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Results for “multispectral sensing”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

An unsupervised classification technique for multispectral remote sensing data.

Description of a two-part clustering technique consisting of (a) a sequential statistical clustering, which is essentially a sequential variance analysis, and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by traditional supervised maximum-likelihood classification techniques.

Su, M. Y.↗
NASA NTRS1971

A survey of multispectral remote sensing techniques for earth resources applications.

Remote sensing for earth resources applications has as its objective the collection and interpretation of information on all environmentally significant features of the atmosphere, oceans, and land surfaces. This information is most effectively gathered by airborne and satellite borne imaging systems. These systems operate at a variety of wavelengths extending from the visual spectrum, through the infrared and into the centimeter wavelengths of the microwave band. A comparison is made of the signal characteristics at these spectrum regions. In particular, the ability of microwave radiometric imaging to augment visual and infrared imaging is discussed. Recent developments in electronically scanned microwave radiometric sensors are described, together with methods of optimizing microwave data display. Results achieved with integrated display systems for both microwave and optical data are presented, together with projections for future applications.-

Pascalar, H. G.↗
NASA NTRS1972

Application of multispectral remote sensing to soil survey research in Indiana

Computer-implemented mappings based on spectral properties of bare soil surfaces were compared with mapping units of interest to soil surveyors. Some soil types could be differentiated by their spectral properties. In other cases, soils with similar surface colors and textures could not be distinguished spectrally. The spectral maps seemed useful for delineating boundaries between soils in many cases.

Zachary, A. L.↗
NASA NTRS1973

Two effective feature selection criteria for multispectral remote sensing

Distance measures which are useful for feature selection are considered, giving attention to the divergence distance measure and the Jeffreys-Matusita (JM) distance. Experimental studies show that the JM-distance yields more reliable results than other distance measures. A number of questions which are not solved by the experiments are discussed. The investigation provides an explanation for previous observations that the JM-distance and a saturating transform of divergence are highly useful for feature selection in the multiclass case.

Swain, P. H.↗
NASA NTRS1975

Multiseasonal-multispectral remote sensing of phenological change for natural vegetation inventory

The author has identified the following significant results. Variations in phenological development among plant species was noted, as well as the tendency for the seasonal appearance of some vegetation types to be dominated by the appearance of one or a few similarly developing species. Most of the common plants in the study area could be characterized by temporal aspects of their phenological development. There was a strong similarity among the spectral signatures of vegetation types in which the spectral return was dominated by green plant material. When the soil background dominated the spectral return from a vegetation stand, then the spectral radiance and the vegetation physiognomy were apparently related. When the deciduous shrubs lost their leaves, their spectral signature altered with a slight decrease of radiance in the visible wavelengths and a strong decrease in the near infrared. As the foliage of perennial grasses cured from August to November, its apparent green radiance remained unchanged, red radiance increased over 50 percent, and near infrared radiance decreased approximately 30 percent. A reflective mineral surface exhibited high radiance levels in all four bands, thus providing a marked contrast to the absorption characteristics of vegetation canopies.

Schrumpf, B. J.↗
NASA NTRS1976

Economic evaluation of crop acreage estimation by multispectral remote sensing

The author has identified the following significant results. Photointerpretation of S190A and S190B imagery showed significantly better resolution with the S190B system. A small tendancy to underestimate acreage was observed. This averaged 6 percent and varied with field size. The S190B system had adequate resolution for acreage measurement but the color film did not provide adequate contrast to allow detailed classification of ground cover from imagery of a single date. In total 78 percent of the fields were correctly classified but with 56 percent correct for the major crop, corn.

Manderscheid, L. V.↗
NASA NTRS1981

Investigation of multispectral remote sensing of snow cover using a solar radiation model

A solar radiation model is described which is able to calculate, for given atmospheric and topographic input conditions, the spectral distributions of the direct and diffuse components of the total irradiance incident upon a target surface. The irradiance includes both upwelling radiation backscattered toward the earth's surface and radiation reflected toward the target from other terrain surfaces. Spectral reflectance data for two dissimilar snow types are fed into the model, along with a geometric description of the topography of the snow covered terrain. These data permit the calculation of the exitance of the target over the wavelength limits of a given sensor and, hence, the apparent contrast between the two snow types for the given input conditions. The results show that the contrast between the two snow types, all other factors being constant, is greatest in the near infrared wavelengths.

