초록 ▼

A system obtains agricultural attribute data from the field. The agricultural attribute data is classified into a plurality of spatially distributed regions across the field. Samples are obtained to provide a second set of agricultural attribute data. A subset of the second set of agricultural attri

A system obtains agricultural attribute data from the field. The agricultural attribute data is classified into a plurality of spatially distributed regions across the field. Samples are obtained to provide a second set of agricultural attribute data. A subset of the second set of agricultural attribute data is associated, by georeferencing, with one class of the spatially distributed regions. The subset is subclassified into respective zones, as may be done by interpolation to define contours. The classification process operates without regard to data that is not in the subset but is also taken from the second set of agricultural attribute data, i.e., the subclassification ignores data in the second set that is georeferenced to classes other than the class associated with the subset. The subclassification is repeated for all classes. An agroproduct prescription map is prepared for the application of agroproducts to the respective zones.

대표청구항 ▼

1. A method of applying agroproducts comprising: obtaining a first set of agricultural attribute data from a field;classifying by use of a computer a first set of agricultural attribute data using a Jenks Optimization to identify a plurality of discrete regions, each region having one or more contig

1. A method of applying agroproducts comprising: obtaining a first set of agricultural attribute data from a field;classifying by use of a computer a first set of agricultural attribute data using a Jenks Optimization to identify a plurality of discrete regions, each region having one or more contiguous special elements related by a commonality of class into a particular one a plurality of classes;obtaining a second set of agricultural attribute data from the field, the agricultural attribute data having at least one value obtained from each classification of the plurality of classes;identifying a subset of the second set of agricultural attribute data, different from the first set of agricultural attribute data, by associating the subset with a single class from among the plurality of classes;subclassifying by use of a computer the subset without regard to data obtained from other classes in the second set of agricultural attribute data to identify a plurality of application zones within the single class;determining an agroproduct prescription map for the plurality of application zones according to the needs of a crop that may be grown in the field; andapplying at least one agroproduct to the field according to the prescription map. 2. The method of claim 1 wherein the step of classifying the first set of agricultural attribute data includes using at least two classifications. 3. The method of claim 1 wherein the step of classifying the first set of agricultural attribute data includes identifying a plurality of non contiguous discrete regions allocated to a particular class. 4. The method of claim 3 wherein the step of subclassifying includes interpolating by use of Kriging Interpolation based upon the analyzed values. 5. The method of claim 1 wherein the step of subclassifying includes interpolating by use of Kriging Interpolation based upon the analyzed values. 6. The method of claim 1 wherein the step of obtaining a second set of agricultural attribute data includes correlating by use of an empirically derived multivariate polynomial equation. 7. The method of claim 1, with selection of a second subset of the second agricultural attribute data and as to that second subset repeating the steps of identifying a subset of the second set of agricultural attribute data,subclassifying the subset without regard to data obtained from other classes,determining an agroproduct prescription map, andapplying at least one agroproduct to the field. 8. A system for prescribing agroproducts comprising: means for obtaining a first set of agricultural attribute data from a field;means for classifying a first set of agricultural attribute data using a Jenks Optimization to identify a plurality of discrete regions, each region having one or more contiguous spatial elements related by commonality of class into a particular one a plurality of classes;means for obtaining a second set of agricultural attribute data from the field, the agricultural attribute data having at least one value obtained from each classification of the plurality of classes;means for identifying a subset of the second set of agricultural attribute data, different from the first set of agricultural attribute data, by associating the subset with a single class from among the plurality of classes;means for subclassifying the subset without regard to data obtained from other classes in the second set of agricultural attribute data to identify a plurality of application zones within the single class;means for determining an agroproduct prescription map for the plurality of application zones according to the needs of a crop that may be grown in the field. 9. The system of claim 8 wherein the means for classifying the first set of agricultural attribute data includes means for using at least two classifications. 10. The system of claim 8 wherein the means for classifying the first set of agricultural attribute data further compromises identifying a plurality of non contiguous discrete regions allocated to a particular class. 11. The system of claim 10 wherein the means for subclassifying interpolates by use of Kriging Interpolation based upon the analyzed values. 12. The system of claim 8 wherein the means for subclassifying includes program logic for interpolating by use of Kriging Interpolation based upon the analyzed values. 13. The system of claim 8 wherein the means for obtaining a second set of agricultural attribute data includes means for correlating by use of an empirically derived multivariate polynomial equation having coefficients fit to the analyzed values. 14. A system for prescribing agroproducts comprising: a first set of agricultural attribute data obtained from a field;a non-transitory computer readable medium containing machine-based program instructions for classifying a first set of agricultural attribute data using a Jenks Optimization to identify a plurality of discrete regions, each region having one or more contiguous spatial elements related by commonality of class into a particular one a plurality of classes;a second set of agricultural attribute data obtained from the field, the agricultural attribute data having at least one value obtained from each classification of the plurality of classes;the non-transitory computer based medium further containing machine-based program instructions for identifying a subset of the second set of agricultural attribute data, different from the first set of agricultural attribute data, by associating the subset with a single class from among the plurality of classes;the non-transitory computer readable medium further containing machine-based program instructions for subclassifying the subset without regard to data obtained from other classes-s in the second set of agricultural attribute data to identify a plurality of application zones within the single class;the non-transitory computer readable medium further containing machine-based program instructions for determining an agroproduct prescription map for the plurality of application zones according to the needs of a crop that may be grown in the field. 15. A machine-based method of prescribing agroproducts comprising: obtaining a first set of agricultural attribute data from a field;classifying by use of a computer programmed with a Jenks Optimization that operates upon a first set of agricultural attribute data to identify a plurality of discrete regions, each region having one or more contiguous spatial elements related by commonality of class into a particular one a plurality of classes;obtaining a second set of agricultural attribute data from the field, the agricultural attribute data having at least one value obtained from each classification of the plurality of classes;identifying a subset of the second set of agricultural attribute data, different from the first set of agricultural attribute data, by associating the subset with a single class from among the plurality of classes;subclassifying by use of a computer the subset without regard to data obtained from other classes in the second set of agricultural attribute data to identify a plurality of application zones within the single class; anddetermining an agroproduct prescription map for the plurality of application zones according to the needs of a crop that may be grown in the field. 16. A non-transitory computer readable form with program instructions operable to: obtain a first set of agricultural attribute data from a field;classify using a Jenks Optimization a first set of agricultural attribute data to identify a plurality of discrete regions, each region having one or more contiguous spatial elements related by commonality of class into a particular one a plurality of classes;obtain a second set of agricultural attribute data from the field, the agricultural attribute data having at least one value obtained from each classification of the plurality of classes;identify a subset of the second set of agricultural attribute data, different from the first set of agricultural attribute data, by associating the subset with a single class from among the plurality of classes;subclassify the subset without regard to data obtained from other classes in the second set of agricultural attribute data to identify a plurality of application zones within the single class; and determine an agroproduct prescription map for the plurality of application zones according to the needs of a crop that may be grown in the field.