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Winter wheat late freezing disaster monitoring and yield prediction method based on Internet of Things and remote sensing inversion

The invention discloses a winter wheat later freezing disaster monitoring and yield prediction method based on Internet of Things and remote sensing inversion, and aims to solve the technical problemthat the yield prediction is directly carried out without considering the influence of winter wheat later freezing disaster. The invention designs a winter wheat later freezing disaster monitoring method based on Internet of Things and remote sensing inversion and a construction method of a winter wheat yield prediction model, and provides a winter wheat yield prediction method. According to the invention, the occurrence of the winter wheat later freezing disaster can be accurately and accurately monitored, the extreme climate is quantified, the decision guidance and suggestions are provided for the timely disaster detection and post-disaster remedy; the influence of the extreme climate on the winter wheat yield is reduced, a yield estimation model is further perfected, and an Internet ofThings and remote sensing data fusion method is provided for the yield prediction; a new idea is provided for the intelligent decision diagnosis of the winter wheat production in Hebei Province, the guidance and suggestions are provided for the agricultural production decision, and the data support is provided for the wheat production and the market transaction.
Owner:HENAN AGRICULTURAL UNIVERSITY
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