Satellite Image Irrigation Trial Layout for Matched Field Sectors
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Solution Overview
Problem
Growers using center pivot irrigation systems face challenges in efficiently comparing different irrigation management systems due to limitations in treatment placement, leading to increased acreage and costs for trials, which complicates the interpretation of results and increases risks for both growers and vendors.
Innovation Solution
A computer-implemented method that uses digital images to optimize the arrangement of irrigation treatments within a single field, ensuring matching crop growing conditions across sectors, allowing for fair comparison and reducing the need for extensive acreage, by analyzing density histograms and quantifying dissimilarity metrics to select the most similar growing conditions for treatment placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional randomized treatment placement is used in center pivot irrigation fields, then fair comparison of irrigation management systems is achieved, but multiple fields with different growing conditions are required, increasing acreage and costs
Solution Approach 1:
The patent applies local quality by analyzing spatial variability within a single field using satellite imagery to identify zones with similar growing conditions. Treatments are placed in sectors with matched local characteristics (soil type, crop variety, planting date, historical yield) rather than random placement, enabling fair comparisons while confining trials to one field.
Solution Approach 2:
The patent transitions from traditional two-dimensional field layout considerations to a multi-dimensional approach by incorporating satellite imagery data, soil characteristics, crop metadata, and historical yield information. This dimensional expansion enables precise matching of growing conditions within a single field's spatial framework.
2Adaptability or versatility
If multiple fields are used for irrigation management trials, then treatment comparison is possible, but interpretation of results is complicated by different growing conditions
Solution Approach 1:
By ensuring that all treatment sectors within a single field share matched local qualities (soil, crop, management history), the patent eliminates confounding variables that arise when comparing across multiple fields. This local matching preserves result interpretability while maintaining treatment comparison capability.
Solution Approach 2:
The patent merges multiple data dimensions (satellite imagery, soil data, crop metadata, historical yield) into a unified analysis framework that identifies optimal treatment placement within a single field, combining information that would traditionally require multiple separate field trials.
3Adaptability or versatility
If extensive acreage is used for trials, then sufficient treatment placement options are available, but costs and compensation for growers increase
Solution Approach 1:
The patent adds informational dimensions (satellite imagery, soil characteristics, crop metadata, historical data) to the traditional spatial framework, enabling sufficient treatment placement options to be identified within a single field's acreage rather than requiring extensive land area.
Solution Approach 2:
The patent changes the parameters used for treatment placement from simple random or systematic layouts to optimized placements based on multiple matched parameters (soil type, crop variety, planting date, historical yield, satellite-derived vegetation indices), maximizing treatment comparison capability within constrained acreage.
4Area of stationary object
If single field trial is used, then acreage and costs are reduced, but treatment placement options are limited by equipment capabilities
Solution Approach 1:
The patent introduces dynamics by using satellite imagery to capture temporal changes in vegetation and growing conditions, enabling the identification of optimal treatment sectors that adapt to actual field conditions rather than relying on static, pre-defined layouts constrained by equipment capabilities.
Solution Approach 2:
The patent transforms the static treatment placement problem into a dynamic optimization by considering multiple parameters (soil, crop, history, satellite data) and using algorithms to identify the best sector arrangements that match growing conditions while accommodating center pivot irrigation constraints.
Data Source
AI summary
Techniques for providing improvements in agricultural science by optimizing irrigation treatment placements for testing are provided, including analyzing a plurality of digital images of a field to determine vegetation density changes in a sector of the field. The techniques proceed by comparing a distribution of pixel characteristics in the digital images for each field sector to determine sectors in which minimal density deviations are present. Instructions for irrigation placements and testing may be displayed or modified based on the results of the sector determinations.