Controlling agricultural production areas

1. A method for controlling an area, the method comprising:

determining a relationship between historical wide-area meteorological gridded prediction data and historical local-area sensor data at a sensor location based on historical wide-area meteorological gridded prediction data for multiple meteorological variables made at a first point in time for a second point in time and historical local-area sensor data captured at the second point in time at the sensor location, the sensor data comprising multiple sensor data variables and the relationship being determined for each of the multiple sensor data variables;

calculating at a present point in time a prediction on a local-area parameter for a future point in time based on

present wide-area meteorological gridded prediction data for the future point in time, and

the relationship for each sensor data variable between the historical wide-area meteorological gridded prediction data and the historical local-area sensor data for that sensor data variable at the sensor location; and

controlling the area based on the prediction on the parameter; and

repeatedly updating the relationship over time based on further wide-area meteorological gridded prediction data and further local-area sensor data at the sensor location to thereby improve the relationship.

2. The method of claim 1 , wherein the prediction relates to at least 24 hours into the future.

3. The method of claim 1 , wherein the historical wide-area meteorological gridded prediction data and the historical local-area sensor data at a point relates to at least 5 previous days.

4. The method of claim 1 , wherein the historical wide-area meteorological gridded prediction data and the present wide-area meteorological gridded prediction data comprise wind data and determining the relationship and calculating the prediction is based on the wind data.

5. The method of claim 1 , wherein

the area comprises multiple sub-areas,

there is at least one local-area sensor in each of the multiple sub-areas, and

determining the relationship and calculating the prediction is performed for each of the sub-areas.

6. The method of claim 1 , wherein controlling the area comprises one or more of:

plant;

irrigate;

harvest;

protect; and

feed.

7. The method of claim 1 , further comprising creating a graphical user interface to present the prediction on the local-area parameter to a user, wherein the method comprises repeating the step of calculating the prediction for multiple future times and creating the graphical user interface to present a time series of the prediction for the multiple future times.

8. The method of claim 7 , wherein the graphical user interface comprises input elements to allow the user to input planned controlling actions.

9. The method of claim 1 , further comprising determining a suggestion for controlling the area based on the prediction on the parameter.

10. The method of claim 9 , further comprising determining a prediction on the local area sensor data based on the current wide-area meteorological gridded prediction data and the relationship between the historical wide-area meteorological gridded prediction data and the historical local-area sensor data at a point, wherein determining the suggestion is based on a predefined risk associated with local area sensor data where that risk is likely to occur and the suggestion is determined based on the prediction on the local area sensor data to reduce the risk.

11. The method of claim 9 , further comprising displaying the suggestion in a user interface.

12. The method of claim 1 , wherein the local-area parameter is a water deficit or water surplus.

13. The method of claim 1 wherein the prediction on the local-area parameter comprises a quality parameter indicative of a predicted quality of a produce from the area and controlling the area comprises optimising the quality parameter.

14. The method of claim 13 , further comprising repeating the step of calculating the prediction on the quality parameter for multiple future times and creating a graphical user interface to present a time series of the prediction on the quality parameter for the multiple future times.

15. The method of claim 13 , wherein the quality parameter comprises an expected shelf life.

16. A non-transitory computer readable medium with computer code stored thereon, when executed by a computer, causes the computer to perform a method comprising:

determining a relationship between historical wide-area meteorological gridded prediction data and historical local-area sensor data at a sensor location based on historical wide-area meteorological gridded prediction data for multiple meteorological variables made at a first point in time for a second point in time and historical local-area sensor data captured at the second point in time at the sensor location, the sensor data comprising multiple sensor data variables and the relationship being determined for each of the multiple sensor data variables;

calculating at a present point in time a prediction on a local-area parameter for a future point in time based on

present wide-area meteorological gridded prediction data for the future point in time, and

the relationship for each sensor data variable between the historical wide-area meteorological gridded prediction data and the historical local-area sensor data for that sensor data variable at the sensor location; and

controlling the area based on the prediction on the parameter; and

repeatedly updating the relationship over time based on further wide-area meteorological gridded prediction data and further local-area sensor data at the sensor location to thereby improve the relationship.

17. A computer system for controlling an area comprising:

a receiver for receiving wide-area meteorological gridded prediction data for multiple meteorological variables and local area sensor data comprising multiple sensor data variables;

a processor to:

determine for each sensor data variable a relationship between historical wide-area meteorological gridded prediction data and historical local-area sensor data at a sensor location based on the historical wide-area meteorological gridded prediction data made at a first point in time for a second point in time and the historical local-area sensor data for that sensor data variable captured at the second point in time at the sensor location;

calculate at a present point in time a prediction on a local-area parameter for a future point in time based on

present wide-area meteorological gridded prediction data for the future point in time, and

the relationship for each sensor data variable between the historical wide-area meteorological prediction data and the historical local-area sensor data for that sensor data variable at the sensor location;

repeatedly update the relationship over time based on further wide-area meteorological gridded prediction data and further local-area sensor data at the sensor location to thereby improve the relationship; and

an output port to control the area based on the prediction on the parameter.