Crop Yield Mapping via Geospatial Data Segmentation
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Solution Overview
Problem
Current crop yield mapping technologies face challenges in accurately associating crop yield with specific geographic areas due to limitations in data resolution and variability caused by factors like elevation changes, equipment ingest rate fluctuations, and difficulty in distinguishing between target crops and weeds.
Innovation Solution
A method and system for generating improved crop yield maps using geospatially distributed data types such as vegetation index imagery, LIDAR data, and stand count data, which allows for more accurate allocation of crop yield values across a field area by processing pixel value distribution patterns and adjusting initial yield distributions based on additional data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If harvest equipment is configured to harvest multiple rows of crops simultaneously to improve productivity, then harvesting efficiency is improved, but the ability to accurately associate crop yield with specific geographic areas deteriorates
Solution Approach 1:
The patent segments the field into multiple zones or blocks and associates yield data with specific geographic coordinates by dividing the harvesting process into discrete spatial units. This allows the system to maintain high productivity while improving measurement precision by linking yield data to specific geographic areas through segmented spatial analysis.
Solution Approach 2:
The patent introduces an intermediary data processing system that receives yield data from the harvester and mediates between the yield measurements and geographic location data. This intermediary system processes and correlates the data types to accurately associate crop yield with specific geographic areas, resolving the contradiction between efficient harvesting and precise mapping.
2Adaptability or versatility
If harvest equipment ingest rate changes to adapt to terrain variations such as hills and valleys, then harvesting capability is improved, but the association between crop yield and specific area deteriorates
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor the harvest equipment's ingest rate and adjust the yield mapping process accordingly. By feeding back information about changes in ingest rate caused by terrain variations, the system can compensate for these changes and maintain accurate association between crop yield and specific geographic areas while adapting to terrain variations.
Solution Approach 2:
The patent changes parameters in the data processing system to account for ingest rate variations. By adjusting mapping parameters based on detected changes in harvest equipment speed and terrain conditions, the system maintains measurement precision while preserving terrain adaptability.
3Measurement precision
If additional data types are processed to improve crop yield distribution accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies partial action by selectively processing only the necessary data types for each specific field or zone rather than uniformly processing all available data. This approach improves measurement precision for crop yield distribution while reducing overall device complexity by avoiding unnecessary data processing operations.
Solution Approach 2:
The patent performs preliminary actions by pre-processing and organizing data types before they are needed for yield mapping. By preparing and structuring data in advance, the system reduces the complexity of real-time processing while maintaining high measurement precision for accurate crop yield distribution analysis.
Data Source
AI summary
Systems and methods for generating crop yield maps are provided. In one example embodiment, a method comprises accessing data indicative of crop yield for a field area; accessing one or more data types associated with the field area, each of the data types providing a geospatial distribution of data associated with vegetation across the field area; determining a crop yield distribution for the field area; and generating a yield map for the field area based at least partially on the crop yield distribution.