Abstract: A method for generating digital models of potential crop yield based on planting date, relative maturity, and actual production history is provided. In an embodiment, data representing historical planting dates, relative maturity values, and crop yield is received by an agricultural intelligence computer system. Based on the historical data, the system generates spatial and temporal maps of planting dates, relative maturity, and actual production history. Using the maps, the system creates a model of potential yield that is dependent on planting date and relative maturity. The system may then receive actual production history data for a particular field. Using the received actual production history data, a particular planting date, and a particular relative maturity value, the agricultural intelligence computer system computes a potential yield for a particular field.

Abstract: In an embodiment, a method comprises determining, in received yield data, one or more passes, each pass including a plurality of observations. For each pass of the one or more passes, one or more discrete derivatives are determined, and based on the one or more discrete derivatives first outlier data is generated. First filtered data is generated by removing the first outlier data from the yield data. Furthermore, for each observation in the yield data, a plurality of nearest neighbor observations is determined, and used to determine a plurality of absolute differences in yield values. Based on the plurality of absolute differences, second outlier data is determined. Second filtered data is generated by removing the second outlier data from the first filtered data. Using a presentation layer of a computer system, a graphical representation of the second filtered data is generated and displayed on the computing system.

Abstract: Systems, methods and apparatus for monitoring soil properties and applying fertilizer during a planting operation. Various sensors are disposed in ground engaging components for monitoring soil properties. The ground engaging components may have structure for opening a side trench in the sidewalls of the seed trench and may include liquid application conduits for injecting liquid into the sidewalls of the resulting side trenches.

Abstract: A protective connector includes a core assembly structure, mating pins and a mating coupling structure. The core assembly structure has circuitry mounted therein. The mating coupling structure substantially encases the core assembly structure and mates with another connector such that the mating pins of the protective connector are electrically coupled to pins of the other connector. The mating coupling structure is mechanically free-moving with respect to the core assembly structure such that forces applied to the mating coupling structure to mate the protective connector to the other connector are not applied to the circuitry within the core assembly structure.

Abstract: In an approach, a computer receives an observation dataset that identifies one or more ground truth values of an environmental variable at one or more times and a reforecast dataset that identifies one or more predicted values of the environmental variable produced by a forecast model that correspond to the one or more times. The computer then trains a climatology on the observation dataset to generate an observed climatology and trains the climatology on the reforecast dataset to generate a forecast climatology. The computer identifies observed anomalies by subtracting the observed climatology from the observation dataset and forecast anomalies by subtracting the forecast climatology from the reforecast dataset. The computer then models the observed anomalies as a function of the forecast anomalies, resulting in a calibration function, which the computer can then use to calibrate new forecasts received from the forecast model.

Abstract: In an approach, hyperspectral and/or multispectral remote sensing images are automatically analyzed by a nitrogen analysis subsystem to estimate the value of nitrogen variables of crops or other plant life located within the images. For example, the nitrogen analysis subsystem may contain a data collector module, a function generator module, and a nitrogen estimator module. The data collector module prepares training data which is used by the function generator module to train a mapping function. The mapping function is then used by the nitrogen estimator module to estimate the values of nitrogen variables for a new remote sensing image that is not included in the training set. The values may then be reported and/or used to determine an optimal amount of fertilizer to add to a field of crops to promote plant growth.

Abstract: A system for detecting clouds and cloud shadows is described. In one approach, clouds and cloud shadows within a remote sensing image are detected through a three step process. In the first stage a high-precision low-recall classifier is used to identify cloud seed pixels within the image. In the second stage, a low-precision high-recall classifier is used to identify potential cloud pixels within the image. Additionally, in the second stage, the cloud seed pixels are grown into the potential cloud pixels to identify clusters of pixels which have a high likelihood of representing clouds. In the third stage, a geometric technique is used to determine pixels which likely represent shadows cast by the clouds identified in the second stage. The clouds identified in the second stage and the shadows identified in the third stage are then exported as a cloud mask and shadow mask of the remote sensing image.

Abstract: A system and method for improving radar based precipitation estimates using spatiotemporal interpolation is provided. In an embodiment, an agricultural intelligence computer system receives a plurality of radar based precipitation rate values representing precipitation rate measurements at a plurality of locations and a plurality of times. The agricultural intelligence computer system identifies a first non-zero radar based precipitation rate value associated with a first location of the plurality of locations and a first time of the plurality of times. The agricultural intelligence computer also identifies a second non-zero radar based precipitation rate value associated with a second location of the plurality of locations and a second time of the plurality of times. The agricultural intelligence computer system determines that the first non-zero radar based precipitation rate value corresponds to the second non-zero radar based precipitation rate value.

Abstract: A method begins by a drive unit affiliated with farm equipment receiving data from the farm equipment to produce agricultural data. The method continues with the drive unit determining a filtering constraint based on one or more parameters selected from a plurality of lists of agricultural parameters and filtering the agricultural data based on the filtering constraint to produce filtered agricultural data. The method continues with the drive unit determining processing of the filtered agricultural data and executing the processing of the filtered agricultural data.

