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Landgrebe, D. A.

Publications and source records attributed to Landgrebe, D. A..

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Test of spectral/spatial classifier

The author has identified the following significant results. The supervised ECHO processor (which utilizes class statistics for object identification) successfully exploits the redundancy of states characteristic of sampled imagery of ground scenes to achieve better classification accuracy, reduce the number of classifications required, and reduce the variability of classification results. The nonsupervised ECHO processor (which identifies objects without the benefit of class statistics) successfully reduces the number of classifications required and the variability of the classification results.

Landgrebe, D. A.↗
NASA NTRS1977

ECHO user's guide

There are no author-identified significant results in this report.

Landgrebe, D. A.↗
NASA NTRS1977

An empirical study of scanner system parameters

Parametric values (instantaneous field of view, number and location of spectral bands, signal-to-noise ratio, etc.) of a multispectral scanner (thematic mapper) are assigned empirically. An empirical simulation approach was used with candidate parameter values selected by heuristic means. Results obtained using a conventional maximum likelihood pixel classifier suggest that although the classification accuracy declines slightly as the instantaneous field of view (IFOV) is decreased this is more than made up by an improved mensuration accuracy. Use of a classifier involving both spatial and spectral features helps resist degradation as the signal-to-noise ratio is decreased. The importance of having at least one spectral band in each of the major available portions of the optical spectrum is demonstrated.

Landgrebe, D. A.↗
NASA NTRS1977

Applications of remote sensing, volume 1

The author has identified the following significant results. ECHO successfully exploits the redundancy of states characteristics of sampled imagery of ground scenes to achieve better classification accuracy, reduce the number of classifications required, and reduce the variability of classification results. The information required to produce ECHO classifications are cell size, cell homogeneity, cell-to-field annexation parameters, input data, and a class conditional marginal density statistics deck.

Landgrebe, D. A.↗
NASA NTRS1977

Applications of remote sensing, volume 3

The author has identified the following significant results. Of the four change detection techniques (post classification comparison, delta data, spectral/temporal, and layered spectral temporal), the post classification comparison was selected for further development. This was based upon test performances of the four change detection method, straightforwardness of the procedures, and the output products desired. A standardized modified, supervised classification procedure for analyzing the Texas coastal zone data was compiled. This procedure was developed in order that all quadrangles in the study are would be classified using similar analysis techniques to allow for meaningful comparisons and evaluations of the classifications.

Landgrebe, D. A.↗
NASA NTRS1977

Applications of remote sensing, volume 2

The author has identified the following significant results. The overall spectral response of the strata measured by a mean vector and covariance matrix for each stratum did not show differences among the LACIE phase 3 strata using the machine clustering procedures. This was expected since the large strata gave rise to broad normal distributions with a great deal of overlap. The static stratification of Kansas contains strata which are small in size. The distributions for these strata are not as broad as those based on the LACIE phase 3 partitions, but there is still some confusion since strata from different categories are not spectrally distinct.

Landgrebe, D. A.↗
NASA NTRS1976

Classification of multispectral image data by extraction and classification of homogeneous objects

A classification method for digitized multispectral-image data is described. This method is designed to exploit a particular type of dependence between adjacent states of nature that is characteristic of the data. The advantages of this, as opposed to the conventional 'per point' approach, are greater accuracy and efficiency, and the results are in a more desirable form for most purposes. Experimental results from both aircraft and satellite data are included.

Kettig, R. L.↗
NASA NTRS1976

Machine processing of remotely acquired data

The two major branches of remote sensing are based on image orientation and numerical orientation. Numerically oriented systems tend to involve computers for data analysis. In designing an information-gathering system, the sensor as well as the means of analysis must be well mated to the type of system orientation. Attention is given to sensor types as related to system types, the multispectral approach and pattern recognition, the multispectral scanner as data source, an illustrative example, procedural details in the use of pattern recognition, the speed and cost of data processing, the use of spatial information, and data preprocessing steps.

Landgrebe, D. A.↗
NASA NTRS1975

Multispectral data analysis: LARSYS III

System uses pattern recognition and interactive data handling techniques applied to remotely sensed data. Basic analysis concept consists of locating data points which are believed to be representative of classes of interest.

Landgrebe, D. A.↗
NASA NTRS1975

Layered classification techniques for remote sensing applications

The single-stage method of pattern classification utilizes all available features in a single test which assigns the unknown to a category according to a specific decision strategy (such as the maximum likelihood strategy). The layered classifier classifies the unknown through a sequence of tests, each of which may be dependent on the outcome of previous tests. Although the layered classifier was originally investigated as a means of improving classification accuracy and efficiency, it was found that in the context of remote sensing data analysis, other advantages also accrue due to many of the special characteristics of both the data and the applications pursued. The layered classifier method and several of the diverse applications of this approach are discussed.

Swain, P. H.↗
NASA NTRS1975

Information systems and services, user services

The following topics were discussed: (1) data availability and distribution, (2) complete processing systems, (3) subsystems, (4) applications, (5) research for future technology, and (6) education, training opportunities, and materials. Evidence was given that remote sensing technology is being increasingly utilized. Therefore, it was concluded that a second stage of remote sensing technology should be developed.

Landgrebe, D. A.↗
NASA NTRS1975

Information/user services, summary

Various aspects of the technology which are available to users now are described. Specific topics discussed include: data distribution: availability of and access to data; technology transfer: system use illustrations and availability of training; hardware systems descriptions: processing hardware constructed and available; data processing techniques: individual processing techniques; and future developments: a sampling of future technology.

Landgrebe, D. A.↗
NASA NTRS1975

Remote sensing, a sketch of the technology

Information is provided on how a potential user of remote sensing technology can gain access to all of the products and services he will need to get started. It was envisioned that these include data, training, hardware, and software. A very brief tutorial summary of the fundamentals of the technology is presented.

Landgrebe, D. A.↗