IP Library › Granted Patent US 12,277,761
Granted Patent B2
US 12,277,761 · App. 18/435,087 · Granted Apr 15, 2025

Remote sensing algorithms for mapping regenerative agriculture

Inventors: Eli Kellen Melaas (Needham, MA); Bobby Harold Braswell (Portsmouth, NH); Douglas Kane Bolton (Boston, MA)
Assignee: Indigo Ag, Inc.
G06V20/188G06V20/13
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Quick Facts
Patent No.
US 12,277,761
App. No.
18/435,087
Granted
Apr 15, 2025
Kind
B2
Abstract

This invention relates to methods for determining adoption and impact of regenerative farming practices. Embodiments of these methods, take satellite imagery and weather data as inputs, process those data according to methods of the present invention, and produce outputs which indicate whether a specific farming practice (for example, no-till or cover cropping) was adopted for a particular field or region for a particular season.

Claims (67)

1. A method of detecting a cover crop, the method comprising:

based on a time-series of satellite imagery, determining a plurality of peaks in a vegetation index;

for a candidate peak, determining a first inflection point between the candidate peak and a preceding peak and a second inflection point between the candidate peak and a subsequent peak;

determining a plurality of time segments between the first inflection point and the candidate peak, each of the plurality of time segments preceding the candidate peak, wherein:

a first time segment of the plurality of time segments is determined to extend from the first inflection point to a first interim point that precedes the candidate peak, the first interim point being at a first predefined percentage of a normalized amplitude of the candidate peak in the vegetation index;

a second time segment of the plurality of time segments is determined to extend from the first interim point to a second interim point that precedes the candidate peak, the second interim point being at a second predefined percentage of the normalized amplitude of the candidate peak in the vegetation index, the second predefined percentage exceeding the first predefined percentage, the second predefined percentage being less than the normalized amplitude of the candidate peak;

a third time segment of the plurality of time segments is determined to extend from the second interim point to a third interim point that precedes the candidate peak, the third interim point being at a third predefined percentage of the normalized amplitude of the candidate peak in the vegetation index, the third predefined percentage exceeding the second predefined percentage, the second predefined percentage being less than the normalized amplitude of the candidate peak; and

the first time segment, the second time segment, and the third time segment are not of predefined lengths;

determining one or more summary statistics for each of the plurality of time segments between the first inflection point and the candidate peak and for one or more summary statistics between the second inflection point and the candidate peak, wherein each of the one or more summary statistics is calculated across an entirety of its respective time segment; and

providing the one or more summary statistics to a trained classifier, and receiving therefrom an indication of a presence or absence of a cover crop at the candidate peak.

2. The method of claim 1 , wherein the vegetation index is Normalized Difference Vegetation Index (NDVI).

3. The method of claim 1 , wherein the first predefined percentage is 15% of the normalized amplitude of the candidate peak.

4. The method of claim 3 , wherein the second predefined percentage is 50% of the normalized amplitude of the candidate peak.

5. The method of claim 4 , wherein the third time segment is determined to extend from 50% of the normalized amplitude of the candidate peak to 85% of the normalized amplitude of the candidate peak.

6. The method of claim 1 , wherein the one or more summary statistics comprise one or more of:

a rate of change in the vegetation index,

a duration,

a maximum value of the vegetation index,

an average value of the vegetation index,

a median value of the vegetation index, and

a 90% percentile value of the vegetation index.

7. The method of claim 1 , wherein the trained classifier is a random forest, k-nearest neighbor, or XGBoost classifier.

8. A non-transitory computer-readable medium comprising memory with instructions encoded thereon for detecting a cover crop, the instructions, when executed by one or more processors, causing the one or more processors to perform operations comprising:

based on a time-series of satellite imagery, determining a plurality of peaks in a vegetation index;

for a candidate peak, determining a first inflection point between the candidate peak and a preceding peak and a second inflection point between the candidate peak and a subsequent peak;

determining a plurality of time segments between the first inflection point and the candidate peak, each of the plurality of time segments preceding the candidate peak, wherein:

a first time segment of the plurality of time segments is determined to extend from the first inflection point to a first interim point that precedes the candidate peak, the first interim point being at a first predefined percentage of a normalized amplitude of the candidate peak in the vegetation index;

a second time segment of the plurality of time segments is determined to extend from the first interim point to a second interim point that precedes the candidate peak, the second interim point being at a second predefined percentage of the normalized amplitude of the candidate peak in the vegetation index, the second predefined percentage exceeding the first predefined percentage, the second predefined percentage being less than the normalized amplitude of the candidate peak;

a third time segment of the plurality of time segments is determined to extend from the second interim point to a third interim point that precedes the candidate peak, the third interim point being at a third predefined percentage of the normalized amplitude of the candidate peak in the vegetation index, the third predefined percentage exceeding the second predefined percentage, the second predefined percentage being less than the normalized amplitude of the candidate peak; and

the first time segment, the second time segment, and the third time segment are not of predefined lengths;

determining one or more summary statistics for each of the plurality of time segments between the first inflection point and the candidate peak and for one or more summary statistics between the second inflection point and the candidate peak, wherein each of the one or more summary statistics is calculated across an entirety of its respective time segment; and

providing the one or more summary statistics to a trained classifier, and receiving therefrom an indication of a presence or absence of a cover crop at the candidate peak.

