A framework for diagnosing and predicting a suitability of soil conditions to various agricultural operations is performed in a combined, multi-part approach for simulating relationships between predictive data and observable outcomes. The framework includes analyzing one or more factors relevant to field trafficability, workability, and suitability for agricultural operations due to the effects of freezing and thawing cycles, and developing artificial intelligence systems to learn relationships between datasets to produce improved indications of trafficability, workability, and forecasts of suitability windows for a particular user, user community, farm, farm group, field, or equipment. The framework also includes a real-time feedback mechanism by which a user can validate or correct these indications and forecasts. The framework may further be configured to override one or more of the soil state assessments to ensure that indicators and forecasts are consistent with the recently-provided feedback.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of diagnosing and predicting in-field soil conditions for assessing a field's trafficability, comprising: diagnosing and predicting weather conditions impacting soil conditions in a particular field by profiling expected weather conditions for the particular field from at least one of in-situ weather data, remotely-sensed weather data, and modeled weather data; simulating an expected soil condition response in the particular field from crop and soil characteristics in the particular field and the diagnosed and predicted weather conditions using an agronomic model of one or more physical and empirical characteristics impacting soil conditions in the particular field; associating one or more observations of field conditions and soil properties that are indicative of a temporal variability of soil moisture content impacting soil compaction and structural capacity for access to and support for agricultural equipment, from at least one of the particular field and one or more other fields with similar crop and soil characteristics, at one or more times, with the diagnosed and predicted weather conditions, simulated expected soil condition response, and the crop and soil characteristics using one or more artificial intelligence models; translating a combined analysis of the diagnosed and predicted weather conditions, the expected soil condition response, the crop and soil characteristics, and associations of the one or more observations from the one or more artificial intelligence models into a trafficability profile of the soil compaction and structural capacity for access to and support for agricultural equipment; and generating one or more indicators of field trafficability from the trafficability profile, the one or more indicators including at least one of a numerical value representing field trafficability, a non-numerical index of field trafficability, and an indicator of soil suitability for agricultural equipment in the particular field. 2. The method of claim 1, further comprising training the one or more artificial intelligence models with the one or more observations of field conditions and soil properties to continually perform the combined analysis of the diagnosed and predicted weather conditions, the expected soil response, the crop-specific characteristics, the soil data, and the field-specific location data. 3. The method of claim 1, further comprising comparing the trafficability profile to the one or more observations of field conditions and soil properties, and forcing the one or more indicators to temporarily adapt to the one or more observations of field conditions and soil properties for a specified period of time. 4. The method of claim 1, further comprising comparing the trafficability profile to the one or more observations of field conditions and soil properties, and forcing the one or more indicators to permanently adapt to the one or more observations of field conditions and soil properties. 5. The method of claim 1, wherein the one or more observations of field conditions and soil properties are at least one of ground truth feedback of sampled soil moisture content and measurements of crop moisture content, data captured by sensors on-board agricultural equipment, data received from GPS transmitters installed on agricultural equipment, and satellite imagery data of a geographical area comprising the particular field. 6. The method of claim 1, wherein the agronomic model includes a land surface model. 7. The method of claim 1, wherein the crop and soil characteristics comprise crop and planting data that includes one or more of crop type data, planting data, growing season data comprising an anticipated length of the crop growing season and one or more anticipated harvest windows, and crop information generated from a crop growth model configured to indicate various stages of crop growth for the particular field. 8. The method of claim 1, wherein the crop and soil characteristics comprise soil data that includes at least one of soil type and surface and subsurface drainage and irrigation properties in the particular field. 9. The method of claim 1, wherein the one or more indicators further comprise at least one of an indicator of a risk of soil compaction, an indicator of soil temperature over time, an indicator of soil moisture content over time, an indicator of soil productivity degradation from a compaction of soil, an indicator of soil structure damage from excessive density inhibiting plant root penetration and distribution, an indicator of excessive soil surface residue, and an indicator of organic matter content level. 10. The method of claim 1, further comprising generating, as output data, one or more indicators customized to a specific field, a specific crop, or specific item of agricultural equipment. 11. The method of claim 1, further comprising applying the trafficability profile of the soil compaction and structural capacity for access to and support for agricultural equipment to a decision support tool configured to provide one or more advisories of the field trafficability to a user. 12. A system of diagnosing and predicting in-field soil conditions for assessing field trafficability, comprising: a computing environment including at least one computer-readable storage medium having program instructions stored therein and a computer processor operable to execute the program instructions to model field trafficability within a plurality of data processing modules, the plurality of data processing modules including: a weather modeling module configured to diagnose and predict weather conditions impacting soil conditions in a particular field, by profiling expected weather conditions for the particular field from at least one of in-situ weather data, remotely-sensed weather data, and modeled weather data; one or more modules configured to 1) simulate an expected soil condition response to the diagnosed and predicted weather conditions, and to crop and soil characteristics for the particular field in an agronomic model of one or more physical and empirical characteristics impacting soil conditions in the particular field, and 2) associate one or more observations of field conditions and soil properties that are indicative of a temporal variability of soil moisture content impacting soil compaction and structural capacity for access to and support for agricultural equipment, from at least one of the particular field and one or more other fields with similar crop and soil characteristics at one or more times, with the diagnosed and predicted weather conditions, simulated expected soil condition response, and crop and soil characteristics using one or more artificial intelligence models; and a translation module configured to train the one or more artificial intelligence models using the one or more observations of field conditions and soil properties and perform a combined analysis of the diagnosed and predicted weather conditions, the expected soil condition response, the crop and soil characteristics, and associations to the one or more observations from the one or more artificial intelligence models to model a trafficability profile of soil compaction and structural capacity for access to and support for agricultural equipment, and generate one or more indicators of field trafficability from the trafficability profile, that include at least one of a numerical value representing field trafficability, a non-numerical index of field trafficability, and an indicator of soil suitability for agricultural equipment in the particular field. 