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Wheat Height Estimation Using LiDAR in Comparison to Ultrasonic Sensor and UAS.
Wenan Yuan1, Jiating Li2, Madhav Bhatta3
1Biological Systems Engineering Department, University of Nebraska⁻Lincoln, Lincoln, NE 68503, USA. wenan.yuan@huskers.unl.edu.
Sensors (Basel, Switzerland)
|November 8, 2018
Summary
Light detection and ranging (LiDAR) and unmanned aircraft systems (UAS) offer accurate and efficient methods for measuring wheat plant height, surpassing traditional manual evaluations. These technologies provide reliable alternatives for crop phenotyping.
Area of Science:
- Agricultural Science
- Remote Sensing Technology
- Crop Phenotyping
Background:
- Manual plant height measurement is time-consuming, labor-intensive, and error-prone.
- Advancements in remote and proximal sensing offer objective and efficient crop measurement alternatives.
- Direct comparisons of different plant height measurement techniques are limited.
Purpose of the Study:
- To compare the accuracy of different sensor technologies for estimating wheat plant height.
- To evaluate a ground-based multi-sensor phenotyping system against manual measurements and unmanned aircraft systems (UAS).
- To identify reliable remote sensing methods for efficient crop height evaluation.
Main Methods:
- Development of a ground-based phenotyping system with ultrasonic sensors and light detection and ranging (LiDAR).
- Estimation of wheat canopy heights across 100 plots five times during a growing season.
- Comparison of ground-based system data, UAS data, and manual measurements.
Main Results:
- LiDAR demonstrated the highest accuracy with a root-mean-square error (RMSE) of 0.05 m and R² of 0.97.
- Unmanned aircraft systems (UAS) provided good results with an RMSE of 0.09 m and R² of 0.91.
- Ultrasonic sensors showed lower performance due to static measurement limitations.
Conclusions:
- Light detection and ranging (LiDAR) and unmanned aircraft systems (UAS) are reliable and accurate methods for wheat height evaluation.
- These technologies offer significant advantages over traditional manual measurements in terms of efficiency and objectivity.
- Further research may optimize ultrasonic sensor applications for dynamic phenotyping.
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