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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Development of flight experiment work performance and workstation interface requirements, part 1. Technical report and appendices A through G

A skill requirement definition method was applied to the problem of determining, at an early stage in system/mission definition, the skills required of on-orbit crew personnel whose activities will be related to the conduct or support of earth-orbital research. The experiment data base was selected from proposed experiments in NASA's earth orbital research and application investigation program as related to space shuttle missions, specifically those being considered for Sortie Lab. Concepts for two integrated workstation consoles for Sortie Lab experiment operations were developed, one each for earth observations and materials sciences payloads, utilizing a common supporting subsystems core console. A comprehensive data base of crew functions, operating environments, task dependencies, task-skills and occupational skills applicable to a representative cross section of earth orbital research experiments is presented. All data has been coded alphanumerically to permit efficient, low cost exercise and application of the data through automatic data processing in the future.

Hatterick, R. G.↗
NASA NTRS1974

The utility of ERTS-1 data for applications in land use classification

A comprehensive study has been undertaken to determine the extent to which conventional image interpretation and computer-aided (spectral pattern recognition) analysis techniques using ERTS-1 data could be used to detect, identify (classify), locate, and measure current land use over large geographic areas. It can be concluded that most of the level 1 and 2 categories in the USGS Circular no. 671 can be detected in the Houston-Gulf Coast area using a combination of both techniques for analysis. These capabilities could be exercised over larger geographic areas, however, certain factors such as different vegetative cover, topography, etc. may have to be considered in other geographic regions. The best results in identification (classification), location, and measurement of level 1 and 2 type categories appear to be obtainable through automatic data processing of multispectral scanner computer compatible tapes.

Dornbach, J. E.↗
NASA NTRS1973

Development of a computer-aided procedure for the national program of inspection of dams

An effort was undertaken to determine the utility of ERTS-1 MSS data, together with automatic data processing (ADP) techniques, to detect and locate surface water, and transfer the related technology to the Texas Water Rights Commission (TWRC). A test site was selected, ERTS-1 MSS and ancillary data obtained, and existent ADP classification programs applied. During the course of this effort a linear discriminant function was developed. The results were evaluated for potential candidates for a transferable procedure. A computer-aided technique using a linear discriminant function was selected and recommended, for inclusion in an operational system, which met detection and location criteria. Specifically, evaluation of the selected computer-aided procedure for the test site resulted in the detection of 100 percent of areas of surface water 10 acres or greater in areal extent and the geographic location of areas classified as water to a positional accuracy of 1000 feet or closer. The procedure was recommended for inclusion in an operational computer-aided procedure for transfer to TWRC.

Source record↗
NASA NTRS1974

LACIE ADP/PI joint case study: ADP analysis guidelines

The procedure is described which was used to train automatic data processing (ADP) analysts to process ERTS 1 imagery from a 5 nm by 6 nm area in Delisle, Canada, and to estimate wheat acreage using training fields provided by photointerpreters. The exercise also served to evaluate and test current large area crop inventory experiment (LACIE) procedures.

Minter, T. C.↗
NASA NTRS1974

Evaluation of satellite remote sensing and automatic data techniques for characterization of wetlands and coastal marshlands

The author has identified the following significant results. The evaluation was conducted in a humid swamp and marsh area of southern Louisiana. ERTS digital multispectral scanner data was compared with similar data gathered by intermediate altitude aircraft. Automatic data processing was applied to several data sets to produce simulated color infrared images, analysis of single bands, thematic maps, and surface classifications. These products were used to determine the effectiveness of satellites to monitor accretion of land, locate aquatic plants, determine water characteristics, and identify marsh and forest species. The results show that to some extent all of these can be done with satellite data. It is most effective for monitoring accretion and least effective in locating aquatic plants. The data sets used show that the ERTS data is superior in mapping quality and accuracy to the aircraft data. However, in some applications requiring high resolution or maximum use of intermittent clear weather conditions, data gathering by aircraft is preferable. Data processing costs for equivalent areas are about three times greater for aircraft data than ERTS data. This is primarily because of the larger volume of data generated by the high resolution aircraft system.

