Remote-Sensing Management Zones for Broad-Scale Soil Detail
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Solution Overview
Problem
Existing precision agriculture techniques rely on localized and field-specific data sources like SSURGO, which lack the necessary detail for optimal yield and management zone delineation, leading to inefficiencies in fertilizer application and crop management.
Innovation Solution
An agricultural technology that uses remote sensing, pattern recognition, and artificial intelligence to delineate enhanced management zones over broad geographic extents, combining data from SSURGO with multi-scale terrain derivatives and spectral information to create hyper-dimensional data-cubes for optimized zone delineation and management recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SSURGO data is used for management zone delineation, then a useful approximation of soil conditions is provided, but the data lacks the necessary detail for optimal yield and management zone delineation
Solution Approach 1:
The patent combines SSURGO data with multiple additional data sources including remote sensing imagery, terrain data, weather data, and historical yield data to create a comprehensive dataset that preserves the useful soil condition approximations of SSURGO while adding the detailed information needed for optimal yield management
Solution Approach 2:
The patent transitions from two-dimensional SSURGO soil survey data to multi-dimensional data cubes that incorporate temporal, spectral, and spatial dimensions, enabling detailed analysis of soil conditions and crop management across multiple scales and time periods
2Adaptability or versatility
If localized and field-specific data sources are used, then management zones can be delineated for specific fields, but the approach lacks applicability to broad geographic extents
Solution Approach 1:
The patent creates a universal system that can operate at multiple scales, from individual field-level management to broad geographic extents, by using standardized data processing methods and multi-scale terrain derivatives that work consistently across different spatial scales
Solution Approach 2:
The patent segments the analysis into multiple scales using terrain derivatives at different resolutions, allowing detailed field-specific management zones to be nested within broader regional patterns, enabling both localized precision and broad geographic applicability
3Measurement precision
If traditional soil sampling methods are used, then soil conditions can be assessed, but the number of soil samples required is large and inefficient
Solution Approach 1:
The patent replaces mechanical soil sampling with remote sensing and pattern recognition techniques that use satellite imagery, aerial photography, and sensor data to assess soil conditions non-invasively, eliminating the need for extensive physical sampling while maintaining or improving measurement precision
Solution Approach 2:
The patent creates digital copies of soil conditions through remote sensing imagery and spectral data that serve as proxies for physical soil samples, allowing comprehensive soil assessment without the time and resource costs of traditional sampling methods
Data Source
AI summary
The present invention is a system and method for agricultural management-zone delineation to be done over broad geographic extents without overly-localized field-specific data. The instant innovation guides precision agricultural sampling and management by delineating enhanced management zones based upon remote sensing and artificial intelligence and combining the two with data derived from an existing countrywide soil survey database. In an embodiment, the instant innovation uses artificial intelligence from multiple sources to provide granular zone detail. Output of the present innovation can be aggregated to produce management zone sizes that have a level of uncertainty compatible with the needs of the customer-farmer and implementable given the capabilities of available equipment.