METHOD AND SYSTEM TO MAP BIOLOGICAL PESTS IN AGRICULTURAL FIELDS USING REMOTELY-SENSED DATA FOR FIELD SCOUTING AND TARGETED CHEMICAL APPLICATION

• US 20150201605A1
• Filed: 04/01/2015
• Published: 07/23/2015
• Est. Priority Date: 05/13/2011
• Status: Active Grant

• Current Assignee: Climate Pty., Ltd.
• Original Assignee: HydroBio, Inc. (Bayer AG)
• Inventors: Groeneveld, David P.
• Granted Patent: US 9,756,844 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A01G 22/00 Cultivation of specific crops or plants not otherwise provided for
• CPC Class Codes: A01M 17/00 Apparatus for the destruction of vermin in soil or in foodstuffs injecting fertilisers into the roots of trees A01G29/00
• CPC Class Codes: A01M 17/008 Destruction of vermin in foodstuffs
• CPC Class Codes: G01C 21/3826 Terrain data
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10036 Multispectral image; Hyperspectral image
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/30176 Document
• CPC Class Codes: G06T 2207/30188 Vegetation; Agriculture
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80

Abstract

A method for precisely applying chemicals targeted by digital maps developed from remotely sensed data, including: obtaining EOS data through a growing season of a crop growing in a field; processing the EOS data to reflectance values; removing error-inducing effects of atmospheric alteration from the processed EOS data; calculating from the processed EOS data a crop performance index that indicates one or more poor performing areas of the field; generating one or more maps of the crop performance index to allow a user to determine whether each of the one or more poor performing areas of the field are due to biological pests instead of topographic or soil constraints in discrete locations of the field; guiding the user to the one or more poor performing areas of the field using the one or more maps to allow the user to scout the one or more poor performing areas of the field to confirm and identify the biological pests; and providing guidance for a chemical application at the one or more poor performing areas that were confirmed as having the biological pests. Other embodiments are provided.

Claims

1. A method for precisely applying chemicals targeted by digital maps developed from remotely sensed data, the method comprising:

obtaining EOS data through a growing season of a crop growing in a field;

processing the EOS data to reflectance values;

removing error-inducing effects of atmospheric alteration from the processed EOS data;

calculating from the processed EOS data a crop performance index that indicates one or more poor performing areas of the field;

generating one or more maps of the crop performance index to allow a user to determine whether each of the one or more poor performing areas of the field are due to biological pests instead of topographic or soil constraints in discrete locations of the field; and

guiding the user to the one or more poor performing areas of the field using the one or more maps to allow the user to scout the one or more poor performing areas of the field to confirm and identify the biological pests;

providing guidance for a chemical application at the one or more poor performing areas that were confirmed as having the biological pests.

2. The method of claim 1, further comprising:

forecasting when the field will experience canopy closure, comprising;

processing the EOS data through at least a first third of the growing season to determine NDVI and NDVI*; and

performing a clocking function to forecast when to begin calculating the crop performance index.

3. The method of claim 1, wherein:

the one or more maps comprise at least one of crop performance index maps, crop performance index change detection maps, or cumulative crop performance index change detection maps.

4. The method of claim 3, wherein:

generating the one or more maps of the crop performance index further comprises generating the crop performance index change detection maps, comprising;

performing change detection on each update of the crop performance index maps by subtracting spatially discrete pixels of a first one of the crop performance index maps from a subsequent update of the crop performance index maps; and

guiding the user to the one or more poor performing areas of the field using the one or more maps further comprises;

outputting at least one of the crop performance index change detection maps.

5. The method of claim 4, wherein:

generating the one or more maps of the crop performance index further comprises generating the cumulative crop performance index change detection maps, comprising;

adding each update of the crop performance index map change detection maps to display a cumulative region affected by the biological pests;

guiding the user to the one or more poor performing areas of the field using the one or more maps further comprises;

outputting at least one of the cumulative crop performance index change detection maps.

6. The method of claim 1, wherein:

guiding the user to the one or more poor performing areas of the field using the one or more maps further comprises;

navigating to at least one of the one or more poor performing areas of the field using GPS functionality of a mobile device;

recording one or more observations regarding the crop at the at least one of the one or more poor performing areas of the field; and

outputting the one or more observations along with positioning information to allow the user to plan a chemical application treatment plan.

7. The method of claim 1, further comprising:

before providing guidance for the chemical application at the one or more poor performing areas using the one or more maps, developing a digital map using the one or more maps to guide the chemical application, comprising;

determining a number of days elapsed from a latest update of the one or more maps used to scout the one or more poor performing areas of the field until the chemical application is to be applied; and

buffering the digital map to increase a size of an area to be treated with the chemical application based on the number of days elapsed.

8. The method of claim 7, wherein:

developing the digital map to guide the chemical application further comprises, if the number of days elapsed is greater than a predetermined threshold;

obtaining new EOS data and updating the digital map using the new EOS data;

wherein;

buffering the digital map to increase the size of the area to be treated with the chemical application comprises;

buffering the digital map to increase the size of the area to be treated with the chemical application based on an updated number of days elapsed from the update of the digital map using the new EOS data until the chemical application is to be applied.

