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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

The effects of seasonal differences in climatic conditions on Landsat spectral signatures and associated land cover classification

Unsupervised classification algorithms are used to analyze Landsat computer-compatible tape data for an area of approximately 840 sq km in central Oklahoma, over the period from June 12 to August 4, 1979. The results obtained show that changes in remotely sensed spectral signatures and land cover classes are associated with a period of transition from moisture availability in late spring to moisture deficit in midsummer, with the latter being marked by greater visible spectrum reflectance and greater near-IR absorption, although each surface cover type has responded differently to the seasonal change in water availability. Consideration of these results has led to the identification of important factors in the use of multidate satellite data in environmental change monitoring. Naturally induced trends in surface albedo introduce noise into studies aimed at identifying anthropogenic land cover change. Specific problems associated with prairie-forest ecotonal areas in the southern Great Plains involve the seasonally induced differences in separability of forest, bush, and grassland cover types.

Harrington, J. A., Jr.↗
NASA NTRS1983

Urban land use classification using synthetic aperture radar

Several approaches to the use of radar imagery for land use classification of urban and near-urban areas are presented. The use of L band, horizontal transmit, and horizontal receive data is emphasized because of their general availability. For urban area studies using imaging radar, the effects of processing in an off-zero Doppler or squint mode, of the presence of large diffuse scatters, and of the possibility of height measurements are discussed. Data from the Los Angeles area are illustratively used.

Bryan, M. L.↗
NASA NTRS1982

Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms, volume 2

Agricultural crop classification models using two or more spectral regions (visible through microwave) were developed and tested and biomass was estimated by including microwave with visible and infrared data. The study was conducted at Guymon, Oklahoma and Dalhart, Texas utilizing aircraft multispectral data and ground truth soil moisture and biomass information. Results indicate that inclusion of C, L, and P band active microwave data from look angles greater than 35 deg from nadir with visible and infrared data improved crop discrimination and biomass estimates compared to results using only visible and infrared data. The active microwave frequencies were sensitive to different biomass levels. In addition, two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass.

Rosenthal, W. D.↗
NASA NTRS1983

Frequency of Fast, Narrow Gamma-ray Bursts and Burst Classification

Evidence from the Vela satellites that very brief, approximately 0.1 s, gamma-ray bursts constitute a class distinct from the longer, highly structured bursts has been strengthened by the results of the Venera 11 and 12 KKONUS experiments. The Goodard ISEE-3 gamma-ray burst spectrometer, utilizing a trigger criterion which is more likely to be independent of duration than previous experiments, detected a sample of events which enhances this bimodal distribution. The ISEE-3 result is corroborated by an increase in the frequency of detection of short bursts in the KONUS 13/14 database over KONUS 11/12, an effect attributable to the use of a shorter trigger integration time in the later experiments. Considerations such as repeating bursters complicate a simple dichotomous classification of gamma-ray bursts.

Norris, J. P.↗
NASA NTRS1984

A tectonic geomorphological classification of the walls of Valles Marineris

Viking 1 imagery of the Coprates NW quadrangle was used in an attempt to develop a geomorphic classification scheme for the canyon walls of Valles Marineris analogous to that devised to evaluate the relative tectonic activity of terrestrial mountain fronts. The four classes of walls established are described and mapped. Regions where a class cannot be assigned owing to the presence of intra canyon sediments, landslides, or landslide debris; and apparent fault scarps that occur on the canyon floor rather than at the wall base are also shown. The most striking feature is the concentration of active tectonic features within lus Chasma, and to a lesser extent in Tithonium Chasma, as well as along the north walls of Coprates and East Candor.

Spencer, J. R.↗
NASA NTRS1983

Evaluation of the effects of the seasonal variation of solar elevation angle and azimuth on the processes of digital filtering and thematic classification of relief units

The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Two sets of LANDSAT data referring to the orbit 150 and row 28 were selected with illumination parameters varying from 43 deg to 64 deg for azimuth and from 30 deg to 36 deg for solar elevation respectively. IMAGE-100 system permitted the digital processing of LANDSAT data. Original images were transformed by means of digital filtering so as to enhance their spatial features. The resulting images were used to obtain an unsupervised classification of relief units. Topographic variables (declivity, altitude, relief range and slope length) were used to identify the true relief units existing on the ground. The LANDSAT over pass data show that digital processing is highly affected by illumination geometry, and there is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

Parada, N. D. J.↗
NASA NTRS1984

A simulation of remote sensor systems and data processing algorithms for spectral feature classification

A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

Arduini, R. F.↗
NASA NTRS1984

Petrography and classification of Ca, Al-rich and olivine-rich inclusions in the Allende CV3 chondrite

The results of a detailed, systematic petrographic survey of Ca, Al-rich and olivine-rich inclusions in the Allende CV3 chondrite are reported, and a new classification system based on clearly defined and readily applied petrographic criteria is presented. Most Allende inclusions are aggregates containing one or more of three distinct constituents: (1) rimmed concentric objects enriched in Al- and Ti-rich oxide minerals and various amounts of Ca-rich silicates; (2) porous, 'fine-grained' chaotic material enriched in Ca-rich silicates, especially clinopyroxenes and garnets; and (3) porous, 'fine-grained', mafic inclusion matrix, enriched in olivine, pyroxene, and feldspathoids. Two texturally distinct varieties of inclusions consist primarily of inclusion matrix: unrimmed olivine aggregates and rimmed olivine aggregates. Ca, Al-rich inclusions are classified on the basis of the size and abundance of their constituent concentric objects. Some fundamental relationships among Allende inclusions that previusly have not been emphasized are discussed.

