UAV Multispectral Data Combined with the PROSAIL Model Using the Adjusted Average Leaf Angle for the Prediction of Canopy Chlorophyll Content in Citrus Fruit Trees
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area and Field Test
2.2. UAV Multispectral Data Acquisition
2.3. Ground-Measured Data
2.4. Simulated Spectrum
2.5. Research Methods
2.5.1. Optimization and Adjustment of ALAs
2.5.2. Hybrid Modeling and Precision Evaluation
3. Results and Analysis
3.1. PROSAIL Parameter Sensitivity Analysis
3.2. Experimental Analysis of the Mixing Ratio Between Measured and Simulated Data
3.3. Comparative Analysis of the ALA Optimization Results
3.4. Performance Evaluation of the ALAadj Hybrid Inversion Model
3.5. Performance Comparison Analysis of the ALAadj Hybrid Inversion Model in the Validation Area
4. Discussion
5. Conclusions
- (1)
- A 1:4 ratio of measured to simulated data was identified as the most pragmatic accommodation for the hybrid inversion model in this study;
- (2)
- The ALAadj value in the study area was 42°, with adjusted PROSAIL parameters showing enhanced spectral response regions favorable for LCC and LAI modeling in the CCC;
- (3)
- Compared with the unadjusted versions, the ALAadj hybrid inversion model demonstrated significant performance improvements across the four machine learning methods, with the peak R2 increasing by 13.8% from 0.723 to 0.823 and the RMSE decreasing by 19.9% from 21.866 μg/cm2 to 17.521 μg/cm2.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Multispectral Bands | Center Wavelength (Bandwidth)/nm | Radiation Correction Coefficient |
---|---|---|
Blue | 450 ± 16 | 0.537 |
Green | 560 ± 16 | 0.538 |
Red | 650 ± 16 | 0.537 |
Red Edge | 730 ± 16 | 0.533 |
NIR | 840 ± 26 | 0.536 |
Parameter | Range | Mean Value | Unit |
---|---|---|---|
SPAD | [38.36, 73.86] | 58.89 | - |
LCC | [32.63, 99.30] | 65.26 | μg/cm2 |
LAI | [1.02, 2.46] | 1.81 | - |
CCC | [51.23, 226.31] | 119.19 | μg/cm2 |
Model | Parameter | Unit | Range | Step |
---|---|---|---|---|
PROSPECT 5- 4SAIL | Chlorophyll content (Cab) | μg/cm2 | 32–100 | 0.1 |
Leaf structure index (N) | - | 1–2 | 0.1 | |
Dry matter content (Cm) | g/cm2 | 0.016 | - | |
Leaf water depth (Cw) | cm | 0.02 | - | |
Carotenoid (Car) | μg/cm2 | 25%Cab | - | |
Brown pigments (Cb) | - | 0 | - | |
Leaf area index (LAI) | m2/m2 | 1–2.5 | 0.1 | |
Soil coefficient (Psoil) | - | 0.1–0.4 | 0.1 | |
Hot spot parameter (Hspot) | m/m | 0.1 | - | |
Average leaf angle (ALA) | (°) | 10–80 | 5 | |
Solar zenith angle (tts) | (°) | 30 | - | |
Observe zenith angle (tto) | (°) | 0 | - | |
Relative azimuth (psi) | (°) | 0 | - |
Model | Hyperparameter Grids |
---|---|
PLSR | n_components: [5, 10, 15, 20] |
GPR | kernel: [RBF, RBF + WhiteKernel] |
alpha: [1 × 10−5, 1 × 10−3] | |
n_restarts_optimizer: [3, 5] | |
RFR | n_estimators: [100, 200] |
max_depth: [10, 20, None] | |
min_samples_split: [2, 5] | |
min_samples_leaf: [1, 2] | |
SVR | kernel: [‘rbf’, ‘linear’] |
C: [0.1, 1, 10] | |
epsilon: [0.1, 0.2] | |
gamma: [‘scale’, 0.01, 0.1] |
Data Source | Total Samples | Training | Testing | Training Proportion | Testing Proportion |
---|---|---|---|---|---|
Simulated Data | 400 | 350 | 50 | 87.5% | 12.5% |
Measured Data | 100 | 50 | 50 | 50% | 50% |
Total | 500 | 400 | 100 | 80% | 20% |
Method | Hybrid Inversion Model | Experimental Area | Validation Area | ||
---|---|---|---|---|---|
R2 | RMSE | R2 | RMSE | ||
PLSR | ALA-unadjusted | 0.625 | 25.465 | 0.675 | 31.920 |
ALAadj | 0.782 | 19.467 | 0.728 | 28.986 | |
GPR | ALA-unadjusted | 0.681 | 22.343 | 0.640 | 37.886 |
ALAadj | 0.744 | 21.676 | 0.717 | 32.024 | |
RFR | ALA-unadjusted | 0.723 | 21.866 | 0.723 | 29.473 |
ALAadj | 0.823 | 17.521 | 0.741 | 28.244 | |
SVR | ALA-unadjusted | 0.717 | 22.131 | 0.740 | 28.515 |
ALAadj | 0.813 | 18.007 | 0.848 | 21.686 |
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Dou, S.; Hou, Y.; Wang, R.; Li, M.; Yuan, S.; Mei, Z.; Song, Y.; Yan, J. UAV Multispectral Data Combined with the PROSAIL Model Using the Adjusted Average Leaf Angle for the Prediction of Canopy Chlorophyll Content in Citrus Fruit Trees. Horticulturae 2025, 11, 1223. https://doi.org/10.3390/horticulturae11101223
Dou S, Hou Y, Wang R, Li M, Yuan S, Mei Z, Song Y, Yan J. UAV Multispectral Data Combined with the PROSAIL Model Using the Adjusted Average Leaf Angle for the Prediction of Canopy Chlorophyll Content in Citrus Fruit Trees. Horticulturae. 2025; 11(10):1223. https://doi.org/10.3390/horticulturae11101223
Chicago/Turabian StyleDou, Shiqing, Yichang Hou, Rongbin Wang, Minglan Li, Shixin Yuan, Zhengmin Mei, Yaqin Song, and Jichi Yan. 2025. "UAV Multispectral Data Combined with the PROSAIL Model Using the Adjusted Average Leaf Angle for the Prediction of Canopy Chlorophyll Content in Citrus Fruit Trees" Horticulturae 11, no. 10: 1223. https://doi.org/10.3390/horticulturae11101223
APA StyleDou, S., Hou, Y., Wang, R., Li, M., Yuan, S., Mei, Z., Song, Y., & Yan, J. (2025). UAV Multispectral Data Combined with the PROSAIL Model Using the Adjusted Average Leaf Angle for the Prediction of Canopy Chlorophyll Content in Citrus Fruit Trees. Horticulturae, 11(10), 1223. https://doi.org/10.3390/horticulturae11101223