Enhanced Estimation of Crown-Level Leaf Dry Biomass of Ginkgo Saplings Based on Multi-Height UAV Imagery and Digital Aerial Photogrammetry Point Cloud Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Overview of the Study Area
2.2. Experimental Design
2.3. Field Data Collection and Processing
2.4. UAV RGB Image Acquisition and Processing
2.5. Remote Sensing Metric Extraction
2.5.1. Color Feature Parameters
2.5.2. Texture Feature Parameters
2.5.3. Extraction of Crown-Level Structural Parameters
2.5.4. Height-Related and Density-Related Metrics Extraction
2.6. Pearson Correlation Analysis
2.7. Regression Analysis and Backward Elimination of Optimal Metrics
2.7.1. GPR Models
2.7.2. PLSR Models
2.8. Estimation Accuracy Evaluation Method
3. Results
3.1. The Leaf Biomass and Height of Ginkgo Saplings under Different Nitrogen Level Treatments
3.2. Tree Top Detection of Ginkgo Saplings
3.3. Correlation Analysis between Leaf Biomass and Remote Sensing Metrics
3.3.1. Correlation Analysis between Leaf Biomass and Image Metrics
3.3.2. Correlation Analysis between DAP Metrics and Leaf Biomass
3.4. Estimation of Leaf Biomass Based on PLSR and GPR Models with Optimal Metrics
3.5. Mapping the Distribution of Crown-Level Leaf Biomass for Ginkgo Saplings
4. Discussion
4.1. Comparison of Measured Structural Parameters of Ginkgo Saplings under Different Nitrogen Treatments
4.2. Comparison of Image Metrics and DAP Metrics for Estimating Leaf Biomass
4.3. Comparison between PLSR and GPR Models and Optimal Metric Selection
4.4. Potentials and Limitations
5. Conclusions
- (1)
- The integration of 60 m height image metrics with 30 m height DAP metrics, derived from the best-performing DAP point cloud datasets for tree top detection, significantly improves leaf biomass estimation.
- (2)
- GPR models generally outperformed PLSR models, regardless of using image metrics only or combined datasets, achieving a maximum R2 of 0.79 in the best-case scenario.
- (3)
- The commonly selected optimal image and DAP metrics for both PLSR and GPR models included G, B, NGI, Tree height, and Crown width.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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UAV | Sensors | Flight Heights | Remote Sensing Metrics | Estimation Method | Monitoring Levels | Plant Species |
---|---|---|---|---|---|---|
Octocopter | Cyber-shot DSC- QX10 | 55 m | Color parameters | MLR | Plot-level AGB | Wheat [12] |
DJI Phantom 3 and 4 | FC350 and FC6310 | 30 m | Color parameters; Height-related metrics | MLM | Plot-level AGB | Wheat [19] |
DJI Phantom 4 PRO | FC6310 | 30 m | Color parameters; Height-related metrics | MLR | Plot-level AGB | Maize [20] |
DJI MAVIC 3M | Hasselblad L2D-20c | 30 m, 60 m and 90 m | Color parameters; Texture features; Height-related metrics | MLM | Plot-level AGB | Wheat [11] |
E-DO (A fixed-wing UAV) | Canon EOS 5D Mark II | 800 m | Color parameters; Height-related metrics; Density-related metrics | MLR | Plot-level AGB | Beech and paper mulberry trees [21] |
E-DO (A fixed-wing UAV) | Canon EOS 5D Mark II | 500 m | Height-related metrics; Density-related metrics | MLR | Plot-level AGB | Dawn redwood and poplar trees [16]; Dawn redwood and poplar trees [17] |
