Crop phenology estimation and tracking with remote sensing imagery

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.

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.

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 nth 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.

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.