Cartmill, R. H.↗
NASA NTRS1974

A demonstration of ERTS-1 analog and digital techniques applied to strip mining in Maryland and West Virginia

The largest contour strip mining operations in western Maryland and West Virginia are located within the Georges Creek and the Upper Potomac Basins. These two coal basins lie within the Georges Creek (Wellersburg) syncline. The disturbed strip mine areas were delineated with the surrounding geological and vegetation features using ERTS-1 data in both analog (imagery) and digital form. The two digital systems used were: (1) the ERTS-Analysis system, a point-by-point digital analysis of spectral signatures based on known spectral values, and (2) the LARS Automatic Data Processing System. The digital techniques being developed will later be incorporated into a data base for land use planning. These two systems aided in efforts to determine the extent and state of strip mining in this region. Aircraft data, ground verification information, and geological field studies also aided in the application of ERTS-1 imagery to perform an integrated analysis that assessed the adverse effects of strip mining. The results indicated that ERTS can both monitor and map the extent of strip mining to determine immediately the acreage affected and indicate where future reclamation and revegetation may be necessary.

Anderson, A. T.↗
NASA NTRS1974

Spectral mapping of soil organic matter

Multispectral remote sensing data were examined for use in the mapping of soil organic matter content. Computer-implemented pattern recognition techniques were used to analyze data collected in May 1969 and May 1970 by an airborne multispectral scanner over a 40-km flightline. Two fields within the flightline were selected for intensive study. Approximately 400 surface soil samples from these fields were obtained for organic matter analysis. The analytical data were used as training sets for computer-implemented analysis of the spectral data. It was found that within the geographical limitations included in this study, multispectral data and automatic data processing techniques could be used very effectively to delineate and map surface soils areas containing different levels of soil organic matter.

Kristof, S. J.↗
NASA NTRS1975

Crop Identification Technolgy Assessment for Remote Sensing (CITARS). Volume 1: Task design plan

A plan for quantifying the crop identification performances resulting from the remote identification of corn, soybeans, and wheat is described. Steps for the conversion of multispectral data tapes to classification results are specified. The crop identification performances resulting from the use of several basic types of automatic data processing techniques are compared and examined for significant differences. The techniques are evaluated also for changes in geographic location, time of the year, management practices, and other physical factors. The results of the Crop Identification Technology Assessment for Remote Sensing task will be applied extensively in the Large Area Crop Inventory Experiment.

Hall, F. G.↗
NASA NTRS1976

Results from the Crop Identification Technology Assessment for Remote Sensing (CITARS) project

The author has identified the following significant results. It was found that several factors had a significant effect on crop identification performance: (1) crop maturity and site characteristics, (2) which of several different single date automatic data processing procedures was used for local recognition, (3) nonlocal recognition, both with and without preprocessing for the extension of recognition signatures, and (4) use of multidate data. It also was found that classification accuracy for field center pixels was not a reliable indicator of proportion estimation performance for whole areas, that bias was present in proportion estimates, and that training data and procedures strongly influenced crop identification performance.

Bauer, M. E.↗
NASA NTRS1975

Crop identification technology assessment for remote sensing (CITARS). Volume 10: Interpretation of results

The CITARS was an experiment designed to quantitatively evaluate crop identification performance for corn and soybeans in various environments using a well-defined set of automatic data processing (ADP) techniques. Each technique was applied to data acquired to recognize and estimate proportions of corn and soybeans. The CITARS documentation summarizes, interprets, and discusses the crop identification performances obtained using (1) different ADP procedures; (2) a linear versus a quadratic classifier; (3) prior probability information derived from historic data; (4) local versus nonlocal recognition training statistics and the associated use of preprocessing; (5) multitemporal data; (6) classification bias and mixed pixels in proportion estimation; and (7) data with differnt site characteristics, including crop, soil, atmospheric effects, and stages of crop maturity.

Bizzell, R. M.↗
NASA NTRS1976

ERTS-1 data applied to strip mining

Two coal basins within the western region of the Potomac River Basin contain the largest strip-mining operations in western Maryland and West Virginia. The disturbed strip-mine areas were delineated along with the surrounding geological and vegetation features by using ERTS-1 data in both analog and digital form. The two digital systems employed were (1) the ERTS analysis system, a point-by-point digital analysis of spectral signatures based on known spectral values and (2) the LARS automatic data processing system. These two systems aided in efforts to determine the extent and state of strip mining in this region. Aircraft data, ground-verification information, and geological field studies also aided in the application of ERTS-1 imagery to perform an integrated analysis that assessed the adverse effects of strip mining. The results indicated that ERTS can both monitor and map the extent of strip mining to determine immediately the acreage affected and to indicate where future reclamation and revegetation may be necessary.

