Crop yield estimation method and device, electronic equipment and storage medium

Abstract

The invention relates to a crop yield estimation method and device, electronic equipment and a storage medium, and the method comprises the steps of determining a key time phase of a remote sensing image based on a key phenological period of a to-be-estimated crop; acquiring a remote sensing image of the key time phase, and calculating a plurality of vegetation indexes; respectively constructing a regression model of each vegetation index and the actually measured yield data; sorting the goodness of fit of the regression model of each vegetation index and the actually measured yield data in the same growth period, and screening out the optimal vegetation index of the key time phase; and constructing a yield estimation model based on the optimal vegetation index of the key time phase and the actually measured yield data, and estimating the yield of the crops. The regional crop yield estimation model is constructed on the basis of remote sensing data, in combination with crop growth characteristics, through crop key phenological period analysis, in combination with optimal vegetation indexes and actually measured data, the method can be used for rapid regional yield estimation, and the reliability of a yield estimation result is improved.

Description

technical field [0001] The invention relates to the technical field of crop production, in particular to a method, device, electronic equipment and storage medium for crop yield estimation. Background technique [0002] The dynamic monitoring of crop growth status and timely and accurate prediction of output are of great significance to the formulation of national grain policies, the development of rural economy and foreign grain trade. With the development of remote sensing technology, remote sensing data with high temporal resolution, high spatial resolution and high spectral resolution are constantly emerging, which has continuously improved the fineness and accuracy of remote sensing data in crop yield estimation. Combining remote sensing data with statistical data Predicting crop yield has become a trend in the field of remote sensing yield estimation. The research on remote sensing yield estimation has also developed from a single crop to multiple crops, from small-ar...

AI Technical Summary

Problems solved by technology

[0004] (1) The principle of the empirical statistical model using a single parameter modeling is simple, but the stability is not high;

[0005] (2) The light energy use efficiency model does not take into account the differences in the physiological processes of crops at different growth stages, and is strongly disturbed by human factors;

[0006] (3) The crop growth model has too many parameters, high operating costs, and a long parameter localization cycle. It can only simulate single-point crop yields and then interpolate to the regional range, and the regionalized yield results are inaccurate.

[0007] (4) The construction process of the coupling model is complicated, and the acquisition method of parameters in different regions is unstable. The coupling principle and method still need further research and improvement

[0008] Single modeling image phase, single modeling index, simple and easy to implement model but poor model stability, unsatisfactory production estimation results; or too many modeling parameters, difficult to obtain parameters, high cost of operation, complex model and difficult to implement, The production estimation period is long and it is difficult to popularize it in a large scale. These factors limit the further application and development of regional remote sensing production estimation technology.

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