US 11,900,560 B2 · Generating crop yield predictions of geographic areas

Abstract

Implementations relate to diagnosis of crop yield predictions and/or crop yields at the field- and pixel-level. In various implementations, a first temporal sequence of high-elevation digital images may be obtained that captures a geographic area over a given time interval through a crop cycle of a first type of crop. Ground truth operational data generated through the given time interval and that influences a final crop yield of the first geographic area after the crop cycle may also be obtained. Based on these data, a ground truth-based crop yield prediction may be generated for the first geographic area at the crop cycle's end. Recommended operational change(s) may be identified based on distinct hypothetical crop yield prediction(s) for the first geographic area. Each distinct hypothetical crop yield prediction may be generated based on hypothetical operational data that includes altered data point(s) of the ground truth operational data.

Claims20

Dependent claims

A method implemented using one or more processors, comprising:

obtaining a temporal sequence of high-elevation digital images, wherein the temporal sequence of high elevation digital images capture a geographic area under consideration through at least part of a crop cycle of a selected type of crop growing in the geographic area;
and
generating a ground truth crop yield prediction of the geographic area at the end of the crop cycle of the selected type of crop growing in the geographic area by applying the high-elevation digital images of the temporal sequence and ground truth operational data associated with the geographic area under consideration as input across a machine learning model, wherein the ground truth operational data includes data about one or more of
application of pesticide in the geographic area;
application of fertilizer in the geographic area;
or
crop rotation implemented in the geographic area.

4 more elements

A system comprising one or more processors and memory storing instructions that, in response to execution by the one or more processors, cause the one or more processors to:

obtain a temporal sequence of high-elevation digital images, wherein the temporal sequence of high elevation digital images capture a geographic area under consideration through at least part of a crop cycle of a selected type of crop growing in the geographic area;
and generate a ground truth crop yield prediction of the geographic area at the end of the crop cycle of the selected type of crop growing in the geographic area by applying the high-elevation digital images of the temporal sequence and ground truth operational data associated with the geographic area under consideration as input across a machine learning model, wherein the ground truth operational data includes data about one or more of application of pesticide in the geographic area;
application of fertilizer in the geographic area;
or crop rotation implemented in the geographic area.

1 more element

At least one non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to:

obtain a temporal sequence of high-elevation digital images, wherein the temporal sequence of high elevation digital images capture a geographic area under consideration through at least part of a crop cycle of a selected type of crop growing in the geographic area;
and generate a ground truth crop yield prediction of the geographic area at the end of the crop cycle of the selected type of crop growing in the geographic area by applying the high-elevation digital images of the temporal sequence and ground truth operational data associated with the geographic area under consideration as input across a machine learning model, wherein the ground truth operational data includes data about one or more of application of pesticide in the geographic area;
application of fertilizer in the geographic area;
or crop rotation implemented in the geographic area.

1 more element

Dependencies are inferred from the claim text.

Generating crop yield predictions of geographic areas

Life of this patent

Generating crop yield predictions of geographic areas

Life of this patent

Abstract

Claims20