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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Diurnal and annual temperature variations in the 30-60 km region as indicated by statistical analysis of rocketsonde temperature data.

The relatively large amount of rocketsonde data now available for selected stations together with representative estimates of the solar radiation corrections has been utilized to establish the phases and amplitudes of the diurnal temperature oscillations from 30 to 60 km. Once the magnitude of the solar radiation errors and the diurnal temperature oscillations are established, these values are used to obtain new estimates of the actual mean temperatures for each calendar month.

Hoxit, L. R.↗
NASA NTRS1972

Evaluation of remote sensing in control of pink cotton bollworm

The author has identified the following significant results. This investigation is attempting to evaluate the use of a satellite in monitoring the cotton production regulation program of the State of California as an aid in controlling pink bollworm infestation in the southern deserts of California. Color combined images of ERTS-1 multispectral images simulating color infrared are being used in crop identification. The status of each field is mapped from the imagery and is then compared to ground surveys taken at the time of each ERTS-1 overflight. Correlation has been to date 100%. A computer analysis will be performed to compare field status with the crop calendar in order to identify crops. Correlation is expected to be 80 to 90%. Cotton fields, because of their state regulated season which is exactly coincident with no other crop, are expected to be easily identified.

Lewis, L. N.↗
NASA NTRS1973

Semi-automatic crop inventory from sequential ERTS-1 imagery

The detection of a newly introduced crop into the Imperial (California) Valley by sequential ERTS-1 imagery is proving that individual crop types can be identified by remote sensing techniques. Initial results have provided an extremely useful product for water agencies. A system for the identification of field conditions enables the production of a statistical summary within two to three days of receipt of the ERTS-1 imagery. The summary indicates the total acreage of producing crops and irrigated planted crops currently demanding water and further indicates freshly plowed fields that will be demanding water in the near future. Relating the field conditions to the crop calendar of the region by means of computer techniques will provide specific crop identification for the 8000 plus fields.

Johnson, C. W.↗
NASA NTRS1973

Determination of land use in Minnesota by automatic interpretation of ERTS MSS data

This program aims to determine the feasibility of identifying land use in Minnesota by automatic interpretation of ERTS-MSS data. Ultimate objectives include establishment of land use delineation and quantification by computer processing with a minimum of human operator interaction. This implies not only that reflectivity as a function of calendar time can be catalogued effectively, but also that the effects of uncontrolled variables can be identified and compensated. Clouds are the major uncontrollable data pollutant, so part of the initial effort is devoted to determining their effect and the construction of a model to help correct or justifiably ignore affected data. Other short range objectives are to identify and verify measurements giving results of importance to land managers. Lake-counting is a prominent example. Open water is easily detected in band 7 data with some support from either band 4 or band 5 to remove ambiguities. Land managers and conservationists commission studies periodically to measure water bodies and total water count within specified areas.

Zirkle, R. E.↗
NASA NTRS1973

A computer program to determine the possible daily release window for sky target experiments

A computer program is presented which is designed to determine the daily release window for sky target experiments. Factors considered in the program include: (1) target illumination by the sun at release time and during the tracking period; (2) look angle elevation above local horizon from each tracking station to the target; (3) solar depression angle from the local horizon of each tracking station during the experimental period after target release; (4) lunar depression angle from the local horizon of each tracking station during the experimental period after target release; and (5) total sky background brightness as seen from each tracking station while viewing the target. Program output is produced in both graphic and data form. Output data can be plotted for a single calendar month or year. The numerical values used to generate the plots are furnished to permit a more detailed review of the computed daily release windows.

Michaud, N. H.↗
NASA NTRS1973

Evaluation of remote sensing in control of pink bollworm in cotton

The author has identified the following significant results. The main objective is to evaluate the use of a satellite in monitoring the cotton production regulation program of the State of California as an aid in controlling pink bollworm infestation in the southern deserts of California. Color combined images of ERTS-1 multispectral images simulating color infrared are being used for crop identification. The status of each field (i.e., crop, bare, harvested, wet, plowed) is mapped from the imagery and is then compared to ground survey information taken at the time of ERTS-1 overflights. A computer analysis has been performed to compare field and satellite data to a crop calendar. Correlation to data has been 97% for field condition. Actual crop identification varies; cotton identification is only 63% due to lack of full season coverage.

Lewis, L. N.↗
NASA NTRS1974

The October 1973 space shuttle traffic model, revision 2

Traffic model data for the space shuttle for calendar years 1980 through 1991 are presented along with some supporting and summary data. This model was developed from the 1973 NASA Payload Model, dated October 1973, and the NASA estimate of the 1973 Non-NASA/Non-DoD Payload Model. The estimates for the DoD flights included are based on the 1971 DoD Mission Model.

Source record↗
NASA NTRS1974

The October 1973 expendable launch vehicle traffic model, revision 2

Traffic model data for current expendable launch vehicles (assuming no space shuttle) for calendar years 1980 through 1991 are presented along with some supporting and summary data. This model was based on a payload program equivalent in scientific return to the October 1973 NASA Payload Model, the NASA estimated non NASA/non DoD Payload Model, and the 1971 DoD Mission Model.

Source record↗
NASA NTRS1974

Evaluation of remote sensing in control of pink bollworm in cotton

The author has identified the following significant results. This investigation is to evaluate the use of a satellite in monitoring the cotton production regulation program of the State of California as an aid in controlling pink bollworm infestation in the southern deserts of California. Color combined images of ERTS-1 multispectral images simulating color infrared are being used for crop identification. The status of each field (crop, bare, harvested, wet, plowed) is mapped from the imagery and is then compared to ground survey information taken at the time of ERTS-1 overflights. A computer analysis has been performed to compare field and satellite data to a crop calendar. Correlation to date has been 97% for field condition. Actual crop identification varies; cotton identification is only 63% due to lack of full season coverage.

