Method for mapping crop yields

1. A system ( 300 ) for generating a yield map (ISO) for a field area, the system ( 300 ) comprising:

one or more display devices ( 325 );

one or more processors ( 312 ); and

one or more memory devices ( 314 ), the one or more memory devices ( 314 ) storing computer-readable instructions ( 316 ) that when executed by the one or more processors ( 312 ) cause the one or more processors ( 312 ) to perform operations, the operations comprising:

accessing, by one or more processors ( 312 ), data indicative of crop yield ( 110 ) for a field area;

accessing, by the one or more processors ( 312 ), a vegetation index (VI) image ( 122 ) of the field area, the VI image ( 122 ) comprising a plurality of pixels ( 12 S), each pixel ( 12 S) in the VI image ( 122 ) having a pixel value associated with an amount of vegetation in a discrete subsection of the field area corresponding to the pixel ( 125 );

determining, by the one or more processors ( 312 ), a crop yield distribution for the field area, the crop yield distribution comprising a crop yield value for each of a plurality of discrete subsections of the field area determined based at least in part on the data indicative of crop yield ( 310 ) and the pixel value of the pixel ( 125 ) in the VI image ( 122 ) corresponding to the discrete subsections in the field area;

generating, by the one or more processors ( 312 ), a yield map ( 150 ) for the area based at least in part on the crop yield distribution, the yield map ( 150 ) comprising a plurality of pixels ( 155 ), the pixel value of each pixel ( 155 ) in the yield map ( 150 ) being determined based at least in part on a crop yield value for the discrete subsections of the field area corresponding to the pixel ( 155 ).

2. The system ( 300 ) of claim 1 , wherein the operations further comprise refining, by the one or more processors ( 312 ), the crop yield distribution based at least in part on one or more data types ( 120 ).

3. The system ( 300 ) of claim 1 , wherein the operations further comprise providing, by the one or more processors ( 312 ), the yield map ( 150 ) for display on the one or more display devices ( 325 ).

4. The system ( 300 ) of claim 2 , wherein the one or more data types ( 120 ) comprise one or more VI images ( 122 ) captured at different time periods, one or more LIDAR images ( 126 ), one or more satellite images ( 124 ), aerial images ( 124 ), or ground based images ( 124 ) of the field area, stand count data ( 128 ), as-planted values obtained from planting equipment ( 130 ), or one or more hyperspectral images ( 130 ).

5. A method ( 200 ) for generating a yield map ( 150 ) for a field area, comprising:

( 202 ) accessing, by one or more processors ( 312 ), data indicative of crop yield ( 110 ) for a field area;

( 204 ) accessing, by the one or more processors ( 312 ), one or more data types ( 120 ) associated with the field area, each of the data types ( 120 ) providing a geospatial distribution of data associated with vegetation across the field area;

( 208 ) determining, by the one or more processors ( 312 ), a crop yield distribution for the field area based at least in part on the data indicative of crop yield ( 110 ) and the one or more data types ( 120 );

( 210 ) generating, by the one or more processors ( 312 ), a yield map (ISO) for the field area based at least in part on the crop yield distribution;

wherein the yield map ( 150 ) comprises a plurality of pixels ( 155 ), the pixel value of each pixel ( 155 ) being determined based at least in part on a crop yield value for the discrete subsections of the field area corresponding to the pixel ( 155 );

displaying the yield map ( 150 ) on one or more display devices ( 325 );

wherein the one or more data types ( 120 ) comprise a vegetation index (VI) image ( 122 ) of the field area.

6. The method ( 200 ) of claim 5 , wherein ( 208 ) determining, by the one or more processors ( 312 ), a crop yield distribution for the field area comprises:

( 206 ) accessing, by the one or more processors ( 312 ), a model ( 140 ) defining crop yield values for discrete subsections of the field area as a function of at least the one or more data types ( 120 ); and

( 208 ) determining, by the one or more processors ( 312 ), the crop yield distribution based at least in part on the model ( 140 ).

7. The method ( 200 ) of claim 5 , wherein ( 208 ) determining, by the one or more processors ( 312 ), a crop yield distribution for the field area comprises determining, by the one or more processors ( 312 ), a crop yield value for discrete subsections of the field area based at least in part on a pixel value of a pixel ( 125 ) corresponding to the discrete subsections in the VI image ( 122 ).

8. The method ( 200 ) of claim 5 , wherein the one or more data types ( 120 ) comprise a plurality of VI images ( 122 ), each of the VI images ( 122 ) captured at a different time.

9. The method ( 200 ) of claim 5 , wherein the one or more data types ( 120 ) comprise as-planted values ( 130 ) obtained from planting equipment and/or stand count data ( 128 ) for the field area.

10. The method ( 200 ) of claim 5 , wherein the one or more data types ( 120 ) comprise one or more LIDA images ( 126 ) associated with the field area and/or one or more hyperspectral images ( 130 ) obtained of the field area.

11. The method ( 200 ) of claim 5 , wherein the one or more data types ( 120 ) comprise one or more satellite images ( 124 ), aerial images ( 124 ), or ground based images ( 124 ) of the field area.

12. A non-transitory computer readable medium having stored a program element which when executed by a processor is configured to carry out the method of claim 5 .