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Results for “Automatic Data Processing”

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 NTRS1976

An analysis of metropolitan land-use by machine processing of earth resources technology satellite data

A successful application of state-of-the-art remote sensing technology in classifying an urban area into its broad land use classes is reported. This research proves that numerous urban features are amenable to classification using ERTS multispectral data automatically processed by computer. Furthermore, such automatic data processing (ADP) techniques permit areal analysis on an unprecedented scale with a minimum expenditure of time. Also, classification results obtained using ADP procedures are consistent, comparable, and replicable. The results of classification are compared with the proposed U. S. G. S. land use classification system in order to determine the level of classification that is feasible to obtain through ERTS analysis of metropolitan areas.

Mausel, P. W.↗
NASA NTRS1973

Basic forest cover mapping using digitized remote sensor data and automated data processing techniques

Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.

Coggeshall, M. E.↗
NASA NTRS1973

Discrete regulation of transfer function of a circuit in experimental data automatic collection and processing systems

A device for discrete control of the circuit transfer function in automatic analog data processing systems is reported that coordinates the dynamic range of the vibration level change with the signal range of the processing device output. Experimental verification of the device demonstrates that its maximum control speed does not exceed 0.5 sec for a frequency nonuniformity of about 10%.

Lyubashevskiy, G. S.↗
NASA NTRS1981

An integrated exhaust gas analysis system with self-contained data processing and automatic calibration

An integrated gas analysis system designed to operate in automatic, semiautomatic, and manual modes from a remote control panel is described. The system measures the carbon monoxide, oxygen, water vapor, total hydrocarbons, carbon dioxide, and oxides of nitrogen. A pull through design provides increased reliability and eliminates the need for manual flow rate adjustment and pressure correction. The system contains two microprocessors to range the analyzers, calibrate the system, process the raw data to units of concentration, and provides information to the facility research computer and to the operator through terminal and the control panels. After initial setup, the system operates for several hours without significant operator attention.

Anderson, R. C.↗
NASA NTRSDate not supplied

Automatic Processing of Intensives at GSFC VLBI Analysis Center

VLBI Intensive (INT) sessions are conducted to determine the change in Earth rotation, which is measured as a correction to UT1. This correction varies unpredictably over time. Because UT1 is used in precise navigation, particularly GNSS, rapid turnaround is very important. The decrease of time elapsed from observations to obtained results can be shortened with the automatic data processing of new INT sessions at the analysis stage.

VLBI↗
NASA NTRS1976

Application of satellite data and LARS's data processing techniques to mapping vegetation of the Dismal Swamp

The feasibility of using digital satellite imagery and automatic data processing techniques as a means of mapping swamp forest vegetation was considered, using multispectral scanner data acquired by the LANDSAT-1 satellite. The site for this investigation was the Dismal Swamp, a 210,000 acre swamp forest located south of Suffolk, Va. on the Virginia-North Carolina border. Two basic classification strategies were employed. The initial classification utilized unsupervised techniques which produced a map of the swamp indicating the distribution of thirteen forest spectral classes. These classes were later combined into three informational categories: Atlantic white cedar (Chamaecyparis thyoides), Loblolly pine (Pinus taeda), and deciduous forest. The subsequent classification employed supervised techniques which mapped Atlantic white cedar, Loblolly pine, deciduous forest, water and agriculture within the study site. A classification accuracy of 82.5% was produced by unsupervised techniques compared with 89% accuracy using supervised techniques.

Messmore, J. A.↗