Remote Sensing Crop Performance Index for Targeted Pest Control
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Solution Overview
Problem
Conventional methods for crop pest management involve blanket chemical applications over large areas, which are wasteful, expensive, and environmentally harmful, as they do not efficiently target specific areas affected by biological pests, leading to yield losses and environmental damage.
Innovation Solution
The use of digital maps developed from remotely sensed data, specifically Earth Observation Satellite (EOS) data, to identify and target areas affected by biological pests, allowing for precise chemical application through a three-part process: atmospheric correction, calculation of a Crop Performance Index (CPI), and guided scouting and application, using band balancing and statistical methods to isolate and track poor-performing areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blanket chemical application is used over large areas, then crop protection coverage is improved, but chemical waste and environmental harm increase
Solution Approach 1:
The field is segmented into multiple zones based on pest presence data from remote sensing images. Each zone is then treated independently with chemical applications only applied to zones where pests are detected, rather than treating the entire field uniformly. This segmentation allows targeted treatment that maintains protection reliability while reducing chemical waste.
Solution Approach 2:
Different treatment strategies are applied to different locations within the field based on local pest conditions. Areas with detected pests receive chemical treatment, while areas without pests receive no treatment or alternative non-chemical control methods. This local differentiation ensures adequate protection where needed while avoiding unnecessary chemical application elsewhere.
2Reliability
If blanket chemical application is used over large areas, then crop protection coverage is improved, but environmental harm increases
Solution Approach 1:
The field is divided into treated and untreated segments based on pest detection. Chemical applications are restricted to only those segments where pests are present, preventing chemical exposure in areas where it is not needed. This reduces environmental contamination from runoff and drift while maintaining adequate crop protection in affected areas.
Solution Approach 2:
Remote sensing technology that detects pest presence is used to identify exactly where chemical application is necessary, converting the potential harm of chemical use into a benefit by enabling precise targeting. The detection capability transforms the problem of chemical over-application into a solution where chemicals are applied only where beneficial.
3Measurement precision
If field scouting is performed on foot, then accurate pest identification is improved, but time efficiency and coverage area deteriorate
Solution Approach 1:
Remote sensing satellites and aerial imagery serve as intermediaries between the farmer and the crop field. These intermediaries capture visual data about pest presence across large areas, providing information that would otherwise require time-consuming manual scouting. The intermediary technology maintains identification accuracy while dramatically improving coverage efficiency.
Solution Approach 2:
Manual field scouting is replaced with remote sensing technology that uses optical and spectral measurements to detect pest presence. This substitution eliminates the need for physical traversal of fields by personnel, allowing rapid assessment of large areas while maintaining the ability to identify pests accurately through image analysis.
4Measurement precision
If manual field scouting is performed, then pest identification accuracy is improved, but time consumption and cost increase
Solution Approach 1:
Remote sensing images are captured and analyzed before field scouting or chemical application decisions are made. This preliminary action provides advance information about pest locations, allowing farmers to plan targeted scouting routes and treatment strategies. The preliminary remote detection reduces the time needed for subsequent manual verification and treatment planning.
Solution Approach 2:
Remote sensing technology acts as a preliminary intermediary that screens large areas for pest presence, filtering out areas that do not require further investigation. This intermediary step reduces the overall time investment needed for complete field assessment by identifying problem areas that warrant closer inspection while eliminating areas that can be managed without intervention.
Data Source
AI summary
A method for precisely applying chemicals targeted by digital maps developed from remotely sensed data, including: obtaining EOS data through a growing season of a crop growing in a field; processing the EOS data to reflectance values; removing error-inducing effects of atmospheric alteration from the processed EOS data; calculating from the processed EOS data a crop performance index that indicates one or more poor performing areas of the field; generating one or more maps of the crop performance index to allow a user to determine whether each of the one or more poor performing areas of the field are due to biological pests instead of topographic or soil constraints in discrete locations of the field; guiding the user to the one or more poor performing areas of the field using the one or more maps to allow the user to scout the one or more poor performing areas of the field to confirm and identify the biological pests; and providing guidance for a chemical application at the one or more poor performing areas that were confirmed as having the biological pests. Other embodiments are provided.