9. The non-transitory computer-readable medium of claim 8 , wherein the vegetation index is Normalized Difference Vegetation Index (NDVI).

10. The non-transitory computer-readable medium of claim 8 , wherein the first predefined percentage is 15% of the normalized amplitude of the candidate peak.

11. The non-transitory computer-readable medium of claim 10 , wherein the second predefined percentage is 50% of the normalized amplitude of the candidate peak.

12. The non-transitory computer-readable medium of claim 11 , wherein the third time segment is determined to extend from 50% of the normalized amplitude of the candidate peak to 85% of the normalized amplitude of the candidate peak.

13. The non-transitory computer-readable medium of claim 8 , wherein the one or more summary statistics comprise one or more of:

a rate of change in the vegetation index,

a duration,

a maximum value of the vegetation index,

an average value of the vegetation index,

a median value of the vegetation index, and

a 90% percentile value of the vegetation index.

14. The non-transitory computer-readable medium of claim 8 , wherein the trained classifier is a random forest, k-nearest neighbor, or XGBoost classifier.

15. A system comprising:

a non-transitory computer-readable medium with instructions encoded thereon for detecting a cover crop; and

one or more processors that, when executing the instructions, are caused to perform operations comprising:

based on a time-series of satellite imagery, determining a plurality of peaks in a vegetation index;

for a candidate peak, determining a first inflection point between the candidate peak and a preceding peak and a second inflection point between the candidate peak and a subsequent peak;

determining a plurality of time segments between the first inflection point and the candidate peak, each of the plurality of time segments preceding the candidate peak, wherein:

a first time segment of the plurality of time segments is determined to extend from the first inflection point to a first interim point that precedes the candidate peak, the first interim point being at a first predefined percentage of a normalized amplitude of the candidate peak in the vegetation index;

a second time segment of the plurality of time segments is determined to extend from the first interim point to a second interim point that precedes the candidate peak, the second interim point being at a second predefined percentage of the normalized amplitude of the candidate peak in the vegetation index, the second predefined percentage exceeding the first predefined percentage, the second predefined percentage being less than the normalized amplitude of the candidate peak;

a third time segment of the plurality of time segments is determined to extend from the second interim point to a third interim point that precedes the candidate peak, the third interim point being at a third predefined percentage of the normalized amplitude of the candidate peak in the vegetation index, the third predefined percentage exceeding the second predefined percentage, the second predefined percentage being less than the normalized amplitude of the candidate peak; and

the first time segment, the second time segment, and the third time segment are not of predefined lengths;

determining one or more summary statistics for each of the plurality of time segments between the first inflection point and the candidate peak and for one or more summary statistics between the second inflection point and the candidate peak, wherein each of the one or more summary statistics is calculated across an entirety of its respective time segment; and

providing the one or more summary statistics to a trained classifier, and receiving therefrom an indication of a presence or absence of a cover crop at the candidate peak.

16. The system of claim 15 , wherein the vegetation index is Normalized Difference Vegetation Index (NDVI).

17. The system of claim 15 , wherein the first predefined percentage is 15% of the normalized amplitude of the candidate peak.

18. The system of claim 17 , wherein the second predefined percentage is 50% of the normalized amplitude of the candidate peak.

19. The system of claim 18 , wherein the third time segment is determined to extend from 50% of the normalized amplitude of the candidate peak to 85% of the normalized amplitude of the candidate peak.

20. The system of claim 15 , wherein the one or more summary statistics comprise one or more of:

a rate of change in the vegetation index,

a duration,

a maximum value of the vegetation index,

an average value of the vegetation index,

a median value of the vegetation index, and

a 90% percentile value of the vegetation index.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 15, 2026
From: INDIGO AG, LLC
To: INDIGO AGRICULTURE, INC.
Reel/Frame 075279/0881 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 15, 2026
From: INDIGO AGRICULTURE, INC.
To: TERION AI, INC.
Reel/Frame 075280/0039 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 2, 2024
From: MELAAS, ELI KELLEN; BRASWELL, BOBBY HAROLD; BOLTON, DOUGLAS KANE
To: INDIGO AG, INC.
Reel/Frame 067297/0723 →
Continuity (5)
Continuation 18156814 · Jan 19, 2023
Continuation PCTUS2021042542 · Jul 21, 2021
Provisional Application 63178278 · Apr 22, 2021
Provisional Application 63054688 · Jul 21, 2020
Related Publication 20240257515A1 · Aug 1, 2024
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