A method and system for real-time yield estimation of grain crops

Abstract

The invention discloses a method and a system for real-time estimation of the grain crop yield. The method comprises the following steps of: acquiring historical data; calculating the anomaly of the enhanced vegetation index according to the enhanced vegetation index in different years and different periods; taking the anomaly of the i-th period enhanced vegetation index as the independent variable and the estimated yield difference as the dependent variable, the linear regression equation was constructed, and the estimated yield model in i-th period was obtained. The estimated difference is the difference between the statistical output and the trend output or the difference between the statistical output and the estimated value of the i-1 period; the anomaly of the enhanced vegetation index in the i-th period is substituted into the estimated production model of the i-th period to obtain the first estimating fluctuation value of the i period; calculating the estimated value of the model in the i-th period according to the estimated fluctuation value of the i-th period and the estimated production value of the i-th period; calculating the error of the estimated production model inthe i-th period; using the estimation model of the i-th period to correct the error for the estimated value of the model in the i-th period, and the estimated value of the i-th period is obtained. Theinvention can realize the accurate and effective and real-time estimation of the production of food crops.

Description

technical field [0001] The invention relates to the field of yield estimation of grain crops, in particular to a method and system for real-time yield estimation of grain crops. Background technique [0002] Timely, accurate and effective grain crop yield estimation is of great significance for coping with changes in international grain prices, stabilizing food security, and making agricultural production management decisions. Since the development of modern agriculture, a series of technical methods for crop yield estimation have achieved varying degrees of success in predicting yield. According to the methods used, they can be divided into statistical yield estimation, meteorological yield estimation, agronomic yield estimation, and remote sensing yield estimation. [0003] Statistical yield estimation is to predict yield by considering the relationship between various statistical factors affecting crop yield and crop yield as a whole, and the commonly used one is trend yi...

AI Technical Summary

Problems solved by technology

However, remote sensing technology is still subject to various influences such as weather, the same object with different spectrum, and different objects with the same spectrum, so it cannot achieve theoretical timely effectiveness.

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