CONTINUAL CROP DEVELOPMENT PROFILING USING DYNAMICAL EXTENDED RANGE WEATHER FORECASTING WITH ROUTINE REMOTELY-SENSED VALIDATION IMAGERY

• US 20160003790A1
• Filed: 09/14/2015
• Published: 01/07/2016
• Est. Priority Date: 08/19/2014
• Status: Active Grant

• Current Assignee: DTN, LLC (TBG AG)
• Original Assignee: Iteris Incorporated
• Inventors: OSBORNE, LEON F., MEWES, JOHN J., SHAW, BRENT L., SALENTINY, DUSTIN M.
• Granted Patent: US 9,880,140 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A01G 7/00 Botany in general
• CPC Class Codes: G01N 33/0098 Plants or trees wood G01N33/46
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

A modeling framework for estimating crop growth and development over the course of an entire growing season generates a continuing profile of crop development from any point prior to and during a growing season until a crop maturity date is reached. The modeling framework applies extended range weather forecasts and remotely-sensed imagery to improve crop growth and development estimation, validation and projection. Output from the profile of crop development profile generates a combination of data for use in auxiliary farm management applications.

Claims

1. A computerized method comprising:

inputting a plurality of data that includes crop-specific information, planting specifications, remotely-sensed imagery of a crop'"'"'s location, and meteorological data that includes fine-resolution dynamical extended range weather forecast information, the fine-resolution dynamical extended range weather forecast information representing a time period extending through to a crop maturity date;

modeling the input data in a plurality of data processing modules within a computing environment in which the plurality of data processing modules are executed in conjunction with, and performed on, at least one computer processor, the data processing modules configured to generate a profile of crop development to a maturity stage by performing, over the course of a growing season, a crop growth model that includes the steps of

     1) generating an accumulated growing degree days estimate of crop growth stages,

     2) validating the estimate of crop growth stages by comparing the estimate with a time-series profile of crop growth data derived from the remotely-sensed imagery of the crop'"'"'s location,

     3) determining actual growth stages from direct user-provided field observations representing at least one of temperature values and crop growth, at least one time during a crop growing season,

     4) identifying differences between the estimate of crop growth stages and crop growth changes indicated by the comparison with remotely-sensed imagery and from the actual growth stages, and adjusting the estimate, and

     5) generating an accumulated growing degree days projection of the crop growth stages by extracting daily maximum and minimum air temperatures from forecasted information based on the dynamical extended range weather forecast information to describe heat accumulated for a crop location for the time period extending through to the crop maturity date;

relating the accumulated growing degree days projection of the crop growth stages to the remotely-sensed imagery of a crop'"'"'s location to generate a map of the crop'"'"'s location representing the crop growth changes over time; and

continually updating the map of the crop'"'"'s location over the course of a growing season.

2. The method of claim 1, wherein the crop-specific information includes a crop type and a variety of crop type that determines a set of growth characteristics of the crop that enables the data processing modules to generate the profile of crop development, the set of growth characteristics including a timing to growth of each crop growth stage, nutrient requirements per crop growth stage, pest and disease susceptibility per crop growth stage, and one or more temperature thresholds for crop growth conditions.

3. The method of claim 1, wherein the meteorological data further includes observed weather data for a geographical area including the crop'"'"'s location, and current field-level weather data for the geographical area including the crop'"'"'s location, the observed weather data and the current field-level weather data being repetitively applied to the crop growth model during a time period where the crop maturity date has not yet been reached.

4. The method of claim 3, wherein the generating an accumulated growing degree days estimate of crop growth stages generates an accumulated growing degree day estimate on a daily basis until a total accumulated growing degree day estimate exceeds the time period extending through to the crop maturity date.

5. The method of claim 1, further comprising analyzing the remotely-sensed imagery using a normalized difference vegetative index to evaluate at least one of plant health, biomass, and nutrient content.

6. The method of claim 1, further comprising generating a notification to a user when a validation of an estimate of crop growth stages produces a change in the map of the crop'"'"'s location.

7. The method of claim 1, further comprising providing the map of the crop'"'"'s location to one or more application protocol interface modules each configured to generate an advisory service for agriculture management applications.

8. The method of claim 1, further comprising providing the map of the crop'"'"'s location to one or more application protocol interface modules each configured to provide a crop alert to a user.

9. The method of claim 1, wherein the remotely-sensed imagery of the crop'"'"'s location is captured by an unmanned aerial system.

10. The method of claim 1, further comprising simulating a full growing season to project an expected timeline of crop growth stages and an anticipated crop maturity date by performing the crop growth model prior to a beginning of a growing season.

11. The method of claim 1, wherein the map of the crop'"'"'s location representing the crop growth changes over time is generated as a visualization of the time-series profile of crop growth data provided and provided to a user on a graphical user interface.

