Refined Average for Agricultural Management Zones
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Solution Overview
Problem
Current methods for determining management zones in agricultural fields are inefficient due to the high cost of direct soil property measurements and the inability to accurately use indicators at lower densities, leading to inaccurate and costly zone delineation.
Innovation Solution
A refined average method combining vegetation indices from multi-year satellite imagery using statistical moments and classification techniques, such as the weighted natural breaks method, to create a management zone map that is robust to outliers and provides continuous transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct measurement of soil properties is used to determine fertility zone boundaries, then measurement precision is improved, but cost increases prohibitively
Solution Approach 1:
The patent uses satellite imagery as a copy or proxy for direct soil measurement. Instead of physically measuring soil properties at numerous locations, the system captures remote sensing data that correlates with soil characteristics, enabling zone delineation at a fraction of the cost while maintaining practical precision for agricultural management decisions
Solution Approach 2:
The patent introduces satellite imagery as an intermediary between the need for soil property information and the actual measurement process. The imagery serves as a mediator that provides indirect but cost-effective information about soil properties, eliminating the need for expensive direct measurements while still enabling accurate management zone identification
2Quantity of substance
If indicators measured at lower density are used to determine management zones, then cost is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent combines multiple satellite imagery indicators (vegetation indices, surface temperature, moisture content) with ancillary data (soil maps, topography, historical yield data) to create a composite dataset. This merging of multiple lower-density indicators compensates for the reduced measurement density, maintaining zone delineation precision while keeping costs low
Solution Approach 2:
The patent creates a composite information product by integrating multiple data sources with different characteristics. The final management zone map is a composite result that synthesizes information from satellite imagery, soil data, topography, and historical records, achieving high precision through the combined strength of multiple lower-density indicators rather than relying on a single high-density measurement source
3Reliability
If multiple vegetation index images from different years are combined, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent transforms multiple vegetation index images by applying statistical transformations (mean, standard deviation, skewness) to create a refined average image. This parameter change approach consolidates multi-year data into a single reliable representation of field variability, improving zone delineation reliability while managing processing complexity through mathematical transformation rather than complex algorithmic processing
Data Source
AI summary
A method for determining management zones within an agricultural field, the method includes selecting a plurality of remotely sensed images of the agricultural field wherein the plurality of remotely sensed images represent a plurality of growing seasons, each of the plurality of remotely sensed images having a vegetation index associated therewith, generating a refined average image from the plurality of remotely sensed images of the agricultural field, and applying a classification method to define management zones associated with the refined average image.