9. The method of claim 1, wherein:

providing guidance for the chemical application at the one or more poor performing areas that were confirmed as having the biological pests further comprises;

determining GPS-guided chemical spray equipment to be used for chemical application; and

sending to the GPS-guided chemical spray equipment a digital map based at least in part on the one or more maps of the crop performance index to allow the GPS-guided chemical spray equipment to apply the chemical application at the one or more poor performing areas that were confirmed.

10. The method of claim 1, wherein:

generating the one or more maps of the crop performance index further comprises;

providing the one or more maps with color coding overlain on a high-resolution air photograph to enable the user to determine the discrete locations having the topographic or soil constraints.

11. A system for precisely applying chemicals targeted by digital maps developed from remotely sensed data, the system comprising:

one or more processing modules; and

one or more non-transitory memory storage modules storing computing instructions configured to run on the one or more processing modules and perform the acts of;

obtaining EOS data through a growing season of a crop growing in a field;

processing the EOS data to reflectance values;

removing error-inducing effects of atmospheric alteration from the processed EOS data;

calculating from the processed EOS data a crop performance index that indicates one or more poor performing areas of the field;

generating one or more maps of the crop performance index to allow a user to determine whether each of the one or more poor performing areas of the field are due to biological pests instead of topographic or soil constraints in discrete locations of the field; and

guiding the user to the one or more poor performing areas of the field using the one or more maps to allow the user to scout the one or more poor performing areas of the field to confirm and identify the biological pests; and

providing guidance for a chemical application at the one or more poor performing areas that were confirmed as having the biological pests.

12. The system of claim 11, wherein the computing instructions are further configured to perform the acts of:

forecasting when the field will experience canopy closure, comprising;

processing the EOS data through at least a first third of the growing season to determine NDVI and NDVI*; and

performing a clocking function to forecast when to begin calculating the crop performance index.

13. The system of claim 11, wherein:

the one or more maps comprise at least one of crop performance index maps, crop performance index change detection maps, or cumulative crop performance index change detection maps.

14. The system of claim 13, wherein:

generating the one or more maps of the crop performance index further comprises generating the crop performance index change detection maps, comprising;

performing change detection on each update of the crop performance index maps by subtracting spatially discrete pixels of a first one of the crop performance index maps from a subsequent update of the crop performance index maps; and

guiding the user to the one or more poor performing areas of the field using the one or more maps further comprises;

outputting at least one of the crop performance index change detection maps.

15. The system of claim 14, wherein:

generating the one or more maps of the crop performance index further comprises generating the cumulative crop performance index change detection maps, comprising;

adding each update of the crop performance index map change detection maps to display a cumulative region affected by the biological pests;

guiding the user to the one or more poor performing areas of the field using the one or more maps further comprises;

outputting at least one of the cumulative crop performance index change detection maps.

16. The system of claim 11, wherein:

guiding the user to the one or more poor performing areas of the field using the one or more maps further comprises;

navigating to at least one of the one or more poor performing areas of the field using GPS functionality of a mobile device;

recording one or more observations regarding the crop at the at least one of the one or more poor performing areas of the field; and

outputting the one or more observations along with positioning information to allow the user to plan a chemical application treatment plan.

17. The system of claim 11, wherein the computing instructions are further configured to perform the acts of:

before providing guidance for the chemical application at the one or more poor performing areas using the one or more maps, developing a digital map using the one or more maps to guide the chemical application, comprising;

determining a number of days elapsed from a latest update of the one or more maps used to scout the one or more poor performing areas of the field until the chemical application is to be applied; and

buffering the digital map to increase a size of an area to be treated with the chemical application based on the number of days elapsed.

18. The system of claim 17, wherein:

developing the digital map to guide the chemical application further comprises, if the number of days elapsed is greater than a predetermined threshold;

obtaining new EOS data and updating the digital map using the new EOS data;

wherein;

buffering the digital map to increase the size of the area to be treated with the chemical application comprises;

buffering the digital map to increase the size of the area to be treated with the chemical application based on an updated number of days elapsed from the update of the digital map using the new EOS data until the chemical application is to be applied.

19. The system of claim 11, wherein:

providing, using the one or more maps, guidance for the chemical application at the one or more poor performing areas that were confirmed as having the biological pests further comprises;

determining GPS-guided chemical spray equipment to be used for chemical application; and

sending to the GPS-guided chemical spray equipment a digital map based at least in part on the one or more maps of the crop performance index to allow the GPS-guided chemical spray equipment to apply the chemical application at the one or more poor performing areas that were confirmed.

20. The system of claim 11, wherein:

generating the one or more maps of the crop performance index further comprises;

providing the one or more maps with color coding overlain on a high-resolution air photograph to enable the user to determine the discrete locations having the topographic or soil constraints.