Active 3D Imaging of Vegetation Based on Multi-Wavelength Fluorescence LiDAR
Abstract
:1. Introduction
2. Materials and Methods
2.1. System Description
2.1.1. Selection of Fluorescence Wavelengths
2.1.2. System Components
2.1.3. Data Description
2.2. Sample Materials
2.3. Methods
2.3.1. D Fluorescence Imaging Based on Spectral Enhancement
2.3.2. System Evaluation Based on Point Cloud Classification
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Multi-Wavelength Fluorescence LiDAR | |
---|---|
Laser wavelength | 355 nm |
Repetition rate | 7 kHz |
Pulse width | 3~5 ns |
Pulse energy | 18 μJ |
Beam divergence | <1 mrad |
Telescope aperture | 200 mm |
Spatial resolution | Distance: 10 mm |
Scanning: 2 mm @20m |
Ground Truth | Predicted Class | Producer Accuracy | ||||
---|---|---|---|---|---|---|
Flowerpot | Withered Leaves | Yellow Leaves | Fresh Green Leaves | |||
(a) 460 nm | Flowerpot | 108 | 0 | 0 | 140 | 0.44 |
Withered leaves | 16 | 0 | 0 | 100 | 0 | |
Yellow leaves | 4 | 0 | 0 | 129 | 0 | |
Fresh green leaves | 132 | 0 | 0 | 1147 | 0.90 | |
User accuracy | 0.42 | 0 | 0 | 0.76 | ||
Overall accuracy (%): 70.7% | ||||||
Kappa coefficient: 0.17 | ||||||
(b) 685 nm | Flowerpot | 235 | 0 | 0 | 13 | 0.95 |
Withered leaves | 30 | 5 | 0 | 81 | 0.04 | |
Yellow leaves | 1 | 1 | 0 | 131 | 0 | |
Fresh green leaves | 159 | 6 | 0 | 1114 | 0.87 | |
User accuracy | 0.55 | 0.42 | 0 | 0.83 | ||
Overall accuracy (%): 76.2% | ||||||
Kappa coefficient: 0.43 | ||||||
(c) 460 nm + 685 nm | Flowerpot | 236 | 2 | 3 | 7 | 0.95 |
Withered leaves | 51 | 13 | 6 | 46 | 0.11 | |
Yellow leaves | 5 | 12 | 18 | 98 | 0.14 | |
Fresh green leaves | 55 | 22 | 25 | 1177 | 0.92 | |
User accuracy | 0.68 | 0.27 | 0.35 | 0.89 | ||
Overall accuracy (%): 81.3% | ||||||
Kappa coefficient: 0.56 | ||||||
(d) Four wavelengths | Flowerpot | 240 | 0 | 4 | 4 | 0.97 |
Withered leaves | 7 | 57 | 19 | 33 | 0.49 | |
Yellow leaves | 0 | 13 | 69 | 51 | 0.52 | |
Fresh green leaves | 24 | 20 | 23 | 1212 | 0.95 | |
User accuracy | 0.89 | 0.63 | 0.60 | 0.93 | ||
Overall accuracy (%): 88.9% | ||||||
Kappa coefficient: 0.75 |
Ground Truth | Predicted Class | Producer Accuracy | ||||
---|---|---|---|---|---|---|
Flowerpot | Withered Leaves | Yellow Leaves | Fresh Green Leaves | |||
(a) Normal vectors | Flowerpot | 107 | 0 | 0 | 141 | 0.43 |
Withered leaves | 8 | 7 | 6 | 95 | 0.06 | |
Yellow leaves | 3 | 0 | 9 | 121 | 0.07 | |
Fresh green leaves | 48 | 0 | 0 | 1231 | 0.96 | |
User accuracy | 0.64 | 1.0 | 0.60 | 0.78 | ||
Overall accuracy (%): 76.2% | ||||||
Kappa coefficient: 0.29 | ||||||
(b) Normal vectors + four wavelengths | Flowerpot | 244 | 0 | 0 | 4 | 0.98 |
Withered leaves | 4 | 73 | 13 | 26 | 0.63 | |
Yellow leaves | 3 | 14 | 91 | 25 | 0.68 | |
Fresh green leaves | 6 | 14 | 24 | 1235 | 0.97 | |
User accuracy | 0.95 | 0.72 | 0.71 | 0.96 | ||
Overall accuracy (%): 92.5% | ||||||
Kappa coefficient: 0.84 |
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Zhao, X.; Shi, S.; Yang, J.; Gong, W.; Sun, J.; Chen, B.; Guo, K.; Chen, B. Active 3D Imaging of Vegetation Based on Multi-Wavelength Fluorescence LiDAR. Sensors 2020, 20, 935. https://doi.org/10.3390/s20030935
Zhao X, Shi S, Yang J, Gong W, Sun J, Chen B, Guo K, Chen B. Active 3D Imaging of Vegetation Based on Multi-Wavelength Fluorescence LiDAR. Sensors. 2020; 20(3):935. https://doi.org/10.3390/s20030935
Chicago/Turabian StyleZhao, Xingmin, Shuo Shi, Jian Yang, Wei Gong, Jia Sun, Biwu Chen, Kuanghui Guo, and Bowen Chen. 2020. "Active 3D Imaging of Vegetation Based on Multi-Wavelength Fluorescence LiDAR" Sensors 20, no. 3: 935. https://doi.org/10.3390/s20030935
APA StyleZhao, X., Shi, S., Yang, J., Gong, W., Sun, J., Chen, B., Guo, K., & Chen, B. (2020). Active 3D Imaging of Vegetation Based on Multi-Wavelength Fluorescence LiDAR. Sensors, 20(3), 935. https://doi.org/10.3390/s20030935