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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Identification and area estimation of agricultural crops by computer classification of Landsat MSS data

Landsat Multispectral Scanner (MSS) data covering a three-county area in northern Illinois were classified using computer-aided techniques as corn, soybeans, or 'other.' Recognition of test fields was 80% accurate. County estimates of the area of corn and soybeans agreed closely with those made by the USDA. Results of the use of a priori information in classification, techniques to produce unbiased area estimates, and the use of temporal and spatial features for classification are discussed. The extendability, variability, and size of training sets, wavelength band selection, and spectral characteristics of crops were also investigated.

Bauer, M. E.↗
NASA NTRS1979

The Large Area Crop Inventory Experiment /LACIE/ - A summary of three years' experience

Aims, history and schedule of the Large Area Crop Inventory Experiment (LACIE) conducted by NASA, USDA and NOAA from 1974-1977 are described. The LACIE experiment designed to research, develop, apply and evaluate a technology to monitor wheat production in important regions throughout the world (U.S., Canada, USSR, Brasil) utilized quantitative multispectral data collected by Landsat in concert with current weather data and historical information. The experiment successfully exploited computer data and mathematical models to extract timely corp information. A follow-on activities for the early 1980's is planned focusing especially on the early warning of changes affecting production and quality of renewable resources and commodity production forecast.

Erb, R. B.↗
NASA NTRS1981

Beef grading by ultrasound

Reflections in ultrasonic A-scan signatures of beef carcasses indicate USDA grade. Since reflections from within muscle are determined primarily by fat/muscle interface, richness of signals is direct indication of degree of marbling and quality. Method replaces subjective sight and feel tests by individual graders and is applicable to grade analysis of live cattle.

Gammell, P. M.↗
NASA NTRS1979

Proceedings of Technical Sessions, Volumes 1 and 2: the LACIE Symposium

The technical design of the Large Area Crop Inventory Experiment is examined and data acquired over 3 global crop years is analyzed with respect to (1) sampling and aggregation; (2) growth size estimation; (3) classification and mensuration; (4) yield estimation; and (5) accuracy assessment. Seventy-nine papers delivered at conference sessions cover system implementation and operation; data processing systems; experiment results and accuracy; supporting research and technology; and the USDA application test system.

Source record↗
NASA NTRS1979

Data base design for a worldwide multicrop information system

A description of the USDA Application Test System data base design approach and resources is presented. The data is described in detail by category, with emphasis on those characteristics which influenced the design most. It was concluded that the use of a generalized data base in support of crop assessment is a sound concept. The IDMS11 minicomputer base system is recommended for this purpose.

Driggers, W. G.↗
NASA NTRS1979

The application test system: Technical approach and system design

An insight is provided of the technical approach which was applied to the system design of the USDA Applications Test Program. Included are: identification of requirements, assessment of remote sensing contributions, evaluations of existing techniques, and cost effective development of a system design which utilizes techniques and procedures consistent with requirements.

Benson, J. L.↗
NASA NTRS1981

A study of poultry processing plant noise control techniques

A number of techniques can be used to reduce noise in poultry processing plants. In general, covering the ceiling with a noise-absorbing medium is a practical first step. Once the reflected noise levels are abated, treatment of specific identifiable noise courses can take place. The development, flammability, and mechanical properties of acoustic panels to be vertically suspended from the ceiling are discussed as well as the covers need to comply with USDA cleanability requirements. The isolation of drive motors and pumps from large expansive areas, the muffling of pneumatic devices, and the insulation of ice chutes are methods of source quieting. Proper maintenance of machinery and vibration monitoring are also needed to reduce hearing damage risk and to improve worker productivity and employee/supervisor relations.

Wyvill, J. C.↗
NASA NTRS1980

Calculations of the spectral nature of the microwave emission from soils

The brightness temperatures for a set of soil profiles observed at USDA facilities in Arizona and Georgia were calculated at the wavelengths of 2.8, 6, 11, 21, and 49 cm using a coherent radiative transfer model. The soil moisture sampling depth is found to be a function of wavelength and is in the range 0.06 to 0.1 of a wavelength. The thermal sampling depth also depends on wavelength and is approximately equal to one wavelength at dry soil condition and 0.1 - 0.5 wavelengths at wet soil conditions. Calculated values of emissivity show strong diurnal variations when the soils are wet, while there is little diurnal change when the soil is dry. The soil moistures within the four depth intervals of 0-2, 0-5, 0-9, and 0-15 cm were parameterized as function of the calculated emissivity and brightness temperature. Best-fit parameters and correlation coefficients are presented for five wavelengths. Interrelationships among the effective temperature, surface temperature, and emissivity are displayed.