13. The system of claim 12, wherein the translation module is further configured to force the one or more indicators to temporarily adapt to the one or more observations of field conditions and soil properties for a specified period of time. 14. The system of claim 12, wherein the translation module is further configured to force the one or more indicators to permanently adapt to the one or more observations of field conditions and soil properties. 15. The system of claim 12, wherein the one or more observations of field conditions and soil properties are at least one of ground truth feedback of sampled soil moisture content and measurements of crop moisture content, data captured by sensors on-board agricultural equipment, data received from GPS transmitters installed on agricultural equipment, and satellite imagery data of a geographical area comprising the particular field. 16. The system of claim 12, wherein the agronomic model includes a land surface model. 17. The system of claim 12, wherein the crop and soil characteristics comprise crop and planting that includes one or more of crop type data, planting data, growing season data comprising an anticipated length of the crop growing season and one or more anticipated harvest windows, and crop information generated from a crop growth model configured to indicate various stages of crop growth for the particular field. 18. The system of claim 12, wherein the crop and soil characteristics comprise soil data that includes at least one of soil type and surface and subsurface drainage and irrigation properties in the particular field. 19. The system of claim 12, wherein the one or more indicators further comprise at least one of an indicator of a risk of soil compaction, an indicator of soil temperature over time, an indicator of soil moisture content over time, an indicator of soil productivity degradation from a compaction of soil, an indicator of soil structure damage from excessive density inhibiting plant root penetration and distribution, an indicator of excessive soil surface residue, and an indicator of organic matter content level. 20. The system of claim 12, further comprising generating, as output data, one or more indicators customized to a specific field, a specific crop, or specific item of agricultural equipment. 21. The system of claim 12, wherein the trafficability profile is applied to a diagnostic support tool configured to provide one or more advisories to a user. 22. A method of assessing a soil state for field trafficability, comprising: ingesting, as input data, weather information, and crop and soil characteristics, the weather information including at least one of in-situ weather data, remotely-sensed weather data, and modeled weather data; modeling the input data in a plurality of data processing modules within a computing environment in which the plurality of data processing modules are executed in conjunction with at least one processor, the data processing modules configured to assess a soil state in a particular field, by: applying the weather information to one or more weather models to diagnose and predict weather conditions that impact soil conditions in the particular field, applying the diagnosed and predicted weather conditions, and the crop and soil characteristics to a land surface model to simulate an expected soil condition response, and applying one or more observations of field conditions and soil properties that are indicative of a temporal variability of soil moisture content impacting soil compaction and structural capacity for access to and support for agricultural equipment from at least one of the particular field and one or more other fields with similar crop and soil characteristics, at one or more times, to train one or more artificial intelligence models configured to produce a trafficability profile of soil compaction and structural capacity for access to and support for agricultural equipment and generate associations to the one or more observations; and combining an analysis of the diagnosed and predicted weather conditions, the expected soil condition response, the crop and soil characteristics, and the associations to the one or more observations in the one or more artificial intelligence models to translate the trafficability profile into one or more indicators of field trafficability, wherein the one or more indicators are customized to a specific field, a specific crop, or specific item of agricultural equipment. 23. The method of claim 22, wherein the one or more indicators including at least one of a numerical value representing field trafficability, a non-numerical index of field trafficability, and an indicator of soil suitability for agricultural equipment in the particular field. 24. The method of claim 22, wherein the one or more indicators further comprise at least one of an indicator of a risk of soil compaction, an indicator of soil temperature over time, an indicator of soil moisture content over time, an indicator of soil productivity degradation from a compaction of soil, an indicator of soil structure damage from excessive density inhibiting plant root penetration and distribution, an indicator of excessive soil surface residue, and an indicator of organic matter content level. 25. The method of claim 22, further comprising forcing the one or more indicators to temporarily adapt to the one or more observations of field conditions and soil properties for a specified period of time. 26. The method of claim 22, further comprising forcing the one or more indicators to permanently adapt to the one or more observations of field conditions and soil properties. 27. The method of claim 22, wherein the one or more observations of field conditions and soil properties are at least one of ground truth feedback of sampled soil moisture content and measurements of crop moisture content, data captured by sensors on-board agricultural equipment, data received from GPS transmitters installed on agricultural equipment, and satellite imagery data of a geographical area comprising the particular field. 29. The method of claim 22, wherein the crop and soil characteristics comprise crop and planting data that includes one or more of crop type data, planting data, growing season data comprising an anticipated length of the crop growing season and one or more anticipated harvest windows, and crop information generated from a crop growth model configured to indicate various stages of crop growth for the particular field. 29. The method of claim 22, wherein the crop and soil characteristics comprise soil data that includes at least one of soil type and surface and subsurface drainage and irrigation properties in the particular field. 30. The method of claim 22, further comprising applying the trafficability profile of the soil compaction and structural capacity for access to and support for agricultural equipment to a decision support tool configured to provide one or more advisories of the field trafficability to a user.