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Related Experiment Videos

Global crop forecasting.

R B Macdonald, F G Hall

    Science (New York, N.Y.)
    |May 16, 1980
    PubMed
    Summary
    This summary is machine-generated.

    Accurate global crop production forecasts are vital for food security. A new satellite and weather reporting system, tested in the Large Area Crop Inventory Experiment (LACIE), shows promise for reliable international crop assessments.

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    Area of Science:

    • Agricultural science
    • Remote sensing technology
    • International trade

    Background:

    • Global food security is challenged by reliance on imports, mirroring oil dependency.
    • Current foreign crop production data is often unreliable, outdated, and subject to economic manipulation.
    • The United States, as a major food exporter, requires timely and accurate international crop information.

    Purpose of the Study:

    • To develop and test a novel crop inventory system for more reliable foreign crop production forecasting.
    • To address the inadequacy and untimeliness of existing international agricultural data.
    • To assess the feasibility of using satellite remote sensing and weather data for crop monitoring.

    Main Methods:

    • Implementation of a crop inventory system integrating satellite remote sensing and global weather data.

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  • Testing the system through the Large Area Crop Inventory Experiment (LACIE).
  • Utilizing real-time data for forecasting agricultural output.

    • Main Results:

    • The system successfully produced a real-time forecast for U.S.S.R. wheat production in 1977.
    • The results validated the effectiveness of the integrated satellite and weather data approach.
    • The experiment demonstrated the potential for accurate crop yield prediction.

    Conclusions:

    • The tested crop inventory system is effective for real-time crop production forecasting.
    • The methodology shows promise for expansion to other countries and crop types.
    • This approach can significantly improve the reliability of global agricultural intelligence.