Mo, T.↗
NASA NTRS1981

Notes for Brazil sampling frame evaluation trip

Field notes describing a trip conducted in Brazil are presented. This trip was conducted for the purpose of evaluating a sample frame developed using LANDSAT full frame images by the USDA Economic and Statistics Service for the eventual purpose of cropland production estimation with LANDSAT by the Foreign Commodity Production Forecasting Project of the AgRISTARS program. Six areas were analyzed on the basis of land use, crop land in corn and soybean, field size and soil type. The analysis indicated generally successful use of LANDSAT images for purposes of remote large area land use stratification.

Horvath, R.↗
NASA NTRS1981

AgRISTARS: Agriculture and resources inventory surveys through aerospace remote sensing

The major objectives and FY 1980 accomplishments are described of a long term program designed to determine the usefulness, cost, and extent to which aerospace remote sensing data can be integrated into existing or future USDA systems to improve the objectivity, reliability, timeliness, and adequacy of information. A general overview, the primary and participating agencies, and the technical highlights of each of the following projects are presented: early warning/crop condition assessment; foreign commodity production forecasting; yield model development; supporting research; soil moisture; domestic crops and land cover; renewable resources inventory; and conservation and pollution.

Source record↗
NASA NTRS1981

A multi-frequency radiometric measurement of soil moisture content over bare and vegetated fields

A USDA Beltsville Agricultural Research Center site was used for an experiment in which soil moisture remote sensing over bare, grass, and alfalfa fields was conducted over a three-month period using 0.6 GHz, 1.4 GHz, and 10.6 GHz Dicke-type microwave radiometers mounted on mobile towers. Ground truth soil moisture content and ambient air and sil temperatures were obtained concurrently with the radiometric measurements. Biomass of the vegetation cover was sampled about once a week. Soil density for each of the three fields was measured several times during the course of the experiment. Results of the radiometric masurements confirm the frequency dependence of moisture sensing sensitivity reduction reported earlier. Observations over the bare, wet field show that the measured brightness temperature is lowest at 5.0 GHz and highest of 0.6 GHz frequency, a result contrary to expectation based on the estimated dielectric permittivity of soil water mixtures and current radiative transfer model in that frequency range.

Wang, J. R.↗
NASA NTRS1981

Evaluation of large area crop estimation techniques

The performance of the USDAs EDITOR system is evaluated. The system processes Landsat imagery and estimates crop hectarage for large areas based on a regression estimator developed on a sample with known ground truth. It is found that use of multitemporal data over unitemporal significantly improves the hectarage estimates, and a 15% reduction in the r-squared of the regression occurs when independent and jackknifed test sets are used to evaluate the performance of the estimator. When an alternative clustering algorithm, CLASSY, is substituted for the current EDITOR method, estimator performance is improved with reduced need for analyst decisions. It is recommended that the CLASSY clustering algorithm and some form of jackknifing be implemented on EDITOR.

Amis, M. L.↗
NASA NTRS1981

Evaluation of the Williams-type model for barley yields in North Dakota and Minnesota

The Williams-type yield model is based on multiple regression analysis of historial time series data at CRD level pooled to regional level (groups of similar CRDs). Basic variables considered in the analysis include USDA yield, monthly mean temperature, monthly precipitation, soil texture and topographic information, and variables derived from these. Technologic trend is represented by piecewise linear and/or quadratic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-1979) demonstrate that biases are small and performance based on root mean square appears to be acceptable for the intended AgRISTARS large area applications. The model is objective, adequate, timely, simple, and not costly. It consideres scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Barnett, T. L.↗
NASA NTRS1982

Comparison of CEAS and Williams-type models for spring wheat yields in North Dakota and Minnesota

