Method and system to map biological pests in agricultural fields using remotely-sensed data for field scouting and targeted chemical application

Patent metadata

Field	Value
Publication number	US-11399532-B2
Application number	US-202017102286-A
Country	US
Kind code	B2
Filing date	Nov 23, 2020
Priority date	May 13, 2011
Publication date	Aug 2, 2022
Grant date	Aug 2, 2022

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.

First claim

What is claimed is:

1. A computer-implemented method of effectively applying chemicals to fields based on remotely sensed data, the method comprising:
obtaining, by a processor, remotely sensed data through a growing season of a crop growing in a field, the remotely sensed data comprising multiple images of the field at different times in the growing season, each image including reflectance values having, per pixel, at least values for an NIR band and a red band;
determining normalized difference vegetation index (NDVI) values, per pixel, for the multiple images, from the reflectance values of the multiple images;
determining a modified normalized difference vegetation index (NDVI*) value, for each pixel, for each image, based on:
NDVI*=(NDVI i −NDVI 0 )/(NDVI S −NDVI 0 )

wherein NDVI i is a NDVI value for a pixel, i, of an image, NDVI S is a saturation value, and NDVI 0 is a bare soil value;
determining field medians from the modified NDVI* values for the images as a time series;
forecasting a time of canopy closure based on the field medians;
generating a map indicating crop performance of the field at or after the forecasted time of canopy closure; and
sending instructions to equipment for applying chemicals to areas indicated on the maps whereby the equipment applies the chemicals to the areas consistent with the instructions.

2. The computer-implemented method of claim 1 , wherein the equipment includes a ground spray rig or an aerial vehicle with a chemical spray.

3. The computer-implemented method of claim 1 , the forecasting comprising:
entering a field median of the field medians into a clocking function to forecast an apparent emergence date (AED); and
calibrating for elapsed days from the AED to forecast the time of canopy closure.

4. The computer-implemented method of claim 1 , further comprising performing, after the time of canopy closure, band balancing on the reflectance values for each of the NIR and red bands, thereby obtaining updated remotely sensed data.

5. The computer-implemented method of claim 4 , further comprising calculating a vegetation index for targeted chemical management (TCM) using the updated remotely sensed data for each of a plurality of locations in the field, the map including data based on the vegetation index for each of the plurality of locations.

6. The computer-implemented method of claim 5 , the calculating being based on the updated remotely sensed data for at least an NIR band, a red band, and a green band.

7. The computer-implemented method of claim 5 , the calculating comprising:
computing an index value for each of one or more pixels in the map; and
computing an index value for each of the plurality of locations by normalizing the index values for the one or more pixels within the location.

8. The computer-implemented method of claim 5 , the sending comprising:
determining, for a certain location of the plurality of locations where the data based on the vegetation index is less than a threshold, a size of a buffer area around the certain location; and
preparing instructions to apply the chemicals to the certain location and the buffer area.

9. The computer-implemented method of claim 8 , wherein the sending is performed on a daily basis, wherein determining the size of the buffer area comprises increasing the size of the buffer area every day based on at least temperature and humidity.

10. The computer-implemented method of claim 1 , further comprising:
transmitting, to a mobile device, instructions for navigating to certain locations in the field based on the areas indicated in the map; and
receiving a confirmation that an area of the locations harbors biological pests.

11. The computer-implemented method of claim 1 , the obtaining the remotely sensed data comprising receiving data from orbital satellites or manned or unmanned aerial vehicles operating within an atmosphere.

12. One or more non-transitory computer-readable storage media storing sequences of instructions which when executed cause one or more hardware processors to perform a computer-implemented method of effectively applying chemicals to fields based on remotely sensed data, the method comprising:
obtaining remotely sensed data through a growing season of a crop growing in a field, the remotely sensed data comprising multiple images of the field at different times in the growing season, each image including reflectance values having, per pixel, at least values for an NIR band and a red band;
determine a modified normalized difference vegetation index (NDVI*) value, for each pixel, for each image, based on:
NDVI*=(NDVI i −NDVI 0 )/(NDVI S −NDVI 0 )

wherein NDVI i is a NDVI value for a pixel, i, of an image, NDVI S is a saturation value, and NDVI 0 is a bare soil value;
determining field medians from the modified NDVI* values for the images as a time series;
forecasting a time of canopy closure based on the field medians;
generating a map indicating crop performance of the field at or after the forecasted time of canopy closure; and
sending instructions to equipment for applying chemicals to areas indicated on the maps whereby the equipment applies the chemicals to the areas consistent with the instructions.

13. The one or more non-transitory computer-readable storage media of claim 12 , wherein the equipment includes a ground spray rig or an aerial vehicle with a chemical spray.

14. The one or more non-transitory computer-readable storage media of claim 12 , the forecasting comprising:
entering a field median of the field medians into a clocking function to forecast an apparent emergence date (AED); and
calibrating for elapsed days from the AED to forecast the time of canopy closure.

15. The one or more non-transitory computer-readable storage media of claim 12 , the method further comprising performing, after the time of canopy closure, band balancing on the reflectance values for each of the NIR and red bands, thereby obtaining updated remotely sensed data.

16. The one or more non-transitory computer-readable storage media of claim 15 , the method further comprising;
calculating a vegetation index for targeted chemical management (TCM) using the updated remotely sensed data for each of a plurality of locations in the field, the map including data based on the vegetation index for each of the plurality of locations.

17. The one or more non-transitory computer-readable storage media of claim 16 , the calculating being based on the updated remotely sensed data for at least an NIR band, a red band, and a green band.

18. The one or more non-transitory computer-readable storage media of claim 16 , the calculating comprising:
computing an index value for each of one or more pixels in the map; and
computing an index value for each of the plurality of locations by normalizing the index values for the one or more pixels within the location.

19. The one or more non-transitory computer-readable storage media of claim 16 , the sending comprising:
determining, for a certain location of the plurality of locations where the data based on the vegetation index is less than a threshold, a size of a buffer area around the certain location; and
preparing instructions to apply the chemicals to the certain location and the buffer area.

20. The one or more non-transitory computer-readable storage media of claim 12 , the obtaining the remotely sensed data comprising receiving data from orbital satellites or manned or unmanned aerial vehicles operating within an atmos

Assignees

• Climate Llc

Inventors

• Groeneveld David P

Classifications

• G06T2207/10016

  Video; Image sequence · CPC title

• G06T2207/30176

  Document · CPC title

• G06T2207/30188

  Vegetation; Agriculture · CPC title

• G06T2207/10048

  Infrared image · CPC title

• G06T2207/10036

  Multispectral image; Hyperspectral image · CPC title