Leaf Area Index Estimation of Grassland Based on UAV-Borne Hyperspectral Data and Multiple Machine Learning Models in Hulun Lake Basin
Abstract
1. Introduction
2. Materials and Methods
2.1. Overview of the Research Area and Data Collection
2.2. Hyperspectral Data Processing and Quality Control
2.3. Spectral Information Extraction and Data Screening
2.4. Model Construction and Accuracy Evaluation Method
- (1)
- Random Forest
- (2)
- Support Vector Machine
- (3)
- K-Nearest Neighbor
- (4)
- Partial Least Squares Regression
2.5. Quadrat-Level Species Richness
2.6. SHAP Explains Models
3. Results
3.1. Feature Band and Vegetation Index Selection
3.2. Model Performance and Validation Between Current LAI Products
3.3. Uncertainty and Mapping of LAI Estimation Model Predictions
3.4. Analysis of the Eigenvalue Contribution of SHAP
4. Discussion
4.1. The Influence of Spatial Heterogeneity on Model Performance
4.2. Comparison of This Study with Existing LAI Products
4.3. Potential and Limitations of Grassland UAV Hyperspectral LAI Estimation for Optimizing the Accuracy of Regional-Scale Carbon Sink Models
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Quality Control Standards | Threshold |
---|---|
Surface reflectance (ρ) | 0 < ρ < 1 |
Noise–signal ratio | |
Solar zenith angle | |
Light conditions | Clear and cloudless |
Name | Formula | Name | Formula | ||
---|---|---|---|---|---|
Conventional VIs | Normalized difference vegetation index (NDVI) | (R800 − R670)/(R800 + R670) | Hyperspectral-specific VIs | Normalized difference red-edge index (NDRE) | (R790 − R720)/(R790 + R720) |
Soil-adjusted vegetation index (SAVI) | 1.5 × (R800 − R670)/(R800 + R670 + 0.5) | Chlorophyll red-edge index (Clre) | R750/R720 − 1 | ||
Optimized soil-adjusted vegetation index (OSAVI) | 1.16 × (R800 − R670)/(R800 + R670 + 0.16) | Modified red-edge simple ratio index (mSR705) | (R750 − R445)/(R705 − R445) | ||
Green-normalized difference vegetation index (GNDVI) | (R750 − R550)/(R750 + R550) | Modified red-edge-normalized difference vegetation index (mND705) | (R750 − R705)/(R750 + R705 − 2R445) | ||
Chlorophyll green index (Clgreen) | R800/R560−1 | Meris terrestrial chlorophyll index (MTCI) | (R750 − R710)/(R710 − R680) | ||
Plant pigment ratio (PPR) | (R550 − R450)/(R550 + R450) | Anthocyanin reflectance index (ARI) | (1/R559)/(1/R721) | ||
Two-band enhanced vegetation index (EVI2) | 2.5 × (R800 − R670)/(R800 + 2.4 × R670 + 1) | Greenness index (GI) | R554/R667 | ||
Red-edge normalized vegetation index (NDVI705) | (R750 − R705)/(R750 + R705) | Plant biochemical index (PBI) | R810/R560 | ||
Triangular vegetation index (TVI) | 0.5 × [120(R800 − R550) − 200(R670 − R550)] | Spectral polygon vegetation index (SPVI) | 0.4 × [3.7(R800 − R670) − 1.2(R530 − R670)] | ||
Enhanced vegetation index (EVI) | 2.5(R864 − R660)/(R864 + 6R660 − 7.5R487 + 1) | Transformed chlorophyll absorption in reflectance index (TCARI) | 3 × [(R700 − R670)− 0.2(R700 − R550)(R700/R670)] |
Spectrum Variables | Central Wavelength (nm) | Vegetation Indices | ||
---|---|---|---|---|
X1 | 972.5 | 0.58 | NDVI | 0.55 |
X2 | 808 | 0.57 | SAVI | 0.63 |
X3 | 769.2 | 0.56 | PPR | 0.54 |
Y1 | 726.7 | 0.71 | EVI2 | 0.65 |
Y2 | 573.3 | -0.70 | TCARI | 0.62 |
Y3 | 649.1 | -0.66 | TVI | 0.67 |
Z1 | 689.3 | 0.61 | SPVI | 0.65 |
Z2 | 506.8 | 0.60 | EVI | 0.59 |
Z3 | 784.0 | 0.58 |
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Wu, D.; Bao, S.; Tong, Y.; Fan, Y.; Lu, L.; Liu, S.; Li, W.; Xue, M.; Cao, B.; Li, Q.; et al. Leaf Area Index Estimation of Grassland Based on UAV-Borne Hyperspectral Data and Multiple Machine Learning Models in Hulun Lake Basin. Remote Sens. 2025, 17, 2914. https://doi.org/10.3390/rs17162914
Wu D, Bao S, Tong Y, Fan Y, Lu L, Liu S, Li W, Xue M, Cao B, Li Q, et al. Leaf Area Index Estimation of Grassland Based on UAV-Borne Hyperspectral Data and Multiple Machine Learning Models in Hulun Lake Basin. Remote Sensing. 2025; 17(16):2914. https://doi.org/10.3390/rs17162914
Chicago/Turabian StyleWu, Dazhou, Saru Bao, Yi Tong, Yifan Fan, Lu Lu, Songtao Liu, Wenjing Li, Mengyong Xue, Bingshuai Cao, Quan Li, and et al. 2025. "Leaf Area Index Estimation of Grassland Based on UAV-Borne Hyperspectral Data and Multiple Machine Learning Models in Hulun Lake Basin" Remote Sensing 17, no. 16: 2914. https://doi.org/10.3390/rs17162914
APA StyleWu, D., Bao, S., Tong, Y., Fan, Y., Lu, L., Liu, S., Li, W., Xue, M., Cao, B., Li, Q., Cha, M., Zhang, Q., & Shan, N. (2025). Leaf Area Index Estimation of Grassland Based on UAV-Borne Hyperspectral Data and Multiple Machine Learning Models in Hulun Lake Basin. Remote Sensing, 17(16), 2914. https://doi.org/10.3390/rs17162914