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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Agricultural applications of remote sensing: A true life adventure

A study of agricultural applications of remote sensing with a major US agricultural firm was undertaken in mid-1973. The study continued for eighteen months, and covered the areas of crop monitoring and management as well as large scale crop inventories. Pilot programs in the application of aircraft remote sensing and LANDSAT data were conducted. An operational aircraft survey program for ranch management has subsequently been implemented by the agricultural firm. LANDSAT data was successfully used to produce a ninety-seven percent accurate inventory of cotton over 4.8 million acres of California's San Joaquin Valley.

Schaller, E. S.↗
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.↗
NASA NTRS1977

Agricultural aviation user requirement priorities

The results are given of a research project pertaining to the development of agricultural aviation user requirement priorities. The raw data utilized in the project was obtained from the National Agricultural Aviation Association. A specially configured poll, developed by the Actuarial Research Corporation was used to solicit responses from NAAA members and others. The primary product of the poll is the specification of seriousness as determined by the respondents for some selected agricultural aviation problem areas identified and defined during the course of an intensive analysis by the Actuarial Research Corporation.

Kaplan, R. L.↗
NASA NTRS1978

Sensor needs for agricultural applications

The peculiarities of agricultural remotely sensed data requirements evoke special sensor requirements. Vegetative species do not possess significantly different spectral signature at given phases of their development cycle. Hence, the key to their discriminability is the phasing of the phenologic cycle of the subject species. Significant improvements in classification can be obtained by consistently employing multi-temporal observations taken at specific times during the year. The present approach to agricultural data processing results in extracted data equal to approximately .05% of the acquired data. This paper discusses the derivation of agricultural peculiar requirements and the benefits to the end-to-end processing system by judicial utilization and placement of key editing functions such as sample segment extraction, cloudy image removal, sample registration and the elimination of redundant data.

Golden, H.↗
NASA NTRS1979

Landsat-simulating radiometer for agricultural remote sensing

The reliability of a Landsat-simulating ground-based spectral radiometer for use in agricultural remote sensing was investigated. Significant correlation coefficients in all wavebands except Band 7 were found to exist between Landsat computer compatible tape (CCT) and ground-based radiometric data from several corn fields. No significant correlations were found within data from small grain fields. Combined data from several common agricultural crops yielded significant correlation coefficients in the wavebands most commonly employed in agricultural remote sensing. It was also found that sun angle within certain limits of a given day had minimal effect on ground-based radiometric measurements taken from a fallow and barley field.

Lemme, G. D.↗
NASA NTRS1978

Principal component greenness transformation in multitemporal agricultural Landsat data

A data compression technique for multitemporal Landsat imagery which extracts phenological growth pattern information for agricultural crops is described. The principal component greenness transformation was applied to multitemporal agricultural Landsat data for information retrieval. The transformation was favorable for applications in agricultural Landsat data analysis because of its physical interpretability and its relation to the phenological growth of crops. It was also found that the first and second greenness eigenvector components define a temporal small-grain trajectory and nonsmall-grain trajectory, respectively.

Abotteen, R. A.↗
NASA NTRS1981

Market assessment of photovoltaic power systems for agricultural applications in the Philippines

The market potential in the Philippines for stand alone photovoltaic (P/V) systems in agriculture was assessed. Applications include: irrigation, postharvest operation, food and fiber processing and storage, and livestock and fisheries operations. Power and energy use profiles for many applications as well as assessments of business, government and financial climate for P/V sales are described. Many characteristics of the Philippine agriculture and energy sector favorably influence the use of P/V systems. However, serious and significant barriers prevent achieving the technically feasible, cost competitive market for P/V systems in the agricultural sector. The reason for the small market is the limited availability capital for financing P/V systems. It is suggested that innovative financing schemes and promotional campaigns should be devised.

Cabraal, R. A.↗
NASA NTRS1984

Basic principles, methodology, and applications of remote sensing in agriculture

The basic principles of remote sensing applied to agriculture and the methods used in data analysis are described. Emphasis is placed on the importance of developing a methodology that may help crop forecast, basic concepts of spectral signatures of vegetation, the methodology of the LANDSAT data utilization in agriculture, and the remote sensing program application of INPE (Institute for Space Research) in agriculture.

Moreira, M. A.↗
NASA NTRS1984

Exploring the use of structural models to improve remote sensing agricultural estimates

Satellite estimates of agricultural characteristics often are not sufficiently precise for reliable use in small geographical regions. The precision of estimates of agricultural characteristics such as crop proportions and leaf area indexes can be increased by modeling ground observations as a function of satellite estimates. Linear regression models using least squares estimators of the model parameters are most often advocated as an appropriate methodology; however, least squares estimation requires that the predictor variables are measured without error, an unreasonable assumption for this application. An alternative estimation methodology which assumes that both the response variables (ground observations) and the predictor variables (satellite estimates) are measured with error involves the use of linear structural models. The application of linear structural models to the estimation of agricultural characteristics using satellite spectral measurements is examined.

Gunst, R. F.↗
NASA NTRS1985

Nastran's Application in Agricultural Engineering

Finite element analysis has been recognized as a valuable solution method by agricultural engineers. NASTRAN has been obtained by the Agricultural Engineering Department at the University of Georgia. The NASTRAN Thermal Analyzer has been used in the teaching program for an undergraduate course in heat transfer and will be used for a new graduate course in finite element analysis. The NASTRAN Thermal Analyzer has also been applied to several research problems in the Agricultural Engineering Department.

