Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data classification”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

A Method for the Study of Human Factors in Aircraft Operations

A method for the study of human factors in the aviation environment is described. A conceptual framework is provided within which pilot and other human errors in aircraft operations may be studied with the intent of finding out how, and why, they occurred. An information processing model of human behavior serves as the basis for the acquisition and interpretation of information relating to occurrences which involve human error. A systematic method of collecting such data is presented and discussed. The classification of the data is outlined.

Barnhart, W.↗
NASA NTRS1975

Canonical analysis and transformation of Skylab multispectral scanner data

The author has identified the following significant results. The original transformation matrix, C, had sixteen axes. However, the first three axes contained 98.83% of the variance contained within the transformation. The values for axes one, two, and three were 83.61%, 14.49%, and 0.72%, respectively. The result was an 81.25% reduction in data bulk. It is expected that using transformed data for classification will result in significant reductions in computer cost.

Mcmurtry, G. J.↗
NASA NTRS1976

Digital preprocessing and classification of multispectral earth observation data

The development of airborne and satellite multispectral image scanning sensors has generated wide-spread interest in application of these sensors to earth resource mapping. These point scanning sensors permit scenes to be imaged in a large number of electromagnetic energy bands between .3 and 15 micrometers. The energy sensed in each band can be used as a feature in a computer based multi-dimensional pattern recognition process to aid in interpreting the nature of elements in the scene. Images from each band can also be interpreted visually. Visual interpretation of five or ten multispectral images simultaneously becomes impractical especially as area studied increases; hence, great emphasis has been placed on machine (computer) techniques for aiding in the interpretation process. This paper describes a computer software system concept called LARSYS for analysis of multivariate image data and presents some examples of its application.

Anuta, P. E.↗
NASA NTRS1979

Sampling for area estimation - A comparison of full-frame sampling with the sample segment approach

The objective of this investigation was to evaluate the effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of Landsat MSS data. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

Hixson, M. M.↗
NASA NTRS1980

Procedure M - An advanced procedure for stratified area estimation using Landsat

Procedure M is a systematic approach to processing multispectral scanner data for classification and acreage estimation. The procedure incorporates a statistically robust mechanism for estimation while utilizing component technologies that are based on the physically expected or measured responses of the canopy, atmosphere and sensor. This paper describes Procedure M in the context of large-area agricultural applications, emphasizing three specific configurations: for winter wheat, spring small grains, and corn and soybeans.

Holmes, Q. A.↗
NASA NTRS1980

Procedure M - A framework for stratified area estimation

This paper describes Procedure M, a systematic approach to processing multispectral scanner data for classification and acreage estimation. A general discussion of the rationale and development of the procedure is given in the context of large-area agricultural applications. Specific examples are given in the form of test results on acreage estimation of spring small grains.

Kauth, R. J.↗
NASA NTRS1981

An inventory of California's irrigated land

Currently in the fourth year of its applications pilot test project to assess irrigated lands for water management, California officials found that the performance goal of plus or minus 5% at the 95% confidence level by each of the state's 10 major hydrologic basins was bettered in all but a few cases using manual analysis techniques for estimation. The process used was photointerpretation of enlarged LANDSAT scenes (1:150,000 scale), adjusting the determined acreage using a regression estimator and ground truth data from 637 sample cells. Sample cells were allocated to areas stratified on the basis of field size and selected crop types. Interpretation of three dates of imagery was required to span the complete time during which irrigated crops are grown in California. The registration of multitemporal data and classification procedures for estimating irrigated land using digital techniques are being studied as part of the second task in the project.

Sawyer, G. B.↗
NASA NTRS1981

Multistage classification of multispectral Earth observational data: The design approach

An algorithm is proposed which predicts the optimal features at every node in a binary tree procedure. The algorithm estimates the probability of error by approximating the area under the likelihood ratio function for two classes and taking into account the number of training samples used in estimating each of these two classes. Some results on feature selection techniques, particularly in the presence of a very limited set of training samples, are presented. Results comparing probabilities of error predicted by the proposed algorithm as a function of dimensionality as compared to experimental observations are shown for aircraft and LANDSAT data. Results are obtained for both real and simulated data. Finally, two binary tree examples which use the algorithm are presented to illustrate the usefulness of the procedure.

