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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Knowledge-based Expert Systems for Crop Identification

The development of an improved understanding of the interactive man machine environment is investigated. In such an environment, as many feature inputs as practical would be automatically derived from a data base and input into an expert system decision making procedure. This procedure could then provide expert assistance to a trained image analyst to upgrade and improve the quantity and accuracy of the information extracted from the input data. A comparison of the similarities and differences between manual and automated image interpretation techniques is also examined.

Smith, T. R.↗
NASA NTRS1984

Asteroid Lightcurve Inversion

The application of convex profile inversion (CPI) to the interpretation of asteroid lightcurves is discussed. This technique investigates the problem of extracting information about an asteroid's shape from its lightcurve. Whenever four ideal conditions are met, P is an estimator for the asteroids mean cross section C, a convex set defined as the average of all cross sections C(Z) cut by planes a distance z above the asteroids equatorial plane. C is therefore a 2-D average of the asteroids 3-D shape. The method is tested by inverting lightcurves generated analytically for geometrically scattered ellipsoids (GSE's) with semiaxes a or = B or = C. Using a defined 'distance measure' to quantify the difference between any two profiles, the deviation of P from C for GSE's as a function of lightcurve noise level, rotation phase sampling interval delta theta, and departure from ideal conditions is calibrated. The distance between P and a circle provides a gauge of the asteroid's nonsphericity and incorporates all the information contained in the lightcurve.

Ostrow, S. J.↗
NASA NTRS1982

Research in satellite-aided crop inventory and monitoring

Automated information extraction procedures for analysis of multitemporal Landsat data in non-U.S. crop inventory and monitoring are reviewed. Experiments to develop and evaluate crop area estimation technologies for spring small grains, summer crops, corn, and soybeans are discussed. Previously announced in STAR as N82-32793

Erickson, J. D.↗
NASA NTRS1984

Validation of the Thematic Mapper radiometric and geometric correction algorithms

The radiometric and geometric correction algorithms for Thematic Mapper are critical to subsequent successful information extraction. Earlier Landsat scanners, known as Multispectral Scanners, produce imagery which exhibits striping due to mismatching of detector gains and biases. Thematic Mapper exhibits the same phenomenon at three levels: detector-to-detector, scan-to-scan, and multiscan striping. The cause of these variations has been traced to variations in the dark current of the detectors. An alternative formulation has been tested and shown to be very satisfactory. Unfortunately, the Thematic Mapper detectors exhibit saturation effects suffered while viewing extensive cloud areas, and is not easily correctable. The geometric correction algorithm has been shown to be remarkably reliable. Only minor and modest improvements are indicated and shown to be effective.

Fischel, D.↗
NASA NTRS1986

Algorithms for Coastal-Zone Color-Scanner Data

Software for Nimbus-7 Coastal-Zone Color-Scanner (CZCS) derived products consists of set of scientific algorithms for extracting information from CZCS-gathered data. Software uses CZCS-generated Calibrated RadianceTemperature (CRT) tape as input and outputs computer-compatible tape and film product.

Source record↗
NASA NTRS1982

Information Science Panel joint meeting with Imaging Science Panel

Specific activity in information extraction science (taken to include data handling) is needed to: help identify the bounds of practical missions; identify potential data handling and analysis scenarios; identify the required enabling technology; and identify the requirements for a design data base to be used by the disciplines in determining potential parameters for future missions. It was defined that specific analysis topics were a function of the discipline involved, and therefore no attempt was made to define any specific analysis developments required. Rather, it was recognized that a number of generic data handling requirements exist whose solutions cannot be typically supported by the disciplines. The areas of concern were therefore defined as: data handling aspects of system design considerations; enabling technology for data handling, with specific attention to rectification and registration; and enabling technology for analysis. Within each of these areas, the following topics were addressed: state of the art (current status and contributing factors); critical issues; and recommendations for research and/or development.

Source record↗
NASA NTRS1984

Automatic terrain elevation mapping and registration

Optimum radar illumination geometries for stereoscopic analysis of surface topography are determined. Correlation and image processing experiments on synthetic aperture radar (SAR) data for improved information extraction are conducted. Model of the geometry of the multiple SIR-B views of the Earth are developed the sensitivity of the derived terrain altitude data to the various system parameters is established. The limits of accuracy of terrain data achievable with shuttle imaging radar (SIR-B) are derived. Algorithms for matching multiple SIR-B images to generate digital terrain maps are developed. Finally, the use of such terrain maps in geometric correction and registration of SIR-B and LANDSAT Thematic Mapper data is demonstrated.

