GENERATING AND IMPROVING UPON AGRICULTURAL MAPS

1 . A computer-implemented method for generating an agriculture map of a region of land, the method comprising:

collecting agricultural data of one or more sub-regions of the region of land, wherein the agricultural data includes classified data and unclassified data;

extracting one or more features from the collected classified agricultural data;

training one or more models based on the extracted one or more features; and

generating an agricultural map of the region of land based on applying the one or more models to the collected unclassified agricultural data.

2 . The method of claim 1 , further comprising:

determining one or more entropy scores of the one or more sub-regions of land;

determining a first sub-region of land from which to collect additional data, wherein the first sub-region of land is the sub-region of land with the highest entropy score; and

collecting additional agricultural data of the first sub-region of land, wherein the collected agricultural data includes the collected additional agricultural data.

3 . The method of claim 2 , further comprising:

extracting one or more additional features from the collected additional agricultural data; and

updating the generated agricultural map based on the one or more additional features.

4 . The method of claim 3 , further comprising:

based on determining that a maximum collection budget is not yet exceeded:

determining a second sub-region of land from which to collect additional data, wherein the second sub-region of land is the sub-region of land with the second highest entropy score;

collecting additional agricultural data of the second sub-region of land;

extracting one or more additional features from the collected additional agricultural data; and

updating the generated agricultural map based on the one or more additional features.

5 . The method of claim 1 , wherein:

at least one model is trained for each sub-region for which the collected classified data was collected; and

the one or more trained models are applied to the one or more extracted features to calculate one or more probabilities of one or more possible classifications of the one or more sub-regions of land.

6 . The method of claim 5 , further comprising:

calculating one or more averages of the one or more probabilities of one or more possible classifications of the one or more sub-regions of land; and

calculating one or more entropy scores based on the one or more averages.

7 . The method of claim 1 , wherein:

the one or more features include features from the group comprising crop samples, soil samples, pest samples, crop yield, precipitation, temperature, moisture, photos/videos of land, and classifications of land; and

the agricultural data includes data from the group comprising physical access or vehicle image annotation data, remote sensing data, weather data, soil data, crop mask data, or irrigation type data.

8 . A computer program product for generating an agriculture map of a region of land, the computer program product comprising:

one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media capable of performing a method, the method comprising:

collecting agricultural data of one or more sub-regions of the region of land, wherein the agricultural data includes classified data and unclassified data;

extracting one or more features from the collected classified agricultural data;

training one or more models based on the extracted one or more features; and

generating an agricultural map of the region of land based on applying the one or more models to the collected unclassified agricultural data.

9 . The computer program product of claim 8 , further comprising:

determining one or more entropy scores of the one or more sub-regions of land;

determining a first sub-region of land from which to collect additional data, wherein the first sub-region of land is the sub-region of land with the highest entropy score; and

collecting additional agricultural data of the first sub-region of land, wherein the collected agricultural data includes the collected additional agricultural data.

10 . The computer program product of claim 9 , further comprising:

extracting one or more additional features from the collected additional agricultural data; and

updating the generated agricultural map based on the one or more additional features.

11 . The computer program product of claim 10 , further comprising:

based on determining that a maximum collection budget is not yet exceeded:

determining a second sub-region of land from which to collect additional data, wherein the second sub-region of land is the sub-region of land with the second highest entropy score;

collecting additional agricultural data of the second sub-region of land;

extracting one or more additional features from the collected additional agricultural data; and

updating the generated agricultural map based on the one or more additional features.

12 . The computer program product of claim 8 , wherein:

at least one model is trained for each sub-region for which the collected classified data was collected; and

the one or more trained models are applied to the one or more extracted features to calculate one or more probabilities of one or more possible classifications of the one or more sub-regions of land.

13 . The computer program product of claim 12 , further comprising:

calculating one or more averages of the one or more probabilities of one or more possible classifications of the one or more sub-regions of land; and

calculating one or more entropy scores based on the one or more averages.

14 . The computer program product of claim 8 , wherein:

the one or more features include features from the group comprising crop samples, soil samples, pest samples, crop yield, precipitation, temperature, moisture, photos/videos of land, and classifications of land; and

the agricultural data includes data from the group comprising physical access or vehicle image annotation data, remote sensing data, weather data, soil data, crop mask data, or irrigation type data.

15 . A computer system for generating an agriculture map of a region of land, the computer system comprising:

one or more computer processors, one or more computer-readable storage media, and program instructions stored on the one or more of the computer-readable storage media for execution by at least one of the one or more processors capable of performing a method, the method comprising:

collecting agricultural data of one or more sub-regions of the region of land, wherein the agricultural data includes classified data and unclassified data;

extracting one or more features from the collected classified agricultural data;

training one or more models based on the extracted one or more features; and

generating an agricultural map of the region of land based on applying the one or more models to the collected unclassified agricultural data.

16 . The computer system of claim 15 , further comprising:

determining one or more entropy scores of the one or more sub-regions of land;

determining a first sub-region of land from which to collect additional data, wherein the first sub-region of land is the sub-region of land with the highest entropy score; and

collecting additional agricultural data of the first sub-region of land, wherein the collected agricultural data includes the collected additional agricultural data.

17 . The computer system of claim 16 , further comprising:

extracting one or more additional features from the collected additional agricultural data; and

updating the generated agricultural map based on the one or more additional features.

18 . The computer system of claim 17 , further comprising:

based on determining that a maximum collection budget is not yet exceeded:

determining a second sub-region of land from which to collect additional data, wherein the second sub-region of land is the sub-region of land with the second highest entropy score;

collecting additional agricultural data of the second sub-region of land;

extracting one or more additional features from the collected additional agricultural data; and

updating the generated agricultural map based on the one or more additional features.

19 . The computer system of claim 15 , wherein:

at least one model is trained for each sub-region for which the collected classified data was collected; and

the one or more trained models are applied to the one or more extracted features to calculate one or more probabilities of one or more possible classifications of the one or more sub-regions of land.

20 . The computer system of claim 19 , further comprising:

calculating one or more averages of the one or more probabilities of one or more possible classifications of the one or more sub-regions of land; and

calculating one or more entropy scores based on the one or more averages.