12. A system comprising:

a computer processor; and

at least one non-transitory computer-readable storage medium operably coupled to the computer processor and having program instructions stored therein, the computer processor being operable to execute the program instructions to generate a profile of crop development to a maturity stage by performing, over the course of a growing season, a crop growth model within a plurality of data processing modules, the plurality of data processing modules including;

a data ingest module configured to input crop-specific information and planting specifications, remotely-sensed imagery, and meteorological data that includes fine-resolution dynamical extended range weather forecast information, the fine-resolution dynamical extended range weather forecast information representing a time period extending through to a crop maturity date;

an estimation module configured to generate an accumulated growing degree days estimate of crop growth stages;

a crop validation module configured to

     1) compare the estimate with a time-series profile of crop growth data derived from remotely-sensed imagery of a crop'"'"'s location to validate the estimate of crop growth stages,

     2) determine actual growth stages from direct user-provided field observations representing at least one of temperature values and crop growth, at least one time during a crop growing season, and

     3) identify differences between the estimate of crop growth stages and crop growth changes indicated by the comparison with remotely-sensed imagery and from the actual growth stages, and adjusting the estimate;

a projection module configure to generate an accumulated growing degree days projection of the crop growth stages by extracting daily maximum and minimum air temperatures from forecasted information based on the dynamical extended range weather forecast information to describe heat accumulated for a crop location for the time period extending through to the crop maturity date; and

a crop growth reporting module configured to relate the accumulated growing degree days projection of the crop growth stages to the remotely-sensed imagery of a crop'"'"'s location and generate a map of the crop'"'"'s location representing the crop growth changes over time, and continually update the map of the crop'"'"'s location over the course of a growing season.

13. The system of claim 12, wherein the crop-specific information includes a crop type and a variety of crop type that determines a set of growth characteristics of the crop that enables the data processing modules to generate the profile of crop development, the set of growth characteristics including a timing to growth of each crop growth stage, nutrient requirements per crop growth stage, pest and disease susceptibility per crop growth stage, and one or more temperature thresholds for crop growth conditions.

14. The system of claim 12, wherein the meteorological data further includes observed weather data for a geographical area including the crop'"'"'s location, and current field-level weather data for the geographical area including the crop'"'"'s location.

15. The system of claim 12, wherein the estimation module generates an accumulated growing degree day estimate on a daily basis until a total accumulated growing degree day estimate exceeds the time period extending through to the crop maturity date.

16. The system of claim 12, wherein the crop growth model analyzes the remotely-sensed imagery using a normalized difference vegetative index to evaluate at least one of plant health, biomass, and nutrient content.

17. The system of claim 12, wherein a notification is provided to a user when a validation of an estimate of crop growth stages produces a change in the map of the crop'"'"'s location.

18. The system of claim 12, further comprising an application programming interface module configured to receive the map of the crop'"'"'s location and generate one or more advisory services for agriculture management applications.

19. The system of claim 12, further comprising an application programming interface module configured to receive the map of the crop'"'"'s location and provide a crop alert a user.

20. The system of claim 12, wherein the remotely-sensed imagery of the crop'"'"'s location is captured by an unmanned aerial system.

21. A method projecting crop growth over the course of a growing season, comprising:

within a computing environment comprised of a computer processor and at least one non-transitory computer-readable storage medium operably coupled to the computer processor and having program instructions stored therein, the computer processor being operable to execute the program instructions to augment a crop growth model configured to perform the steps of;

estimating an accumulated growing degree days of a plurality of crop growth stages, by generating a profile of crop development over the course of a crop growing season through to a maturity stage;

adjusting the estimate based on differences with crop growth changes identified by a comparison between the estimate with a time-series profile of crop growth data derived from the remotely-sensed imagery of a crop'"'"'s location and from actual growth stages indicated by direct user-provided field observations;

projecting accumulated growing degree days of the crop growth stages for a time period extending through to the crop maturity date by extracting daily maximum and minimum air temperatures from forecasted information based on dynamical extended range weather forecast information to describe heat accumulated for the crop'"'"'s location; and

mapping the accumulated growing degree days of the crop growth stages.

22. The method of claim 21, wherein the mapping the accumulated growing degree days of the crop growth stages further comprises relating the accumulated growing degree days projection of the crop growth stages to the remotely-sensed imagery of a crop'"'"'s location to generate a map of the crop'"'"'s location representing the crop growth changes over time.

23. The method of claim 21, further comprising inputting crop-specific information and planting specifications, the remotely-sensed imagery of the crop'"'"'s location, and meteorological data that includes the fine-resolution dynamical extended range weather forecast information.

24. The method of claim 21, wherein the crop-specific information includes a crop type and a variety of crop type determines a set of growth characteristics of the crop that enables the data processing modules to generate the profile of crop development, the set of growth characteristics including a timing to growth of each crop growth stage, nutrient requirements per crop growth stage, pest and disease susceptibility per crop growth stage, and one or more temperature thresholds for crop growth conditions.

25. The method of claim 21, wherein the meteorological data further includes observed weather data for a geographical area including the crop'"'"'s location, and current field-level weather data for the geographical area including the crop'"'"'s location, the observed weather data and the current field-level weather data being repetitively applied to the crop growth model during a time period where the crop maturity date has not yet been reached.

26. The method of claim 21, further comprising generating a notification to a user when an adjustment of the estimate of crop growth stages produces a change in the map of the crop'"'"'s location.

27. The method of claim 21, further comprising providing the map of the crop'"'"'s location to one or more application protocol interface modules configured to generate an advisory service for agriculture management applications.

28. The method of claim 21, further comprising providing the map of the crop'"'"'s location to one or more application protocol interface modules configured to provide a crop alert to a user.

29. The method of claim 21, wherein the remotely-sensed imagery of the crop'"'"'s location is captured by an unmanned aerial system

30. The method of claim 21, further comprising simulating a full growing season, prior to a beginning of a growing season, to project an expected timeline of crop growth stages and an anticipated crop maturity date.