Bauer, M. E.↗
NASA NTRS1982

Identification of Fe I lines in the ultraviolet solar spectrum

High-resolution ultraviolet echelle spectrograms of the sun obtained from a rocket-borne spectrograph have been used for the identification of Fe I absorption lines in the wavelength range 1770-2020 A. Wavelength measurements, with a precision of about 15 mA, are tabulated for 425 Fe I features, along with available laboratory wavelenghs or predicted wavelengths calculated from atomic energy level data. The classification system of Moore has been extended to include possible additional multiplets with 126 newly classified lines; 234 unclassified lines were observed and identified with laboratory Fe I spectra

Mccabe, M. K.↗
NASA NTRS1983

The use of thematic mapper data for land cover discrimination: Preliminary results from the UK SATMaP programme

The principal objectives of the UK SATMaP program are to determine thematic mapper (TM) performance with particular reference to spatial resolution properties and geometric characteristics of the data. So far, analysis is restricted to images from the U.S. and concentrates on spectra and radiometric properties. The results indicate that the data are inherently three dimensional compared with the two dimensional character of MSS data. Preliminary classification results indicate the importance of the near infrared band (TM 4), at least one middle infrared band (TM 5 or TM 6) and at least one of the visible bands (preferably either TM 3 or TM 1). The thermal infrared also appears to have discriminatory ability despite its coarser spatial resolution. For band 4 the forward and reverse scans show somewhat different spectral responses in one scene but this effect is absent in the other analyzed. From examination of the histograms it would appear that the full 8-bit quantization is not being effectively utilized for all the bands.

Jackson, M. J.↗
NASA NTRS1985

The Use of Thematic Mapper Data for Land Cover Discrimination: Preliminary Results from the UK Satmap Programme

The principal objectives of the UK SATMaP program are to determine thematic mapper (TM) performance with particular reference to spatial resolution properties and geometric characteristics of the data. So far, analysis is restricted to images from the U.S. and concentrates on spectra and radiometric properties. The results indicate that the data are inherently three dimensional compared with the two dimensional character of MSS data. Preliminary classification results indicate the importance of the near infrared band (TM 4), at least one middle infrared band (TM 5 or TM 6) and at least one of the visible bands (preferably either TM 3 or TM 1). The thermal infrared also appears to have discriminatory ability despite its coarser spatial resolution. For band 4 the forward and reverse scans show somewhat different spectral responses in one scene but this effect is absent in the other analyzed. From examination of the histograms it would appear that the full 8 bit quantization is not being effectively utilized for all the bands.

Jackson, M. J.↗
NASA NTRS1985

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Guseman, L. F., Jr.↗
NASA NTRS1990

An empirical investigation of sparse distributed memory using discrete speech recognition

Presented here is a step by step analysis of how the basic Sparse Distributed Memory (SDM) model can be modified to enhance its generalization capabilities for classification tasks. Data is taken from speech generated by a single talker. Experiments are used to investigate the theory of associative memories and the question of generalization from specific instances.

Danforth, Douglas G.↗
NASA NTRS1991

A consensual neural network

A neural network architecture called a consensual neural network (CNN) is proposed for the classification of data from multiple sources. Its relation to hierarchical and ensemble neural networks is discussed. CNN is based on the statistical consensus theory and uses nonlinearly transformed input data. The input data are transformed several times, and the different transformed data are applied as if they were independent inputs. The independent inputs are classified using stage neural networks and outputs from the stage networks are then weighted and combined to make a decision. Experimental results based on remote-sensing data and geographic data are given.

Benediktsson, J. A.↗
NASA NTRS1993

Security aspects of space operations data

This paper deals with data security. It identifies security threats to European Space Agency's (ESA) In Orbit Infrastructure Ground Segment (IOI GS) and proposes a method of dealing with its complex data structures from the security point of view. It is part of the 'Analysis of Failure Modes, Effects Hazards and Risks of the IOI GS for Operations, including Backup Facilities and Functions' carried out on behalf of the European Space Operations Center (ESOC). The security part of this analysis has been prepared with the following aspects in mind: ESA's large decentralized ground facilities for operations, the multiple organizations/users involved in the operations and the developments of ground data systems, and the large heterogeneous network structure enabling access to (sensitive) data which does involve crossing organizational boundaries. An IOI GS data objects classification is introduced to determine the extent of the necessary protection mechanisms. The proposal of security countermeasures is oriented towards the European 'Information Technology Security Evaluation Criteria (ITSEC)' whose hierarchically organized requirements can be directly mapped to the security sensitivity classification.

Schmitz, Stefan↗
NASA NTRS1996

Geostatistical approaches to interpolation and classification of remote-sensing data from ice surfaces

Geostatistical methods for interpolation and extrapolation techniques are used in glaciological data analysis. The results of a program involving the mapping of the Antarctica from satellite radar altimeter data are discussed. A combination of high and low resolution techniques was applied in the analysis of the Bering Glacier (Alaska). The global positioning system (GPS) located video data collected from small aircraft and the ERS-1 synthetic aperture radar (SAR) images were used. From the perspective of SAR data analysis, the Bering Glacier surge was the opportunity to characterize the surface of fast flowing ice and the rapid changes in the surface roughness.

Herzfeld, Ute Christina↗