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  • 1
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    LACIE - An application of meteorology for United States and foreign wheat assessment (1980)
    In:  Other Sources
    Details
    Publication Date: 2011-08-17
    Description: This paper describes the overall Large Area Crop Inventory Experiment technical approach utilizing the global weather-reporting network and the Landsat satellite to make a quasi-operational application of existing research results, and the accomplishments of this cooperative experiment in utilizing the weather information. Global weather data were utilized in preparing timely yield estimates for selected areas of the U.S. Great Plains, the U.S.S.R. and Canada. Additionally, wheat yield models were developed and pilot tested for Brazil, Australia, India and Argentina. The results of the work show that heading dates for wheat in North America can be predicted with an average absolute error of about 5 days for winter wheat and 4 days for spring wheat. Independent tests of wheat yield models over a 10-year period for the U.S. Great Plains produced a root-mean-square error of 1.12 quintals per hectare (q/ha) while similar tests in the U.S.S.R. produced an error of 1.31 q/ha. Research designed to improve the initial capability is described as is the rationale for further evolution of a capability to monitor global climate and assess its impact on world food supplies.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Journal of Applied Meteorology; 19; Jan. 198
    Format: text
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  • 2
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    Experiment design session: Wheat yield model development (1978)
    In:  Other Sources
    Details
    Publication Date: 2016-03-08
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Briefing Mater. for Tech. Presentations, Vol. A: The LACIE Symp.; p 31-48
    Format: text
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  • 3
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    Development of LACIE CCEA-1 weather/wheat yield models (1979)
    In:  Other Sources
    Details
    Publication Date: 2016-03-08
    Description: The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: NASA. Johnson Space Center Proc. of Tech. Sessions, Vol. 1 and 2; p 99-108
    Format: text
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  • 4
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    Argentina corn yield model (1984)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: A model based on multiple regression was developed to estimate corn yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the corn-growing area. Predictor variables for the model were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. A trend variable was included for the years 1965 to 1980 since an increasing trend in yields due to technology was observed between these years.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E84-10105 , NASA-CR-173374 , YM-N4-04456 , JSC-18908 , NAS 1.26:173374
    Format: application/pdf
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  • 5
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    Argentina wheat yield model (1984)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: Five models based on multiple regression were developed to estimate wheat yields for the five wheat growing provinces of Argentina. Meteorological data sets were obtained for each province by averaging data for stations within each province. Predictor variables for the models were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. Buenos Aires was the only province for which a trend variable was included because of increasing trend in yield due to technology from 1950 to 1963.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E84-10101 , NASA-CR-173370 , YM-N4-04457 , JSC-18909 , NAS 1.26:173370
    Format: application/pdf
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  • 6
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    Brazil soybean yield covariance model (1984)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E84-10104 , NASA-CR-173373 , YM-N4-04455 , JSC-18907 , NAS 1.26:173373
    Format: application/pdf
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  • 7
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    Argentina soybean yield model (1984)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E84-10102 , NASA-CR-173371 , YM-N4-04453 , JSC-18905 , NAS 1.26:173371
    Format: application/pdf
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  • 8
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    Brazil wheat yield covariance model (1984)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: A model based on multiple regression was developed to estimate wheat yields for the wheat growing states of Rio Grande do Sul, Parana, and Santa Catarina in Brazil. The meteorological data of these three states were pooled and the years 1972 to 1979 were used to develop the model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E84-10103 , NASA-CR-173372 , YM-N4-04454 , JSC-18906 , NAS 1.26:173372
    Format: application/pdf
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  • 9
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    LACIE transition protect, FY 1978-1979: Reanalysis of CCEA 1 US Great Plains wheat yield models (1978)
    In:  CASI
    Details
    Publication Date: 2019-06-27
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E79-10062 , NASA-TM-79927 , LACIE-00472 , JSC-13740 , CCEA-TR-78-3
    Format: application/pdf
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  • 10
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    Large Area Crop Inventory Experiment (LACIE). an Index for Estimating Wheat Yield in Australia (1977)
    In:  CASI
    Details
    Publication Date: 2019-06-27
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E79-10128 , NASA-CR-158137 , LACIE-00502 , JSC-11699 , CCEA-TN-76-3
    Format: application/pdf
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