Ramapriyan, H. K.↗
NASA NTRS1984

The evaluation of display symbology - A chronometric study of visual search

Three single-target visual search tasks were used to evaluate a set of CRT symbols for a helicopter traffic display. The search tasks were representative of the kinds of information extraction required in practice, and reaction time was used to measure the efficiency with which symbols could be located and identified. The results show that familiar numeric symbols were responded to more quickly than graphic symbols. The addition of modifier symbols such as a nearby flashing dot or surrounding square had a greater disruptive effect on the graphic symbols than the alphanumeric characters. The results suggest that a symbol set is like a list that must be learned. Factors that affect the time to respond to items in a list, such as familiarity and visual discriminability, and the division of list items into categories, also affect the time to identify symbols.

Remington, R.↗
NASA NTRS1985

Proceedings of the Airborne Imaging Spectrometer Data Analysis Workshop

The Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on April 8 to 10, 1985. It was attended by 92 people who heard reports on 30 investigations currently under way using AIS data that have been collected over the past two years. Written summaries of 27 of the presentations are in these Proceedings. Many of the results presented at the Workshop are preliminary because most investigators have been working with this fundamentally new type of data for only a relatively short time. Nevertheless, several conclusions can be drawn from the Workshop presentations concerning the value of imaging spectrometry to Earth remote sensing. First, work with AIS has shown that direct identification of minerals through high spectral resolution imaging is a reality for a wide range of materials and geological settings. Second, there are strong indications that high spectral resolution remote sensing will enhance the ability to map vegetation species. There are also good indications that imaging spectrometry will be useful for biochemical studies of vegetation. Finally, there are a number of new data analysis techniques under development which should lead to more efficient and complete information extraction from imaging spectrometer data. The results of the Workshop indicate that as experience is gained with this new class of data, and as new analysis methodologies are developed and applied, the value of imaging spectrometry should increase.

Vane, G.↗
NASA NTRS1986

Remote Sensing Information Sciences Research Group, Santa Barbara Information Sciences Research Group, year 3

Research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. The focus is on remote sensing and application for the Earth Observing System (Eos) and Space Station, including associated polar and co-orbiting platforms. The remote sensing research activities are being expanded, integrated, and extended into the areas of global science, georeferenced information systems, machine assissted information extraction from image data, and artificial intelligence. The accomplishments in these areas are examined.

Estes, J. E.↗
NASA NTRS1985

Discrete-object modeling of remotely sensed scenes

Remotely sensed scenes can be modeled as collections of discrete, three-dimensional objects that cast shadows on a background. Approaching scenes from this perspective has led to two related lines of research. First is the geometric/optical modeling of a forest canopy, in which conifers are modeled as cones whose size and spacing vary according to functions established by field measurements. This canopy model is 'L-resolution' in nature - the objects are smaller than the resolution cells of the image and cannot be resolved individually. Second is scene modeling in which image variance is taken as a function of the relationship between the size, shape and spacing of objects and the resolution cell size of the digital image derived from the scene. This modeling is 'H-resolution' in nature - the objects in the scene are assumed to be larger than the resolution cells of the image, and thus can be individually distinguished. Both approaches illustrate the utility of the discrete-object scene model in extracting information from remotely sensed scenes.

Strahler, A. H.↗
NASA NTRS1985

1985 International Geoscience and Remote Sensing Symposium (IGARSS '85), University of Massachusetts, Amherst, October 7-9, 1985, Digest. Volumes 1 & 2