Waterman, S. E.↗
NASA NTRS1982

Computational modeling of multispectral remote sensing systems: Background investigations

A computational model of the deterministic and stochastic process of remote sensing has been developed based upon the results of the investigations presented. The model is used in studying concepts for improving worldwide environment and resource monitoring. A review of various atmospheric radiative transfer models is presented as well as details of the selected model. Functional forms for spectral diffuse reflectance with variability introduced are also presented. A cloud detection algorithm and the stochastic nature of remote sensing data with its implications are considered.

Aherron, R. M.↗
NASA NTRS1980

Parallel processing implementations of a contextual classifier for multispectral remote sensing data

Contextual classifiers are being developed as a method to exploit the spatial/spectral context of a pixel to achieve accurate classification. Classification algorithms such as the contextual classifier typically require large amounts of computation time. One way to reduce the execution time of these tasks is through the use of parallelism. The applicability of the CDC flexible processor system and of a proposed multimicroprocessor system (PASM) for implementing contextual classifiers is examined.

Siegel, H. J.↗
NASA NTRS1992

Effects of water-emission anisotropy on multispectral remote sensing at thermal wavelengths of ocean temperature and of cirrus clouds

The impact of water-emission anisotropy on remotedly sensed long-wave data has been studied. Water emission is formulated from a calm body for a facile computation of radiative transfer in the atmosphere. The error stemming from the blackbody assumption are calculated for cases of a purely absorbing or a purely scattering atmosphere taking the optical properties of the atmosphere as known. For an absorbing atmosphere, the errors in the sea-surface temperature (SST) are found to be always reduced and be the same whether measurements are made from space or at any level of the atmosphere. The inferred optical thickness tau of an absorbing layer can be in error under the blackbody assumption by a delta tau of 0.01-0.08, while the inferred optical thickness of a scattering layer can be in error by a larger amount, delta tau of 0.03-0.13. It is concluded that the error delta tau depends only weakly on the actual optical thickness and the viewing angle, but is rather sensitive to the wavelength of the measurement.

Otterman, J.↗
NASA NTRS1975

The four- and five-band multispectral scanners for Landsat

The earth resources sensing Multispectral Scanner (MSS) for the Landsat satellite has two versions; one with four spectral bands from 0.5 to 1.1 microns, and one with five bands, the added band being 10.4 to 12.6 microns. This paper describes optical design and performance. The instrument uses a flat, object-space scanning mirror of near-linear motion, with a sensitive optical position monitor to detect mirror angular position. The 22.9-cm aperture telescope images the scene on an array of fiber optics, which dissect and transmit the scene energy to photomultiplier tubes detecting in Bands 1, 2, and 3, and silicon photodiodes detecting Band 4. Band 5 energy passes the fiber optic assembly and is reimaged on a radiatively cooled mercury cadmium telluride (HgCdTe) detector. The orbiting four-band scanner is furnishing data registered to better than 50-m band-to-band and resolving 80-m repetitive pattern over a 185-km swath width from 907-km altitude.

Lansing, J. C., Jr.↗
NASA NTRS1974

Investigation related to multispectral imaging systems

A summary of technical progress made during a five year research program directed toward the development of operational information systems based on multispectral sensing and the use of these systems in earth-resource survey applications is presented. Efforts were undertaken during this program to: (1) improve the basic understanding of the many facets of multispectral remote sensing, (2) develop methods for improving the accuracy of information generated by remote sensing systems, (3) improve the efficiency of data processing and information extraction techniques to enhance the cost-effectiveness of remote sensing systems, (4) investigate additional problems having potential remote sensing solutions, and (5) apply the existing and developing technology for specific users and document and transfer that technology to the remote sensing community.

Nalepka, R. F.↗
NASA NTRS1977

Multispectral data analysis

LARSYS III.1 program is designed for remote-sensing research and application. Pattern recognition and interaction data handling techniques analyze remotely-sensed multispectral and multitemporal data. Primary inputs are multispectral data in image orientation.

Source record↗
NASA NTRS1972

Remote sensing in Virginia agriculture

An experimental investigation, designed to develop and evaluate multispectral sensing techniques used in sensing agricultural crops, is described. Initial studies were designed to detect plant species and associated diseases, soil variations, and cultural practices under natural environment conditions. In addition, crop varieties, age, spacing, plant height, percentage of ground cover, and plant vigor are determined.

Pettry, D. E.↗