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Clark, J.

Publications and source records attributed to Clark, J..

28 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Potentials for change detection using Seasat synthetic aperture radar data

The use of synthetic aperture radar (SAR) images for detecting change on the earth's surface is highly dependent on target orientation, azimuth angle, and sensor depression angle. SAR data can be used for change detection when consistency is maintained in radar wavelength, polarization, azimuth directions, and off-nadir depression angle. The interaction of these parameters and the imaged surface for change detection are shown in examples drawn from (1) Los Angeles, CA, (2) southern Florida, (3) Imperial Valley, CA, (4) a desert region west of Tucson, AZ, and (5) western Kansas. SAR imagery is used to emphasize the geometric form, and roughness, of the earth's surface. As changes in the roughness of the surface occur over time, temporal SAR images will indicate those differences. Several guidelines for change detection studies using imaging radar are derived from the examples.

Bryan, M. L.↗
NASA NTRS1983

Integration of imagery and cartographic data through a common map base

Several disparate data types are integrated by using control points as the basis for spatially registering the data to a map base. The data are reprojected to match the coordinates of the reference UTM (Universal Transverse Mercator) map projection, as expressed in lines and samples. Control point selection is the most critical aspect of integrating the Thematic Mapper Simulator MSS imagery with the cartographic data. It is noted that control points chosen from the imagery are subject to error from mislocated points, either points that did not correlate well to the reference map or minor pixel offsets because of interactive cursorring errors. Errors are also introduced in map control points when points are improperly located and digitized, leading to inaccurate latitude and longitude coordinates. Nonsystematic aircraft platform variations, such as yawl, pitch, and roll, affect the spatial fidelity of the imagery in comparison with the quadrangles. Features in adjacent flight paths do not always correspond properly owing to the systematic panorama effect and alteration of flightline direction, as well as platform variations.

Clark, J.↗
NASA NTRS1981

Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

Clark, J.↗
NASA NTRS1981

Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

Clark, J.↗
NASA NTRS1979

Landsat-D thematic mapper simulation in an urban area using aircraft multispectral scanner data

A simulation of imagery from the Landsat-D thematic mapper was conducted in order to determine its usefulness for urban land-use classification. Aircraft 24-channel multispectral scanner imagery of the Los Angeles area at 7.5-m resolution was processed digitally by means of matrix averaging and image smoothing techniques to simulate the 30-m resolution of the thematic mapper. Mean and standard deviation statistics of training sites for resolutions of 7.5, 15, 30 and 60 m were used to generate final classification maps. Plots of relative standard deviation showed that for larger training sites, as the resolution decreased, the distribution range of density values also decreased, while plots of relative classification accuracies showed that as resolution decreased, classification accuracies for three levels of standard deviation increased. A point of diminishing returns was indicated, however, confirming the utility of the resolution intended for Landsat-D.

Clark, J.↗
NASA NTRS1977

LANDSAT-D thematic mapper simulation using aircraft multispectral scanner data

A simulation of imagery from the upcoming LANDSAT-D thematic mapper was accomplished by using selected channels of 24-channels aircraft multispectral scanner data. The purpose was to simulate thematic mapper 30-meter resolution imagery and compare its spectral quality with the original aircraft MSS data and determine changes in thematic classification accuracy for the simulated imagery. The original resolution of approximately 7.5 meters IFOV and simulated resolution of 15, 30, and 60 meters were used to indicate the trend of spectral quality and classification accuracy. The study was based in a 6.5 square kilometer area of urban Los Angeles having a diversity of land use.

Clark, J.↗
NASA NTRS1977

Landsat-D thematic mapper simulation using aircraft multispectral scanner data

A simulation of imagery from the upcoming Landsat-D Thematic Mapper was accomplished by using selected channels of aircraft 24-channel multispectral scanner data. The purpose was to simulate Thematic Mapper 30-meter resolution imagery, to compare its spectral quality with the original aircraft MSS data, and to determine changes in thematic classification accuracy for the simulated imagery. The original resolution of approximately 7.5 meters IFOV and simulated resolution of 15, 30, and 60 meters were used to indicate the trend of spectral quality and classification accuracy. The study was based in a 6.5 square kilometer area of urban Los Angeles having a diversity of land use. The original imagery was reduced in resolution by two related methods: pixel matrix averaging, and matrix smoothing with a unity box filter, followed by matrix averaging. Thematic land use classification using training sites and a Bayesian maximum-likelihood algorithm was performed at three levels of standard deviation - 1.0, 2.0, and 3.0 sigma. Plots of relative standard deviation showed that for larger training sites with a normal distribution of data, as the resolution decreased, the distribution range of density values decreased. Also, the classification accuracies for three levels of standard deviation increased as resolution decreased. However, the indication is that a point of diminishing returns had been reached, and 30 meters IFOV should be the best for multispectral classification of urban scenes.

Clark, J.↗
NASA NTRS1965

Marine biology and remote sensing

Remote sensing from manned orbital spacecraft for measuring characteristics of physical environment at sea surface - marine biology

SENSING↗