The present conference on remote sensing instrumentation considers topics in water resources research, planetary remote sensing and mathematical geophysics, sea ice behavior in view of the Cold Regions Research and Engineering Laboratories pond measurements, Shuttle Imaging Radar-B (SIR-B) system performance and calibration results, geological applications of remote sensing, and microwave scattering from vegetation. Further attention is given to atmospheric probing with lasers, image processing for remote sensing, forest inventory and condition assessment, atmospheric remote sensing, SIR-B geological results, the reflectance, emission, and scattering characteristics of vegetation, sea ice sensing, multipolarization SAR results, the theoretical modeling of surfaces and volumes, crop condition assessment and productivity estimates, and SIR-B results for vegetation cover. Also considered are the microwave remote sensing of soil moisture, advanced sensors, advanced information extraction, wind and wave remote observations, results from the ESA Remote Sensing satellite, large area crop and land cover statistics, SIR-B results for directional ocean wave spectra, seasonal snow cover, ice sheets, and lake ice, fundamental research in terrain remote sensing, image classification methods, vegetation stress detection, remote sensing of coastal processes, SAR systems and calibration, electromagnetic geophysical methods and signal processing, image processing techniques, and SAR internal wave measurements.

Carver, K. R.↗
NASA NTRS1986

Proceedings of the Second Airborne Imaging Spectrometer Data Analysis Workshop

The Second Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on May 6, 7, and 8, 1986. It was attended by 100 people from seven countries. Papers were presented by 24 attendees; summaries of 19 of the papers are published in these Workshop Proceedings. The Second Workshop was divided into three sessions: Calibration, the Atmosphere, and Data Techniques; Geological Research; and Botanical and Geobotanical Research. Because many of the AIS researchers have had an additional year to work with their data, a general advance was seen in the utilization of the data for solving earth science problems. The major conclusions that can be drawn from the Workshop are: (1) Almost everyone now working with AIS data is attempting to take into account in data analysis the effects of the atmosphere and sensor calibration and performance. As a result, information extraction techniques are becoming more sophisticated and effective. (2) The emphasis on work in the geological disciplines is beginning to shift to the application of AIS data for solving geological problems now that the efficacy of the data for mineral identification has been demonstrated. (3) In the botanical sciences, interpretation of AIS data is becoming more quantitative. Several statistical techniques are under development for extracting the subtle differences in plant spectra in the region of the near infrared and short wavelength infrared. In summary, an overall advance was seen in the ability to effectively utilize the fundamentally new class of data acquired with imaging spectrometers. There was also a general feeling at the Workshop however, that much work remains to be done in remote sensing research before the maximum potential of these data for solving earth science problems is realized.

Gregg Vane↗
NASA NTRS1987

Remote Sensing Information Sciences Research Group, year four

The needs of the remote sensing research and application community which will be served by the Earth Observing System (EOS) and space station, including associated polar and co-orbiting platforms are examined. Research conducted was used to extend and expand existing remote sensing research activities in the areas of georeferenced information systems, machine assisted information extraction from image data, artificial intelligence, and vegetation analysis and modeling. Projects are discussed in detail.

Estes, John E.↗
NASA NTRS1987

Quick look Atlantic Ocean rain maps for gale

A set of quick look maps of Atlantic Ocean rainfall were made. The maps are based entirely on information extracted from geostationary satellite images. The maps and the process by which they were made are briefly described. The major shortcomings of such a project are pointed out. For convenience the maps are presented in rectangular format. Each map covers one day. Rainfall is contoured in units of millimeters. Rainfall was estimated by the Arkin technique.

Martin, David W.↗
NASA NTRS1987

Remote Sensing Information Sciences Research Group: Santa Barbara Information Sciences Research Group, year 4

Information Sciences Research Group (ISRG) research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. Particular focus in on the needs of the remote sensing research and application science community which will be served by the Earth Observing System (EOS) and Space Station, including associated polar and co-orbiting platforms. The areas of georeferenced information systems, machine assisted information extraction from image data, artificial intelligence and both natural and cultural vegetation analysis and modeling research will be expanded.

Estes, John E.↗
NASA NTRS1987

The factor of scale in remote sensing

A method that measures the spatial structure of images as a function of spatial resolution is presented for selecting the appropriate scale for remote sensing. Graphs are obtained by imaging the scene at fine resolution and then collapsing the image to successively coarser resolutions while calculating the local variance. For the spatial resolution of SPOT and TM imagery, local image variance is relatively high for forested and urban/suburban environments, indicating that information-extraction techniques using texture, context, and mixture modeling are appropriate for these sensor systems. For agricultural environments where local variance is low, more traditional classifiers are appropriate.

Woodcock, Curtis E.↗