Seasonal field-level yield forecast

Through deep learning models and feature engineering processing of satellite image data, the accuracy and efficiency of crop yield prediction at the field level are solved, and efficient yield prediction at the field level is achieved.

CN113196287BActive Publication Date: 2024-12-20MONSANTO TECHNOLOGY LLC
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Patent Information

Application Number
CN201980084807.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Priority Date
2018-12-21
Filing Date
2019-12-23
Publication Date
2024-12-20
Estimated Expiration
2039-12-23

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Abstract

In an embodiment, a digital image of a farmland is received at an agricultural intelligent processing system. Each digital image includes a set of pixels having pixel values, and each pixel value of a pixel includes a plurality of spectral band intensity values. Each spectral band intensity value describes the spectral band intensity of a band in a plurality of electromagnetic radiation bands. For each farmland in the farmland, the spectral band intensity value of each band is preprocessed at the field level using the digital image of the farmland, resulting in a preprocessed intensity value. The preprocessed intensity value is provided as an input to a machine learning model. The model generates a predicted yield value for each field. The predicted yield value is used to update the field yield map of the farmland for forecasting, and can be displayed via a graphical user interface (GUI) of a client computing device.
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