DJI Phantom 4 PRO and 4 Advanced | FC6310 | 40 m | Structural parameters | AE | Individual crown-level AGB | Dawn redwood trees [13]; Holm oak saplings [14] |
DJI Phantom 4 | FC6310 | 20 m | Structural parameters | AE | Individual crown-level wood biomass | American sweetgum [15] |
DJI Phantom 4 PRO | FC6310 | 10 m | Color parameters; Texture features; Structural parameters | MLR | Individual crown-level AGB | Desert shrub [18] |
Metrics Type | Characteristic Parameters | Calculation Formula | Reference |
---|---|---|---|
Single-band metrics | R | Red | [27] |
G | Green | [27] | |
B | Blue | [27] | |
Ratio metrics | G/R | G/R | [28] |
G/B | G/B | [28] | |
R/B | R/B | [28] | |
Normalized metrics | NRI | R/(R + G + B) | [27,29] |
NGI | G/(R + G + B) | [27,29] | |
NBI | B/(R + G + B) | [27,29] | |
VIG,R | (G − R)/(G + R) | [29,30] | |
VIG,B | (G − B)/(G + B) | [29,31] | |
VIB,R | (B − R)/(B + R) | [29,30] | |
VARI | (NGI − NRI)/(NGI + NRI-NBI) | [32] | |
GLI | (2 × NGI − NBI − NRI)/(2 × NGI + NBI + NRI) | [32] | |
Difference metrics | GMR | G − R | [28,29] |
GMB | G − B | [28,29] | |
BMR | B − R | [28,29] | |
ExG | 2 × NGI − NRI − NBI | [32] | |
ExR | 1.4 × NRI − NGI | [32] | |
ExGR | ExG − ExR | [32] | |
HSI color model metrics | H | arccos [0.5 × [(R − G) + (R − B)]/[(R − G)2 +(R − B)(G − B)]0.5] | [33] |
S | 1 − (3 × [min(R, G, B)])/(R + G + B) | [33] | |
I | (R + G + B)/3 | [33] | |
Lab color model metrics | L* | 116 × (0.299R + 0.587G + 0.114B)1/3 -16 | [31,34] |
a* | 500 × [1.006 × (0.607R + 0.174G + 0.201B)1/3 − (0.299R + 0.587G + 0.114B)1/3] | [31,34] | |
b* | 200 × [(0.299R + 0.587G + 0.114B)1/3 − 0.846 × (0.066G + 1.117B)]1/3 | [31,34] |
Parameters | Value Settings |
---|---|
Grid size (m) | 0.0826 |
Buffer size (pixels) | 50 |
Height above ground point (m) | 0.4 |
Smallest tree height (m) | 0.78 |
Parameters | Meaning |
---|---|
Tree height | The height for individual segmented saplings derived from DAP point clouds |
Crown width | The crown width for individual segmented saplings derived from DAP point clouds |
Crown area | The crown area for individual segmented saplings derived from DAP point clouds |
Crown volume | The crown volume for individual segmented saplings derived from DAP point clouds |
Metrics Name | Meaning |
---|---|
Height-related metrics | |
H25 | The 25th, 50th, 75th, and 95th percentiles of the canopy height distributions for the first returns within the statistical cell of individual sapling crowns |
H50 | |
H75 | |
H95 | |
Hcv | The coefficient of variation (CV) represents the variability of Z-values across all points within a specific statistical cell of individual sapling crowns |
Hmean | The average height is calculated by taking the mean of all the heights of all first returns within a specific statistical cell of individual sapling crowns |
Density-related metrics | |
D3 | The proportion of points exceeding the 30th, 40th, 50th, 70th, and 90th quantiles to the total number of points within a specific statistical cell of individual sapling crowns |
D4 | |
D5 | |
D7 | |
D9 |
