Partitioning agricultural fields for annotation

1. A method implemented using one or more processors, comprising:

rendering, as part of a graphical user interface (GUI), a map of a geographic area containing a plurality of distinct agricultural fields,

wherein the plurality of distinct agricultural fields are visually delineated from each other and visually annotated at a field level to convey a first set of clusters of similar distinct agricultural fields, wherein within each cluster of the first set, all distinct agricultural fields that are members of the cluster are uniformly visually annotated, and

wherein the plurality of distinct agricultural fields are partitioned into the first set of clusters based on a first granularity value and field-level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields;

receiving user input that indicates a second granularity value that is different than the first granularity value;

based on the second granularity value and the field level agricultural features, partitioning the plurality of distinct agricultural fields into a second set of clusters of similar agricultural fields, wherein a count of the second set of clusters is different than a count of the first set of clusters and a count of the plurality of distinct agricultural fields remains constant across the first and second sets of clusters;

rendering, as part of the GUI, an updated map of the geographic area in which the plurality of distinct agricultural fields remain visually delineated from each other and are visually annotated at the same field level to convey the second set of clusters of similar distinct agricultural fields, wherein within each cluster of the second set, all agricultural fields in the cluster are uniformly visually annotated; and

rendering, as part of the GUI, a plurality of histograms based on values of the field level agricultural features across the plurality of distinct agricultural fields, wherein the plurality of histograms convey relative influences of the field level agricultural features in partitioning individual and distinct agricultural fields into the second set of clusters.

2. The method of claim 1 , wherein each histogram is based on values of a respective agricultural feature of the field level agricultural features across the plurality of distinct agricultural fields.

3. The method of claim 1 , wherein for a given agricultural feature of the field level agricultural features, a different histogram is rendered for each cluster of the second set of clusters.

4. The method of claim 3 , wherein for the given agricultural feature, the different histograms are rendered to at least partially overlap each other.

5. The method of claim 1 , wherein bins of the plurality of histograms correspond to ranges of values of the field level agricultural features.

6. The method of claim 1 , wherein the partitioning includes performing K-means clustering, the first granularity value comprises a first K value, and the second granularity value comprises a second K value.

7. The method of claim 1 , wherein the field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields used to perform the partitioning include one or more landform properties.

8. The method of claim 1 , wherein the field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields used to perform the partitioning include one or more edaphic features.

9. The method of claim 1 , wherein the field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields used to perform the partitioning include a measure of evapotranspiration.

10. A system comprising one or more processors and memory storing instructions that, in response to execution of the instructions by the one or more processors, cause the one or more processors to:

render, as part of a graphical user interface (GUI), a map of a geographic area containing a plurality of distinct agricultural fields,

wherein the plurality of distinct agricultural fields are visually delineated from each other and visually annotated at a field level to convey a first set of clusters of similar distinct agricultural fields, wherein within each cluster of the first set, all distinct agricultural fields that are members of the cluster are uniformly visually annotated, and

wherein the plurality of distinct agricultural fields are partitioned into the first set of clusters based on a first granularity value and field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields;

receive user input that indicates a second granularity value that is different than the first granularity value;

based on the second granularity value and the field level agricultural features, partition the plurality of distinct agricultural fields into a second set of clusters of similar agricultural fields, wherein a count of the second set of clusters is different than a count of the first set of clusters and a count of the plurality of distinct agricultural fields remains constant across the first and second sets of clusters;

render, as part of the GUI, an updated map of the geographic area in which the plurality of distinct agricultural fields remain visually delineated from each other and are visually annotated at the same field level convey the second set of clusters of similar distinct agricultural fields, wherein within each cluster of the second set, all agricultural fields in the cluster are uniformly visually annotated; and

render, as part of the GUI, a plurality of histograms based on values of the field level agricultural features across the plurality of distinct agricultural fields, wherein the plurality of histograms convey relative influences of the field level agricultural features in partitioning individual and distinct agricultural fields into the second set of clusters.

11. The system of claim 10 , wherein each histogram is based on values of a respective agricultural feature of the field level agricultural features across the plurality of distinct agricultural fields.

12. The system of claim 10 , wherein for a given agricultural feature of the field level agricultural features, a different histogram is rendered for each cluster of the second set of clusters.

13. The system of claim 12 , wherein for the given agricultural feature, the different histograms are rendered to at least partially overlap each other.

14. The system of claim 10 , wherein bins of the plurality of histograms correspond to ranges of values of the field level agricultural features.

15. The system of claim 10 , wherein the partitioning includes performing K-means clustering, the first granularity value comprises a first K value, and the second granularity value comprises a second K value.

16. The system of claim 10 , wherein the field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields used to perform the partitioning include one or more landform properties.

17. The system of claim 10 , wherein the field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields used to perform the partitioning include one or more edaphic features.

18. The system of claim 10 , wherein the field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields used to perform the partitioning include a measure of evapotranspiration.

19. A non-transitory computer-readable medium comprising instructions that, in response to execution of the instructions by a processor, cause the processor to:

render, as part of a graphical user interface (GUI), a map of a geographic area containing a plurality of distinct agricultural fields,

wherein the plurality of distinct agricultural fields are visually delineated from each other and visually annotated at a field level to convey a first set of clusters of similar distinct agricultural fields, wherein within each cluster of the first set, all distinct agricultural fields that are members of the cluster are uniformly visually annotated, and

wherein the plurality of distinct agricultural fields are partitioned into the first set of clusters based on a first granularity value and field level agricultural features of individual agricultural fields of the plurality of distinct agricultural fields;

receive user input that indicates a second granularity value that is different than the first granularity value;

based on the second granularity value and the field level agricultural features, partition the plurality of distinct agricultural fields into a second set of clusters of similar agricultural fields, wherein a count of the second set of clusters is different than a count of the first set of clusters and a count of the plurality of distinct agricultural fields remains constant across the first and second sets of clusters;

render, as part of the GUI, an updated map of the geographic area in which the plurality of distinct agricultural fields remain visually delineated from each other and are visually annotated at the same field level to convey the second set of clusters of similar distinct agricultural fields, wherein within each cluster of the second set, all agricultural fields in the cluster are uniformly visually annotated; and

render, as part of the GUI, a plurality of histograms based on values of the field level agricultural features across the plurality of distinct agricultural fields, wherein the plurality of histograms convey relative influences of the field level agricultural features in partitioning individual and distinct agricultural fields into the second set of clusters.

20. The non-transitory computer-readable medium of claim 19 , wherein each histogram is based on values of a respective agricultural feature of the field level agricultural features across the plurality of distinct agricultural fields.