Residue Coverage Estimation Using Multi-Temporal Field Imaging
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Solution Overview
Problem
Current systems for determining residue coverage in agricultural fields are not sufficiently accurate, as they typically rely on single-image data captured shortly before harvest, failing to account for conditions early in the crop-growing period that impact residue amounts.
Innovation Solution
A method and system that utilize multiple images captured at different times during the crop-growing period, analyzed by a controller to generate an estimated residue coverage map, which is then used to create a prescription map for optimizing subsequent agricultural operations like tillage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single-image data captured shortly before harvest is used to determine residue coverage, then the system complexity is low, but the measurement precision of residue coverage is insufficient
Solution Approach 1:
The system captures images at multiple time points during the crop-growing period (planting, mid-season, pre-harvest) rather than relying solely on pre-harvest images. This preliminary action of collecting data throughout the growing season allows for more accurate residue coverage estimation by accounting for crop health and environmental conditions that affect residue amounts, resolving the contradiction between measurement precision and system complexity
Solution Approach 2:
The system uses a prescription map generated from multi-temporal image analysis to guide tillage operations. The residue coverage estimation feedback from multiple time points allows farmers to adjust tillage, fertilizing, and drainage practices, creating a closed-loop system that improves measurement accuracy without excessive complexity increase
2Measurement precision
If multiple images captured at different times during the crop-growing period are used, then the measurement precision of residue coverage improves, but the loss of time increases
Solution Approach 1:
Images are captured at predetermined time points (planting, mid-season, pre-harvest) during the crop-growing period, allowing residue coverage estimation to be performed in advance of harvest. This preliminary action reduces time loss by preparing residue maps before the critical harvest-tillage window, while the automated processing keeps time investment manageable
Solution Approach 2:
The system captures images at three time points, which may be more than the single pre-harvest image traditionally used. This partial excessive action (capturing more images than minimum needed) improves measurement precision by accounting for crop development and environmental factors, while the automated processing pipeline prevents time loss from becoming excessive
Data Source
AI summary
A method for determining residue coverage within a field may include receiving, with one or more computing devices, first and second images of the field. The first image may depict a portion of the field at a first time during a crop-growing period and the second image may depict the portion of the field at a second time during the crop-growing period, with the first and second times being different. Furthermore, the method may include generating, with the one or more computing devices, an estimated residue coverage map for the field based on the received first and second images. Additionally, the method may include generating, with the one or more computing devices, a prescription map for the field based on the estimated residue coverage map.