Crop phenology estimation and tracking with remote sensing imagery

1. A method of estimating crop maturity using remote sensing imagery, the method comprising:

providing a remote sensing image of crops acquired at an image acquisition time;

predicting a maturity level of the crops at the image acquisition time based on input crop maturity data from an input time and weather-based growth indication data from between the input time and the image acquisition time, wherein the weather-based growth indication data comprises heat accumulation data accumulated between the input time and the acquisition time, and wherein the heat accumulation data comprises growing degree day data; and

updating the predicted maturity level to an updated maturity level based on the remote sensing image and a response model relating remote sensing image information to crop maturity information.

2. The method of claim 1 , wherein the providing, predicting, and updating steps are performed sequentially and iteratively, for N iterations, N being an integer greater than one, and wherein the updated maturity level at the image acquisition time from the n th iteration is used in providing the input crop maturity data at the input time for the (n+1) th iteration, n ranging from 1 to N−1.

3. The method of claim 2 , further comprising providing the input crop maturity data for the first iteration based on a distribution of crop planting dates that defines the input time for the first iteration.

4. The method of claim 1 , wherein the predicting and updating steps comprise performing a particle filtering operation.

5. The method of claim 4 , wherein the particle filtering operation comprises:

generating, as the predicted maturity level, a set of particles representing a probability density function of a state variable indicative of the crop maturity at the image acquisition time, each particle in the set of particles having a state value and a weight based on the input crop maturity data and the weather-based growth indication data; and

determining the updated maturity level by adjusting the weights of the particles based on a likelihood function by using the remote sensing image in the response model.

6. The method of claim 1 , wherein the remote sensing image comprises a synthetic aperture radar (SAR) image.

7. The method of claim 6 , wherein the SAR image comprises a polarimetric SAR image, and wherein the remote sensing image information comprises a SAR polarimetric parameter.

8. The method of claim 1 , further comprising converting the updated maturity level of the crops to a Biologische Bundesanstalt, Bundessortenamt and CHemical (BBCH) code by relating the updated maturity level to a ratio of a number of growing degree days associated with the crops for reaching a particular BBCH code to a number of growing degree days associated with a lifetime of the crops.

9. The method of claim 1 , further comprising predicting a subsequent maturity level of the crops at a subsequent time after the image acquisition time based on the updated maturity level and weather-based growth indication data from between the image acquisition time and the subsequent time.

10. The method of claim 1 , further comprising predicting a past maturity level of the crops at a past time before the image acquisition time based on the updated maturity level and past data, the past data comprising weather-based growth indication data from between the past time and the image acquisition time, or remote sensing image data acquired between the past time and the image acquisition time, or a combination thereof.

11. The method of claim 1 , further comprising adjusting the updated maturity level based on another remote sensing image acquired at a different time than the image acquisition time of the remote sensing image.

12. The method of claim 1 , further comprising predicting, based on the updated maturity level, a time at which the crops have reached or will reach a specified crop growth stage.

13. The method of claim 1 , wherein the input time is before the image acquisition time.

14. The method of claim 1 , wherein providing the remote sensing image comprises acquiring the remote sensing image with a remote sensing imager.

15. A non-transitory computer readable storage medium having stored thereon computer executable instructions that, when executed by a processor, cause the processor to perform a method comprising:

receiving a remote sensing image of crops acquired at an image acquisition time;

predicting a maturity level of the crops at the image acquisition time based on input crop maturity data from an input time and weather-based growth indication data from between the input time and the image acquisition time, wherein the weather-based growth indication data comprises growing degree day data accumulated between the input time and the acquisition time; and

updating the predicted maturity level to an updated maturity level based on the remote sensing image and a response model relating remote sensing image information to crop maturity information.

16. The non-transitory computer readable storage medium of claim 15 , wherein the providing, predicting, and updating steps are performed sequentially and iteratively, for N iterations, N being an integer greater than one, and wherein the updated maturity level at the image acquisition time from the n th iteration is used in providing the input crop maturity data at the input time for the (n+1) th iteration, n ranging from 1 to N−1.

17. The non-transitory computer readable storage medium of claim 16 , further comprising providing the input crop maturity data for the first iteration based on a distribution of crop planting dates that defines the input time for the first iteration.

18. The non-transitory computer readable storage medium of claim 16 , wherein the predicting and updating steps comprise performing a particle filtering operation, the particle filtering operation comprising:

generating, as the predicted maturity level, a set of particles representing a probability density function of a state variable indicative of the crop maturity at the image acquisition time, each particle in the set of particles having a state value and a weight based on the input crop maturity data and the weather-based growth indication data; and

determining the updated maturity level by adjusting the weights of the particles based on a likelihood function by using the remote sensing image in the response model.

19. The non-transitory computer readable storage medium of claim 15 , wherein the remote sensing image comprises a synthetic aperture radar (SAR) image.

20. The non-transitory computer readable storage medium of claim 15 , wherein the method further comprises predicting a subsequent maturity level of the crops at a subsequent time after the image acquisition time based on the updated maturity level and weather-based growth indication data from between the image acquisition time and the subsequent time.

21. The non-transitory computer readable storage medium of claim 15 , wherein the method further comprises predicting a past maturity level of the crops at a past time before the image acquisition time based on the updated maturity level and past data, the past data comprising weather-based growth indication data from between the past time and the image acquisition time, or remote sensing image data acquired between the past time and the image acquisition time, or a combination thereof.