Abstract: Some embodiments include a method. The method can include mapping a spatial pattern of yield for a crop of an agricultural field and prescribing spatially-variable application rates of one or more nutrients for the agricultural field. Other embodiments of related methods and systems are also disclosed.

Abstract: Systems and methods for generation of images of a particular type from images of a different type are disclosed. In an embodiment, an agricultural intelligence computer system receives a first plurality of images of a first type and a second plurality of images of a second type. The first and second types may refer to variances in resolution, frequency ranges of frequency bands, and/or types of frequency bands used to generate the images. Based on the first plurality of images and the second plurality of images, the agricultural intelligence computer system generates a feature set dictionary comprising mappings from features of the first plurality of images to features of the second plurality of images. When the agricultural intelligence computer system receives a particular image of the first type, the agricultural intelligence computer system uses the received image and the feature set dictionary to generate an image of the second type.

Abstract: In an embodiment, computer processes are programmed to determine planting plans based on planting characteristics data received for an agricultural field and a plurality of management zone delineation options defined for the agricultural field. Each of the planting plans specifies different planting recommendations for the agricultural field. A first graphical representation of the planting plans, and an interactive object is generated and displayed on a computing device. The interactive object is configured to receive input specifying a relative importance ratio between the planting plans for determining a new planting plan for the agricultural field. A particular relative importance ratio is received via the interactive object, and is used to determine the new planting plan, which specifies new planting recommendations for the agricultural field. Information about the new planting plan is displayed on the computer device.

Abstract: A system for identifying ponding water located on a field from image data is described. In an approach, an image of an agricultural field is analyzed using a classifier that has been trained based on the spectral bands of labeled image pixels to identify a probability for each pixel within the image that the pixel corresponds to water. A flow simulation is performed to determine regions of the field that are likely to pool water after rainfall based on precipitation data, elevation data, and soil property data of the field. A graph of vertices representing the pixels and edges representing connections between neighboring pixels is generated. The probability of each pixel within the graph being ponding water is set based on the probability pixel being water, the likelihood that water will pool in the area represented by the pixel, the probability of neighboring pixels being ponding water, and a cropland mask that identifies which pixels correspond to cropland.

Abstract: Systems, methods and apparatus are provided for monitoring soil properties including soil moisture, soil electrical conductivity and soil temperature during an agricultural input application. Embodiments include a soil reflectivity sensor and/or a soil temperature sensor mounted to a seed firmer for measuring moisture and temperature in a planting trench. A thermopile for measuring temperature via infrared radiation is described herein. In one example, the thermopile is disposed in a body and senses infrared radiation through an infrared transparent window. Aspects of any of the disclosed embodiments may be implemented in or communicate with an agricultural intelligence computer system as described herein.

Abstract: A method begins by a computing device allocating a plurality of tasks of an agricultural prescription for a farming geographic area to a fleet of farming equipment. While executing tasks of the plurality of tasks, the method continues with at least some of the fleet of farming equipment collecting task execution data. Based on the task execution data, the method continues with the computing device updating at least one of the agricultural prescription, the plurality of tasks, and the allocation of at least one task of the plurality of tasks.

Abstract: A method begins by agriculture equipment collecting current on-site gathered agriculture data regarding an agriculture region and sending at least a representation of the current on-site gathered agriculture data to a host device. The method continues with the host device processing one or more of the at least a representation of the current on-site gathered agriculture data, current off-site gathered agriculture data, historical on-site gathered agriculture data, historical off-site gathered agriculture data, and historical analysis of agriculture predictions regarding the agriculture region to produce a current agriculture prediction for the agriculture region. The method continues with the host device generating an agriculture prescription regarding at least a portion of the agriculture region based on the current agriculture prediction and sending the agriculture prescription to one or more of the agriculture equipment.

Abstract: Described herein are systems and methods for capturing images of a field and performing agricultural data analysis of the images. In one embodiment, a computer system for monitoring field operations includes a database for storing agricultural image data including images of at least one stage of crop development that are captured with at least one of an apparatus and a remote sensor moving through a field. The computer includes at least one processing unit that is coupled to the database. The at least one processing unit is configured to execute instructions to analyze the captured images, to determine relevant images that indicate a change in at least one condition of the crop development, and to generate a localized view map layer for viewing the field at the at least one stage of crop development based on at least the relevant captured images.

Abstract: A method for agronomic and agricultural monitoring includes designating an area for imaging, determining a flight path above the designated area, operating an unmanned aerial vehicle (UAV) along the flight path, acquiring images of the area using a camera system attached to the UAV, and processing the acquired images.

Abstract: A method begins by a computing device allocating a plurality of tasks of an agricultural prescription for a farming geographic area to a fleet of farming equipment. While executing tasks of the plurality of tasks, the method continues with at least some of the fleet of farming equipment collecting task execution data. Based on the task execution data, the method continues with the computing device updating at least one of the agricultural prescription, the plurality of tasks, and the allocation of at least one task of the plurality of tasks.

Abstract: Systems, methods and apparatus for detecting stalks processed by a combine harvester, for measuring stalk diameters, and for displaying harvest metrics and yield data to a user based on stalk locations and stalk diameters.