The CEAS and Williams-type yield models are both based on multiple regression analysis of historical time series data at CRD level. The CEAS model develops a separate relation for each CRD; the Williams-type model pools CRD data to regional level (groups of similar CRDs). Basic variables considered in the analyses are USDA yield, monthly mean temperature, monthly precipitation, and variables derived from these. The Williams-type model also used soil texture and topographic information. Technological trend is represented in both by piecewise linear functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test of each model (1970-1979) demonstrate that the models are very similar in performance in all respects. Both models are about equally objective, adequate, timely, simple, and inexpensive. Both consider scientific knowledge on a broad scale but not in detail. Neither provides a good current measure of modeled yield reliability. The CEAS model is considered very slightly preferable for AgRISTARS applications.

Barnett, T. L.↗
NASA NTRS1982

User's appraisal of yield model evaluation criteria

The five major potential USDA users of AgRISTAR crop yield forecast models rated the Yield Model Development (YMD) project Test and Evaluation Criteria by the importance placed on them. These users were agreed that the "TIMELINES" and "RELIABILITY" of the forecast yields would be of major importance in determining if a proposed yield model was worthy of adoption. Although there was considerable difference of opinion as to the relative importance of the other criteria, "COST", "OBJECTIVITY", "ADEQUACY", AND "MEASURES OF ACCURACY" generally were felt to be more important that "SIMPLICITY" and "CONSISTENCY WITH SCIENTIFIC KNOWLEDGE". However, some of the comments which accompanied the ratings did indicate that several of the definitions and descriptions of the criteria were confusing.

Warren, F. B.↗
NASA NTRS1981

AgRISTARS - Plans and first-year achievements

The results of the agriculture and resources inventory surveys through aerospace remote sensing (AgRISTARS) program managed by the USDA for exploring the use of satellite data for domestic and global commodity information needs are discussed. The program was intended to gather early warning of changes affecting production and quality of commodities and renewable resources, for predicting commodity production, land use classification and quantification, for inventories and assessments of renewable resources, land productivity measurements, assessment of conservation practices, and for pollution detection and impact evaluation. Up to 20 crop/region combinations in 7 countries were covered by the experiments, which comprised NOAA 6 and Landsat data analyses. Attempts to reduce variances through improved machine classification techniques are reported, together with soil moisture profiling, and the use of airborne sensors for providing comparative data.

Hall, F. G.↗
NASA NTRS1982

The use of large-area spectral data in wheat yield estimation

Large-area relations between satellite spectral data and end-of-season crop yield were investigated. Green Index Number (GIN) values from Landsat MSS data of sample segments throughout the U.S. Great Plains winter wheat belt in 1978 were correlated to county USDA-SRS reported yields. A linear relation between GIN and yield appeared to exist up to GIN values of 40 or 50, covering cases of severe to moderate stress. In a test on 1978 Texas winter wheat at the county level, GIN values for sample segments in the counties were used in conjunction with an agronomic-meteorological yield model. The combined fit explained significantly more of the observed yield variation at the county level than the agromet model alone.

Barnett, T. L.↗
NASA NTRS1984

Meteorological models for estimating phenology of corn

Knowledge of when critical crop stages occur and how the environment affects them should provide useful information for crop management decisions and crop production models. Two sources of data were evaluated for predicting dates of silking and physiological maturity of corn (Zea mays L.). Initial evaluations were conducted using data of an adapted corn hybrid grown on a Typic Agriaquoll at the Purdue University Agronomy Farm. The second phase extended the analyses to large areas using data acquired by the Statistical Reporting Service of USDA for crop reporting districts (CRD) in Indiana and Iowa. Several thermal models were compared to calendar days for predicting dates of silking and physiological maturity. Mixed models which used a combination of thermal units to predict silking and days after silking to predict physiological maturity were also evaluated. At the Agronomy Farm the models were calibrated and tested on the same data. The thermal models were significantly less biased and more accurate than calendar days for predicting dates of silking. Differences among the thermal models were small. Significant improvements in both bias and accuracy were observed when the mixed models were used to predict dates of physiological maturity. The results indicate that statistical data for CRD can be used to evaluate models developed at agricultural experiment stations.

Daughtry, C. S. T.↗