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At least 1,243 records · Page 69

Digital image transformation and rectification of spacecraft and radar images

The application of digital processing techniques to spacecraft television pictures and radar images is discussed. The use of digital rectification to produce contour maps from spacecraft pictures is described; images with azimuth and elevation angles are converted into point-perspective frame pictures. The digital correction of the slant angle of radar images to ground scale is examined. The development of orthophoto and stereoscopic shaded relief maps from digital terrain and digital image data is analyzed. Digital image transformations and rectifications are utilized on Viking Orbiter and Lander pictures of Mars.

Wu, S. S. C.↗

A method for classification of multisource data using interval-valued probabilities and its application to HIRIS data

A method of classifying multisource data in remote sensing is presented. The proposed method considers each data source as an information source providing a body of evidence, represents statistical evidence by interval-valued probabilities, and uses Dempster's rule to integrate information based on multiple data source. The method is applied to the problems of ground-cover classification of multispectral data combined with digital terrain data such as elevation, slope, and aspect. Then this method is applied to simulated 201-band High Resolution Imaging Spectrometer (HIRIS) data by dividing the dimensionally huge data source into smaller and more manageable pieces based on the global statistical correlation information. It produces higher classification accuracy than the Maximum Likelihood (ML) classification method when the Hughes phenomenon is apparent.

Kim, H.↗

Combining multispectral and ancillary data in remote sensing using interval-valued probabilities

This paper presents a method for classifying multisource data in remote sensing and geographic information systems using interval-valued probabilities. In this method, each data source is considered as an information source which provides a body of statistical evidence. In order to integrate information obtained from multiple data sources, the method adopts Dempster's rule for combining multiple bodies of evidence. Preliminary experiments have been undertaken to illustrate the use of the method in a supervised ground-cover classification on multispectral data combined with digital elevation data. They demonstrate the ability of the method in capturing information provided by inexact and incomplete evidence when there are not enough training samples to estimate statistical parameters.

Kim, H.↗

A method for classification of multisource data using interval-valued probabilities and its application to HIRIS data

A method of classifying multisource data in remote sensing is presented. The proposed method considers each data source as an information source providing a body of evidence, represents statistical evidence by interval-valued probabilities, and uses Dempster's rule to integrate information based on multiple data sources. The method is applied to the problems of ground-cover classification of multispectral data combined with digital terrain data such as elevation, slope, and aspect. Then this method is applied to simulated 201-band High Resolution Imaging Spectrometer (HIRIS) data by dividing the dimensionally huge data source into smaller and more manageable pieces based on the global statistical correlation information. It produces higher classification accuracy than the Maximum Likelihood (ML) classification method when the Hughes phenomenon is apparent.

Kim, H.↗

Computer Aids Delineation Of Boundaries In Farmlands

Computer-aided stratification (CAS) procedure developmental procedure of image-processing computer equipment and programs partly automating delineation of boundaries between areas. These areas, "primary sampling units", are images of primarily agricultural lands composed by melding digital Landsat Thematic Mapper data and Digital Line Graph data from United States Geological Survey. CAS output data used as inputs for subsequent sampling procedures from which statistics on uses of agricultural lands developed.

Slyle, R.↗

Improving classification of crop residues using digital land ownership data and Landsat TM imagery

Plant residue on the surface of cultivated soils in Miami County, Indiana is analyzed in terms of quantity and type with Landsat TM data to generate information for a conservation program for agricultural soil. The Landsat data are enhanced with land-ownership data in a geographic information system to facilitate classification with maximum-likelihood, minimum-distance, and neural-network classifiers. The most effective classifications resulted from the use of the neural network on the enhanced TM data.

Zhuang, Xin↗

Appraisal of digital terrain elevation data for low-altitude flight

The use of terrain elevation databases in advanced guidance and navigation systems has greatly expanded. However, the limitations and accuracies of these databases must be considered and established prior to safe system flight evaluation. A simple approach to quantify reasonable flight limits is presented and evaluated for a helicopter guidance system dependent on a terrain database. The flight test evaluated involved a helicopter equipped with a Global Positioning System (GPS) receiver and radar altimeter, and a ground station GPS receiver which provided improved helicopter positioning. The precision navigation and radar altimeter data was acquired while flying low-altitude missions in south-central Pennsylvania. The aircraft-determined terrain elevations were compared with the terrain predicted by the Defense Mapping Agency (DMA) Level 1 terrain elevation data for the same area. The results suggest a safe set clearance altitude of 220 ft for flight testing of a DMA-based guidance avionic in the same area.

Zelenka, Richard E.↗

Appraisal of digital terrain elevation data for low-altitude flight

The use of terrain elevation databases in advanced guidance and navigation systems has greatly expanded. However, the limitations and accuracies of these databases must be considered and established prior to safe system flight evaluation. A simple approach to quantify reasonable flight limits is presented and evaluated for a helicopter guidance system dependent on a terrain database. The flight test evaluated involved a helicopter equipped with a Global Positioning System (GPS) receiver and radar altimeter, and a ground station GPS receiver which provided improved helicopter positioning. The precision navigation and radar altimeter data was acquired while flying low-altitude missions in south-central Pennsylvania. The aircraft-determined terrain elevations were compared with the terrain predicted by the Defense Mapping Agency (DMA) Level 1 terrain elevation data for the same area. The results suggest a safe set clearance altitude of 220 ft for flight testing of a DMA-based guidance avionic in the same area.