Anderson, A. T.↗
NASA NTRS1975

Results from the crop identification technology assessment for remote sensing /CITARS/ project

The CITARS (Crop Identification Technology Assessment for Remote Sensing) task design, objectives, and results are reviewed along with relevant conclusions and recommendations. The principal assessment concern crop identification performance for corn and soybeans in six sites in Illinois and Indiana. Use of quantitative measures of classification performance and statistical evaluations of the results have been important parts of the technology assessment. Relation of crop and sensor characteristics is discussed. Factors affecting crop identification performance are identified as crop maturity and site characteristics, type of single-date automatic data processing procedure used for local recognition, nonlocal recognition with and without processing for extension of recognition signatures, and use of multidate or multitemporal data. In particular, the probability of correct classification of field center pixels is not well correlated and thus is not a reliable indicator of proportion estimation performance.

Bizzell, R. M.↗
NASA NTRS1976

The ten-ecosystem study investigation plan

With the continental United States divided into ten forest and grassland ecosystems, the Ten Ecosystem Study (TES) is designed to investigate the feasibility and applicability of state-of-the-art automatic data processing remote sensing technology to inventory forest, grassland, and water resources by using Land Satellite data. The study will serve as a prelude to a possible future nationwide remote sensing application to inventory forest and rangeland renewable resources. This plan describes project design and phases, the ten ecosystem, data utilization and output, personnel organization, resource requirements, and schedules and milestones.

Kan, E. P.↗
NASA NTRS1976

Water resources planning for rivers draining into Mobile Bay

The application of remote sensing, automatic data processing, modeling and other aerospace related technologies to hydrological engineering and water resource management are discussed for the entire river drainage system which feeds the Mobile Bay estuary. The adaptation and implementation of existing mathematical modeling methods are investigated for the purpose of describing the behavior of Mobile Bay. Of particular importance are the interactions that system variables such as river flow rate, wind direction and speed, and tidal state have on the water movement and quality within the bay system.

April, G. C.↗
NASA NTRS1979

Nationwide forestry applications program. Ten-Ecosystem Study (TES) site 7, Weld County, Colorado

The author has identified the following significant results. The best dates for automatic data processing analysis appeared to be in midsummer. The level 2 separation of grassland, water, and other resources was reasonably successful, but the level 3 separation of grassland into cultivated (growing crops) and weeds did not appear feasible. Low simulated inventory proportions of grassland indicated that the restricted inventory signature was not representative of all grassland classes and could not be extended with acceptable accuracy.

Weaver, J. E.↗
NASA NTRS1979

Ten-Ecosystem Study (TES) site 9, Washington County, Missouri

The author has identified the following significant results. Sufficient spectral separability exists among softwood, hardwood, grassland, and water to develop a level 2 classification and inventory. Using the tested automatic data processing technology, softwood and grassland signatures can be extended across the county with acceptable accuracy; with more dense sampling, the hardwood signature probably could also be extended. Fall was found to be the best season for mapping this ecosystem.

Echert, W. H.↗
NASA NTRS1978

SCATS: SRB Cost Accounting and Tracking System handbook

The Solid Rocket Booster Cost Accounting and Tracking System (SCATS) which is an automatic data processing system designed to keep a running account of the number, description, and estimated cost of Level 2, 3, and 4 changes is described. Although designed specifically for the Space Shuttle Solid Rocket Booster Program, the ADP system can be used for any other program that has a similar structure for recording, reporting, and summing numbers and costs of changes. The program stores the alpha-numeric designators for changes, government estimated costs, proposed costs, and negotiated value in a MIRADS (Marshall Information Retrieval and Display System) format which permits rapid access, manipulation, and reporting of current change status. Output reports listing all changes, totals of each level, and totals of all levels, can be derived for any calendar interval period.

Zorv, R. B.↗
NASA NTRS1978

The Ten-Ecosystem Study - Landsat ADP mapping of forest and rangeland in the United States

The Ten-Ecosystem Study was designed to assess the maximum information content of Landsat data and its utility for large area classification using a uniform technical approach on the 10 generalized forest and rangeland ecosystems of the United States. Conclusions on the feasibility of using Landsat remote sensing automatic data processing methods, selecting the best seasons, analyzing costs and the effects of site complexity, miscellaneous analysis, problems, and recommendations were derived from 2 years of study, the project being three-fourths completed.

Kan, E. P.↗