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Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method
Longlong Li1,2,3, Ruirui Zhang1,2,3, Liping Chen1,2,3
1Research Center of Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing, China.
Frontiers in Plant Science
|August 4, 2022
Summary
This study introduces a 3D LiDAR sensor method for evaluating agricultural spray drift, offering a faster alternative to traditional passive collectors. The new technique shows high accuracy in measuring drift patterns, demonstrating its potential for rapid assessment.
Area of Science:
- Agricultural Engineering
- Environmental Science
- Sensor Technology
Background:
- Spray drift is a significant concern in agricultural plant protection, impacting environmental safety and operational efficiency.
- Conventional methods for spray drift evaluation using passive collectors are time-consuming and labor-intensive.
- There is a need for rapid and efficient methods to assess spray drift.
Purpose of the Study:
- To present and validate a novel method for evaluating spray drift using a 3D LiDAR sensor.
- To test the feasibility of 3D LiDAR as an alternative to passive drift collectors.
- To analyze the influencing factors on the 3D LiDAR spray drift assessment method.
Main Methods:
- Developed a spray drift measurement algorithm based on 3D LiDAR point cloud data.
- Conducted wind tunnel tests with various agricultural nozzles, spray pressures, and wind speeds.
- Compared 3D LiDAR measurements with data from traditional passive collectors (polyethylene lines).
Main Results:
- 3D LiDAR provides detailed spatial information on drift droplet distribution (height, width).
- High correlation (R² > 0.75) was found between 3D LiDAR measurements and passive collector data.
- The anti-drift IDK12002 nozzle at 0.2 MPa showed the highest correlation (R² = 0.9583).
- LiDAR detection is sensitive to droplet density, drift mass, and nozzle droplet spectrum.
Conclusions:
- 3D LiDAR technology shows significant potential as a rapid and effective alternative for spray drift assessment.
- The method offers a more efficient approach compared to conventional labor-intensive techniques.
- Further research is needed to refine detection thresholds for optimal LiDAR performance.