Zelenka, Richard E.↗

Identifying Objects via Encased X-Ray-Fluorescent Materials - the Bar Code Inside

Systems for identifying objects by means of x-ray fluorescence (XRF) of encased labeling elements have been developed. The XRF spectra of objects so labeled would be analogous to the external bar code labels now used to track objects in everyday commerce. In conjunction with computer-based tracking systems, databases, and labeling conventions, the XRF labels could be used in essentially the same manner as that of bar codes to track inventories and to record and process commercial transactions. In addition, as summarized briefly below, embedded XRF labels could be used to verify the authenticity of products, thereby helping to deter counterfeiting and fraud. A system, as described above, is called an encased core product identification and authentication system (ECPIAS). The ECPIAS concept is a modified version of that of a related recently initiated commercial development of handheld XRF spectral scanners that would identify alloys or detect labeling elements deposited on the surfaces of objects. In contrast, an ECPIAS would utilize labeling elements encased within the objects of interest. The basic ECPIAS concept is best illustrated by means of an example of one of several potential applications: labeling of cultured pearls by labeling the seed particles implanted in oysters to grow the pearls. Each pearl farmer would be assigned a unique mixture of labeling elements that could be distinguished from the corresponding mixtures of other farmers. The mixture would be either incorporated into or applied to the surfaces of the seed prior to implantation in the oyster. If necessary, the labeled seed would be further coated to make it nontoxic to the oyster. After implantation, the growth of layers of mother of pearl on the seed would encase the XRF labels, making these labels integral, permanent parts of the pearls that could not be removed without destroying the pearls themselves. The XRF labels would be read by use of XRF scanners, the spectral data outputs of which would be converted to alphanumeric data in a digital equivalent data system (DEDS), which is the subject of the previous article. These alphanumeric data would be used to track the pearls through all stages of commerce, from the farmer to the retail customer.

Schramm, Harry F.↗

Use of remotely sensed data for assessing forest stand conditions in the Eastern United States

Techniques for the detection, classification, and measurement of forest disturbances, using digital Landsat data for three study areas (Pennsynvania, North Carolina, and Maine) are reported. Results with respect to (1) the delineation and assessment of forest damage due to the use of two forest insect defoliators, and (2) qualitative assessment of the Multispectral Scanner (MSS) and the Thematic Mapper data for delineating forest stand characteristics are presented. Key results include a development of a statewide MSS digital data base and associated image-processing techniques for accurately delineating insect-damaged and healthy forest areas. For classification of broad land-cover classes which are spectrally homogeneous, the accuracy yielded by the use of either MSS data or TM Simulator data is similar. However, the TMS data provided 20 percent accuracy improvement over the MSS results when detailed (Level III) forest classes were mapped.

Williams, D. L.↗

Decimal digit generator for commutated data: A Concept

Perform analog-to-digital conversion on input signal with staircase circuit having 10% resolution, convert digital result to analog voltage, subtract it from original input signal; read out feedback signals as decimal digit representation during one clock phase and servo-error difference between input and feedback as analog portion during following clock phase.

Rusk, S. J.↗

Convective rainfall estimation from digital GOES-1 infrared data

An investigation was conducted to determine the feasibility of developing and objective technique for estimating convective rainfall from digital GOES-1 infrared data. The study area was a 240 km by 240 km box centered on College Station, Texas (Texas A and M University). The Scofield and Oliver (1977) rainfall estimation scheme was adapted and used with the digital geostationary satellite data. The concept of enhancement curves with respect to rainfall approximation is discussed. Raingage rainfall analyses and satellite-derived rainfall estimation analyses were compared. The correlation for the station data pairs (observed versus estimated rainfall amounts) for the convective portion of the storm was 0.92. It was demonstrated that a fairly accurate objective rainfall technique using digital geostationary infrared satellite data is feasible. The rawinsonde and some synoptic data that were used in this investigation came from NASA's Atmospheric Variability Experiment, AVE 7.

Sickler, G. L.↗

Techniques for digital enhancement of Landsat MSS data using an Apple II+ microcomputer

The information provided by remotely sensed data collected from orbiting platforms has been useful in many research fields. Particularly convenient for evaluation are generally digital data stored on computer compatible tapes (CCT's). The major advantages of CCT's are the quality of the data and the accessibility to computer manipulation. Minicomputer systems are widely used for the required computer processing operations. However, microprocessor-related technological advances make it now possible to process CCT data with computing systems which can be obtained at a much lower price than minicomputer systems. A detailed description is provided of the design considerations of a microcomputer-based Digital Image Analysis System (DIAS). Particular attention is given to the algorithms which are incorporated for eighter edge enhancement or smoothing Landsat multispectral scanner data.

Harrington, J. A., Jr.↗

Geometric aspects in digital analysis of Multi-Spectral Scanner (MSS) data

Present automated systems of interpretation which apply pattern recognition techniques on MSS data do not fully consider the geometry of the acquisition system. In an effort to improve the usefulness of the MSS data when digitally treated, geometric aspects are analyzed and discussed. Attempts to correct for scanner instabilities in position and orientation by affine and polynomial transformations, as well as by modified collinearity equations are described. Methods of accounting for panoramic and relief effects are also discussed. It is anticipated that reliable area as well as position determinations can be accomplished during the process of automatic interpretation. A concept for a unified approach to the treatment of remote sensing data, both metric and nonmetric is presented.

Mikhail, E. M.↗

Predictive Phenomics Initiative Project Dataset Catalog Collection

The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.

59 BASIC BIOLOGICAL SCIENCES↗