22. A computer device for estimating crop maturity using remote sensing imagery, the computer device comprising:

a processor; and

the non-transitory computer readable storage medium of claim 15 , the non-transitory computer readable storage medium being operatively coupled to the processor.

23. A system for estimating crop maturity using remote sensing imagery, the system comprising:

a remote sensing imager configured for acquiring a remote sensing image of crops at an image acquisition time;

a control and processing unit arranged in communication with the remote sensing imager, the control and processing unit being configured for:

receiving the remote sensing image from the remote sensing imager;

predicting a maturity level of the crops at the image acquisition time based on input crop maturity data from an input time and weather-based growth indication data from between the input time and the image acquisition time, wherein the weather-based growth indication data comprises heat accumulation data accumulated between the input time and the acquisition time, and wherein the heat accumulation data comprises growing degree day data; and

updating the predicted maturity level to an updated maturity level based on the remote sensing image and a response model relating remote sensing image information to crop maturity information.

24. A method of estimating crop maturity using remote sensing imagery, the method comprising:

providing a remote sensing image of crops acquired at an image acquisition time;

predicting a maturity level of the crops at the image acquisition time based on input crop maturity data from an input time and weather-based growth indication data from between the input time and the image acquisition time; and

updating the predicted maturity level to an updated maturity level based on the remote sensing image and a response model relating remote sensing image information to crop maturity information,

wherein the providing, predicting, and updating steps are performed sequentially and iteratively, for N iterations, N being an integer greater than one, and wherein the updated maturity level at the image acquisition time from the n th iteration is used in providing the input crop maturity data at the input time for the (n+1) th iteration, n ranging from 1 to N−1, and

wherein the method further comprises providing the input crop maturity data for the first iteration based on a distribution of crop planting dates that defines the input time for the first iteration.

25. The method of claim 24 , wherein the predicting and updating steps comprise performing a particle filtering operation.

26. The method of claim 25 , wherein the particle filtering operation comprises:

generating, as the predicted maturity level, a set of particles representing a probability density function of a state variable indicative of the crop maturity at the image acquisition time, each particle in the set of particles having a state value and a weight based on the input crop maturity data and the weather-based growth indication data; and

determining the updated maturity level by adjusting the weights of the particles based on a likelihood function by using the remote sensing image in the response model.

27. The method of claim 24 , wherein the remote sensing image comprises a synthetic aperture radar (SAR) image.

28. The method of claim 24 , further comprising predicting a subsequent maturity level of the crops at a subsequent time after the image acquisition time based on the updated maturity level and weather-based growth indication data from between the image acquisition time and the subsequent time.

29. The method of claim 24 , further comprising predicting a past maturity level of the crops at a past time before the image acquisition time based on the updated maturity level and past data, the past data comprising weather-based growth indication data from between the past time and the image acquisition time, or remote sensing image data acquired between the past time and the image acquisition time, or a combination thereof.

30. A non-transitory computer readable storage medium having stored thereon computer executable instructions that, when executed by a processor, cause the processor to perform a method of claim 24 .

31. A system for estimating crop maturity using remote sensing imagery, the system comprising:

a remote sensing imager configured for acquiring a remote sensing image of crops at an image acquisition time;

a control and processing unit arranged in communication with the remote sensing imager, the control and processing unit comprising:

a processor; and

the non-transitory computer readable storage medium of claim 30 .

32. A method of estimating crop maturity using remote sensing imagery, the method comprising:

providing a remote sensing image of crops acquired at an image acquisition time;

predicting a maturity level of the crops at the image acquisition time based on input crop maturity data from an input time and weather-based growth indication data from between the input time and the image acquisition time; and

updating the predicted maturity level to an updated maturity level based on the remote sensing image and a response model relating remote sensing image information to crop maturity information,

wherein predicting and updating steps comprise performing a particle filtering operation, the particle filtering operation comprising:

generating, as the predicted maturity level, a set of particles representing a probability density function of a state variable indicative of the crop maturity at the image acquisition time, each particle in the set of particles having a state value and a weight based on the input crop maturity data and the weather-based growth indication data; and

determining the updated maturity level by adjusting the weights of the particles based on a likelihood function by using the remote sensing image in the response model.

33. The method of claim 32 , wherein the remote sensing image comprises a synthetic aperture radar (SAR) image.

34. The method of claim 32 , further comprising predicting a subsequent maturity level of the crops at a subsequent time after the image acquisition time based on the updated maturity level and weather-based growth indication data from between the image acquisition time and the subsequent time.

35. The method of claim 32 , further comprising predicting a past maturity level of the crops at a past time before the image acquisition time based on the updated maturity level and past data, the past data comprising weather-based growth indication data from between the past time and the image acquisition time, or remote sensing image data acquired between the past time and the image acquisition time, or a combination thereof.

36. A non-transitory computer readable storage medium having stored thereon computer executable instructions that, when executed by a processor, cause the processor to perform a method of claim 32 .

37. A system for estimating crop maturity using remote sensing imagery, the system comprising:

a remote sensing imager configured for acquiring a remote sensing image of crops at an image acquisition time;

a control and processing unit arranged in communication with the remote sensing imager, the control and processing unit comprising:

a processor; and

the non-transitory computer readable storage medium of claim 36 .