Lewis, L. N.↗
NASA NTRS1974

HILTOP supplement: Heliocentric interplanetary low thrust trajectory optimization program, supplement 1

Modifications and improvements are described that were made to the HILTOP electric propulsion trajectory optimization computer program during calendar years 1973 and 1974. New program features include the simulation of power degradation, housekeeping power, launch asymptote declination optimization, and powered and unpowered ballistic multiple swingby missions with an optional deep space burn.

Mann, F. I.↗
NASA NTRS1976

Hydrogen Energy: A bibliography with abstracts

Bibliographic series cites documents relating to use of hydrogen as energy carrier. In addition to cumulative volume, annual supplement is available for 1974, and quarterly update program serves 1975 and current calendar year.

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NASA NTRS1975

Revised prediction (estimation) of Cape Kennedy, Florida, wind speed profile

The prediction of the wind profile maximum speed at Cape Kennedy, Florida, is made for any selected calendar data. The prediction is based on a normal probability distribution model with 15 years of smoothed input data and is static in the sense that no dynamic principles of persistence or synoptic features are considered. Comparison with similar predictions based on 6 years of data shows the same general pattern, but the variability decreased with the increase of sample size.

Guttman, N. B.↗
NASA NTRS1975

Plan for the uniform mapping of earth resources and environmental complexes from Skylab imagery. Assessment of natural vegetation, environmental, and crop analogs

The author has identified the following significant results. For interpreting a wide range of natural vegetation analogs, S-190A color infrared and the ERTS-1 color composite were consistently more useful than were conventional color or black and white photos. Color infrared was superior for five vegetation analogs while color was superior for only three. The errors in identification appeared to associate more with black and white single band images than with multiband color. For rice crop analogs, spectral and spatial discriminations both contribute to the usefulness of images for data collection. Tests and subjective analyses conducted in this study indicated that the spectral bands exploited in color infrared film were the most useful for agricultural crop analysis. Accuracy of crop identification on any single date of Skylab images was less than that of multidate analysis due to differences in crop calendar, cultural practices used, rice variety, planting date, planting method, water use, fertilization, disease, or mechanical problems.

Poulton, C. E.↗
NASA NTRS1975

Satellite-tracking and earth-dynamics research programs

The activities and progress in the satellite tracking and earth dynamics research during the first half of calendar year 1975 are described. Satellite tracking network operations, satellite geodesy and geophysics programs, GEOS 3 project support, and atmospheric research are covered.

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NASA NTRS1976

Lacie phase 1 Classification and Mensuration Subsystem (CAMS) rework experiment

An experiment was designed to test the ability of the Classification and Mensuration Subsystem rework operations to improve wheat proportion estimates for segments that had been processed previously. Sites selected for the experiment included three in Kansas and three in Texas, with the remaining five distributed in Montana and North and South Dakota. The acquisition dates were selected to be representative of imagery available in actual operations. No more than one acquisition per biophase were used, and biophases were determined by actual crop calendars. All sites were worked by each of four Analyst-Interpreter/Data Processing Analyst Teams who reviewed the initial processing of each segment and accepted or reworked it for an estimate of the proportion of small grains in the segment. Classification results, acquisitions and classification errors and performance results between CAMS regular and ITS rework are tabulated.

Chhikara, R. S.↗
NASA NTRS1976

Scheduling algorithm for mission planning and logistics evaluation users' guide

The scheduling algorithm for mission planning and logistics evaluation (SAMPLE) program is a mission planning tool composed of three subsystems; the mission payloads subsystem (MPLS), which generates a list of feasible combinations from a payload model for a given calendar year; GREEDY, which is a heuristic model used to find the best traffic model; and the operations simulation and resources scheduling subsystem (OSARS), which determines traffic model feasibility for available resources. The SAMPLE provides the user with options to allow the execution of MPLS, GREEDY, GREEDY-OSARS, or MPLS-GREEDY-OSARS.

Chang, H.↗
NASA NTRS1975

Cropland acreage estimates from temporal, multispectral ERTS-1 data

Temporal, multispectral Earth Resources Technology Satellite (ERTS-1) images as pertinent to cropland acreage estimates are illustrated and discussed. A cropland classifier is described that evaluates approximately registered, temporal, and multispectral digital ERTS-1 data acquired over a 14 section test site in central Iowa during 1973. Satellite-derived acreage estimates are compared with estimates derived from low-level images. Discrepancies between these estimates are discussed. Satellite coverage critically timed with a crop development calendar is noted to improve classifier effectiveness.

Carlson, R. E.↗
NASA NTRS1976

Benefits to world agriculture through remote sensing

Remote sensing of agricultural land permits crop classification and mensuration which can lead to improved forecasts of production. This technique is particularly important for nations which do not already have an accurate agricultural reporting system. Better forecasts have important economic effects. International grain traders can make better decisions about when to store, buy, and sell. Farmers can make better planting decisions by taking advantage of production estimates for areas out of phase with their own agricultural calendar. World economic benefits will accrue to both buyers and sellers because of increased food supply and price stabilization. This paper reviews the econometric models used to establish this scenario and estimates the dollar value of benefits for world wheat as 200 million dollars annually for the United States and 300 to 400 million dollars annually for the rest of the world.

Buffalano, A. C.↗