Vanwicklen, G. L.↗
NASA NTRS1984

A summary of the history of the development of automated remote sensing for agricultural applications

An historical account is given of the development of technology for the processing of satellite-acquired multispectral data aimed at the identification of the type, condition, and ontogenic stages of agricultural areas. During 1972 and 1973, research established the feasibility of automating digital classification for the processing of large volumes of Landsat MSS data. This capability was successfully demonstrated during the Large Area Crop Inventory Experiment, which estimated wheat crop production on a global basis. This achievement in turn led to the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing, which investigated other portions of the electromagnetic spectrum and expanded the study of key commercial crops in important agricultural areas.

Macdonald, R. B.↗
NASA NTRS1985

Evaluation of AIS Data for Agronomic and Rangeland Vegetation: Preliminary Results for August 1984 Flight over Nebraska Sandhills Agricultural Laboratory

Since 1978 scientists from the Center for Agricultural Meteorology and Climatology at the University of Nebraska have been conducting research at the Sandhills Agricultural Laboratory on the effects of water stress on crop growth, development and yield using remote sensing techniques. We have been working to develop techniques, both remote and ground-based, to monitor water stress, phenological development, leaf area, phytomass production and grain yields of corn, soybeans and sorghum. Because of the sandy soils and relatively low rainfall at the site it is an excellent location to study water stress without the necessity of installing expensive rainout shelters. The primary objectives of research with the airborne imaging spectrometer (AIS) data collected during an August 1984 flight over the Sandhills Agricultural Laboratory are to evaluate the potential of using AIS to: (1) discriminate crop type; (2) to detect subtle architectural differences that exist among different cultivars or hybrids of agronomic crops; (3) to detect and quantify, if possible, the level of water stress imposed on the crops; and (4) to evaluate leaf area and biomass differences for different crops.

Blad, B. L.↗
NASA NTRS1986

Applications of TIMS data in agricultural areas and related atmospheric considerations

While much of traditional remote sensing in agricultural research was limited to the visible and reflective infrared, advances in thermal infrared remote sensing technology are adding a dimension to digital image analysis of agricultural areas. The Thermal Infrared Multispectral Scanner (TIMS) an airborne sensor having six bands over the nominal 8.2 to 12.2 m range, offers the ability to calculate land surface emissivities unlike most previous singular broadband sensors. Preliminary findings on the utility of the TIMS for several agricultural applications and related atmospheric considerations are discussed.

Pelletier, R. E.↗
NASA NTRS1989

Computer-aided boundary delineation of agricultural lands

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

Cheng, Thomas D.↗
NASA NTRS1990

Global climate change and US agriculture

Agricultural productivity is expected to be sensitive to global climate change. Models from atmospheric science, plant science, and agricultural economics are linked to explore this sensitivity. Although the results depend on the severity of climate change and the compensating effects of carbon dioxide on crop yields, the simulation suggests that irrigated acreage will expand and regional patterns of U.S. agriculture will shift. The impact of the U.S. economy strongly depends on which climate model is used.

Adams, Richard M.↗
NASA NTRS2000

Mapping Agricultural Crops with AVIRIS Spectra in Washington State

Spectroscopy is used in the laboratory to measure the molecular components and concentrations of plant constituents to answer questions about the plant type, status, and health. Imaging spectrometers measure the upwelling spectral radiance above the Earth's surface as images. Ideally, imaging spectrometer data sets should be used to understand plant type, plant status, and health of plants in an agricultural setting. An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data set was acquired over agricultural fields near Wallula, Washington on July 23rd, 1997. AVIRIS measures upwelling radiance spectra through 224 spectral channels with contiguous 10-nm sampling from 400 to 2500 run in the solar-reflected spectrum. The spectra are measured as images of 11 by up to 800 km with 20-m spatial resolution. The spectral images measured by AVIRIS represent the integrated signal resulting from: the solar irradiance; two way transmittance and scattering of the atmosphere; the absorptions and scattering of surface materials; as well as the spectral, radiometric and spatial response functions of AVIRIS. This paper presents initial research to derive properties of the agricultural fields near Wallula from the calibrated spectral images measured by AVIRIS near the top of the atmosphere.

Green, Robert O.↗
NASA NTRS1998

Mapping Agricultural Crops with AVIRIS Spectra in Washington State

Spectroscopy is used in the laboratory to measure the molecular components and concentrations of plant constituents to answer questions about the plant type, status, and health. Imaging spectrometers measure the upwelling spectral radiance above the Earth's surface as images. Ideally, imaging spectrometer data sets should be used to understand plant type, plant status, and health of plants in an agricultural setting. An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data set was acquired over agricultural fields near Wallula, Washington on July 23rd, 1997. AVIRIS measures upwelling radiance spectra through 224 spectral channels with contiguous 10-nm sampling from 400 to 2500 nm in the solar-reflected spectrum. The spectra are measured as images of 11 by up to 800 km with 20-m spatial resolution. The spectral images measured by AVIRIS represent the integrated signal resulting from: the solar irradiance; two way transmittance and scattering of the atmosphere; the absorptions and scattering of surface materials; as well as the spectral, radiometric and spatial response functions of AVIRIS. This paper presents initial research to derive properties of the agricultural fields near Wallula from the calibrated spectral images measured by AVIRIS near the top of the atmosphere.

Green, Robert↗