Kormacki, A. S.↗
NASA NTRS1983

The statewide forest/nonforest classification of Pennsylvania using Landsat MSS data

A procedure is described for processing the large volume of data needed to generate a Landsat-derived forest resource map (forest/nonforest mask) for the state of Pennsylvania, for use in a defoliation assessment program. Landsat coverage of the 28 million acres encompassing Pennsylvania requires portions of ten Landsat frames, totalling approximately 76 million pixels. A prime effort of this project was to efficiently and accurately classify this data into forest or nonforest categories. A specialized approach to Bayesian classification was developed which involved the use of MSS5 and MSS7; the identification of a single class, forest; and the use of the confidence map to generate the forest/nonforest mask. Statewide, for 7-acre contiguous forest areas, the overall agreement achieved between the mask and reference data was 90 percent.

Russo, S. A.↗
NASA NTRS1983

Automated vegetation classification using Thematic Mapper Simulation data

The present investigation is concerned with the results of a study of Thematic Mapper Simulation (TMS) data. One of the objectives of the study was related to an evaluation of the usefulness of the Thematic Mapper's (TM) improved spatial resolution and spectral coverage. The study was undertaken as part of a preparation for the efficient incorporation of Landsat 4 data into ongoing technology development in remote sensing. The study included an application of automated Landsat vegetation classification technology to TMS data. Results of comparing TMS data to Multispectral Scanner (MSS) data were found to indicate that all field definition, crop type discrimination, and subsequent proportion estimation may be greatly increased with the availability of TM data.

Nedelman, K. S.↗
NASA NTRS1984

Texture classification using autoregressive filtering

A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

Lawton, W. M.↗
NASA NTRS1985

Geomorphic Classification of Lava Flows on Io

The lava flows on Io are classified into the following categories: broad, filamental, digitate, intercalated, sheet, and contained. Each classification is described according to flow distribution, geomorphology, color, thickness, and source.

Pieri, D. C.↗
NASA NTRS1985

Classification of Circular Features on Venus

Among the unanswered questions concerning Venus are the age of its surface and the mechanisms of lithospheric heat transfer (conduction, plate recycling, and hot spot volcanism). If there is a large population of impact craters, then the surface is ancient and Venus is characterized by conduction like the Moon, and Mercury, rather than plate recycling and hot spot volcanism. Alternatively, if there is a large population of volcanic craters, then the surface is younger and other mechanisms of heat transfer likely dominate. Previous studies have emphasized various aspects of the observational, theoretical, experimental, and comparative planetological studies of cratering on Venus, and several have reached divergent opinions concerning the age of the Venus surface. A major source of uncertainty in previous studies is the possible inclusion of circular features of nonimpact (volcanic or tectonic) origin in the so called impact crater population. A classification scheme of circular features on Venus is developed in order to further distinguish their origin and distribution.

Stofan, E. R.↗
NASA NTRS1984

Improved classification of small-scale urban watersheds using thematic mapper simulator data

The utility of Landsat MSS classification methods in the case of small, highly urbanized hydrological basins containing complex land-use patterns is limited, and is plagued by misclassifications due to the spectral response similarity of many dissimilar surfaces. Landsat MSS data for the Conley Creek basin near Atlanta, Georgia, have been compared to thematic mapper simulator (TMS) data obtained on the same day by aircraft. The TMS data were able to alleviate many of the recurring patterns associated with MSS data, through bandwidth optimization, an increase of the number of spectral bands to seven, and an improvement of ground resolution to 30 m. The TMS is thereby able to detect small water bodies, powerline rights-of-way, and even individual buildings.

Owe, M.↗
NASA NTRS1984

Use of Landsat-derived profile features for spring small-grains classification

The present model for the temporal behavior of agricultural greenness is applied to the extraction of Landsat-derived profile features, distinguishing small from large grain crops. An additional feature derivable from the temporal behavior of the ratio of greenness to brightness is noted which aids in the separation of crops from other vegetation. A limited training set of 20 pure pixels/class, obtained from ground data, is subjected to the Ho-Kashyap (1965) linear classifier. The initial correct classification value for pure pixels of about 85 percent drops to 75 percent for all Landsat pixels.

Badhwar, G. D.↗
NASA NTRS1983

Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms

This paper describes the results of a study to determine if crop acreage and biomass estimates could be improved by using visible IR and microwave data. The objectives were to (1) develop and test agricultural crop classification models using two or more spectral regions (visible through microwave), and (2) estimate biomass by including microwave with visible and infrared data. Aircraft multispectral data collected during the study included visible and infrared data (multiband data from 0.5 m - 12 m), and active microwave data K band (2 cm), C band (6 cm), L band (20 cm), and P band (75 cm) HH and HV polarizations. Ground truth data from each field consisted of soil moisture and biomass measurements. Results indicated that C, L, and P band active microwave data combined with visible and infrared data improved crop discrimination and biomass estimates compared to results using only visible and infrared data. The active microwave frequencies were sensitive to different biomass levels; K and C being sensitive to differences at low biomass levels, while P band was sensitive to differences at high biomass levels.

Rosenthal, W. D.↗
NASA NTRS1985

African land-cover classification using satellite data

Data from the advanced very high resolution radiometer sensor on the National Oceanic and Atmospheric Administration's operational series of meteorological satellites were used to classify land cover and monitor vegetation dynamics for Africa over a 19-month period. There was a correspondence between seasonal variations in the density and extent of green leaf vegetation and the patterns of rainfall associated with the movement of the Intertropical Convergence Zone. Regional variations, such as the 1983 drought in the Sahel of western Africa, were observed. Integration of the weekly satellite data with respect to time for a 12-month period produced a remotely sensed estimate of primary production based upon the density and duration of green leaf biomass. Eight of the 21-day composited data sets covering an 11-month period were used to produce a general land-cover classification that corresponded well with those of existing maps.

Tucker, C. J.↗