for aerodynamic model identification

A new algorithm, called the Minimal Residual QR algorithm, is presented to solve subset regression problems. It is shown that this new scheme can be used as a numerically reliable implementation of the stepwise regression technique, which is widely used to identify an aerodynamic model from flight test data. This capability as well as the numerical superiority of this scheme over the stepwise regression technique is demonstrated in an experimental simulation study.

Verhaegen, M. H.↗