Height | N0 (Number = 105) | N2 (Number = 105) | N4 (Number = 106) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
CD | OE | CE | DT | CD | OE | CE | DT | CD | OE | CE | DT | |
30 m | 105 (100.00%) | 0 (0.00%) | 2 (1.90%) | 0 (0.00%) | 104 (99.05%) | 1 (0.95%) | 3 (2.86%) | 1 (0.95%) | 106 (100.00%) | 0 (0.00%) | 1 (0.94%) | 1 (0.94%) |
60 m | 98 (93.33%) | 7 (6.67%) | 4 (3.81%) | 0 (0.00%) | 99 (94.29%) | 6 (5.71%) | 3 (2.86%) | 1 (0.95%) | 98 (92.45%) | 8 (7.55%) | 2 (1.89%) | 2 (1.89%) |
90 m | 81 (77.14%) | 24( 22.86%) | 5 (4.76%) | 2 (1.90%) | 92 (87.62%) | 13 (12.38%) | 3 (2.86%) | 1 (0.95%) | 86 (81.13%) | 20 (18.87%) | 5 (4.72%) | 2 (1.89%) |
Image Metrics | AL_30m | AL_60m | AL_90m | BL_30m | BL_60m | BL_90m | DL_30m | DL_60m | DL_90m |
---|---|---|---|---|---|---|---|---|---|
Color parameters | |||||||||
R | −0.58 ** | −0.62 ** | −0.59 ** | −0.47 ** | −0.46 ** | −0.40 * | −0.60 ** | −0.61 ** | −0.56 ** |
G | −0.54 ** | −0.54 ** | −0.53 ** | −0.51 ** | −0.40 * | −0.35 * | −0.61 ** | −0.46 ** | −0.46 ** |
B | −0.23 | −0.41 * | −0.47 ** | −0.20 | −0.18 | −0.15 | −0.38 * | −0.34 * | −0.37 * |
NRI | −0.62 ** | −0.69 ** | −0.60 ** | −0.39 * | −0.53 ** | −0.56 ** | −0.56 ** | −0.69 ** | −0.65 ** |
NGI | 0.41 * | 0.64 ** | 0.55 ** | −0.15 | 0.01 | 0.01 | 0.27 * | 0.45 ** | 0.43* |
NBI | 0.57 ** | 0.53 ** | 0.24 | 0.54 ** | 0.56 ** | 0.49 ** | 0.53 ** | 0.53 ** | 0.38 * |
G/R | 0.61 ** | 0.73 ** | 0.62 ** | 0.23 | 0.37 * | 0.37 * | 0.48 ** | 0.65 ** | 0.59 ** |
G/B | −0.49 ** | −0.34 * | 0.06 | −0.54 ** | −0.45 ** | −0.36 * | −0.40 * | −0.27 | −0.07 |
R/B | −0.60 ** | −0.62 ** | −0.46 ** | −0.51 ** | −0.58 ** | −0.57 ** | −0.59 ** | −0.65 ** | −0.58 ** |
VIG,R | 0.61 ** | 0.73 ** | 0.62 ** | 0.23 | 0.37 * | 0.37 * | 0.49 ** | 0.65 ** | 0.60 ** |
VIG,B | −0.49 ** | −0.34 * | 0.08 | −0.54 ** | −0.45 ** | −0.36 * | −0.40 * | −0.26 | −0.07 |
VIB,R | 0.60 ** | 0.62 ** | 0.45 ** | 0.50 ** | 0.58 ** | 0.57 ** | 0.57 ** | 0.64 ** | 0.57 ** |
GMR | 0.59 ** | 0.71 ** | 0.63 ** | 0.22 | 0.37 * | 0.36 * | 0.43 * | 0.60 ** | 0.58 ** |
GMB | −0.59 ** | −0.54 ** | −0.43 * | −0.62 ** | −0.50 ** | −0.47 ** | −0.68 ** | −0.48 ** | −0.47 ** |
BMR | 0.61 ** | 0.64 ** | 0.60 ** | 0.52 ** | 0.57 ** | 0.56 ** | 0.63 ** | 0.68 ** | 0.66 ** |
H | 0.62 ** | 0.72 ** | 0.61 ** | 0.23 | 0.36 * | 0.35 * | 0.51 ** | 0.65 ** | 0.60 ** |
S | −0.60 ** | −0.62 ** | −0.44 ** | −0.50 ** | −0.58 ** | −0.57 ** | −0.57 ** | −0.64 ** | −0.56 ** |
I | −0.54 ** | −0.57 ** | −0.56 ** | −0.45 ** | −0.39 * | −0.33 * | −0.58 ** | −0.52 ** | −0.49 ** |
L* | −0.55 ** | −0.57 ** | −0.56 ** | −0.49 ** | −0.41 * | −0.35 * | −0.60 ** | −0.52 ** | −0.50 ** |
a* | −0.58 ** | −0.73 ** | −0.62 ** | −0.08 | −0.24 | −0.22 | −0.39 * | −0.56 ** | −0.53 ** |
b* | −0.60 ** | −0.59 ** | −0.47 ** | −0.59 ** | −0.56 ** | −0.53 ** | −0.66 ** | −0.59 ** | −0.57 ** |
ExG | 0.41 * | 0.64 ** | 0.55 ** | −0.15 | 0.01 | 0.01 | 0.27 * | 0.45 ** | 0.43 * |
ExR | −0.61 ** | −0.72 ** | −0.63 ** | −0.27 * | −0.41 * | −0.42 * | −0.50 ** | −0.66 ** | −0.61 ** |
ExGR | 0.57 ** | 0.72 ** | 0.60 ** | 0.07 | 0.22 | 0.20 | 0.40 * | 0.58 ** | 0.53 ** |
VARI | 0.61 ** | 0.73 ** | 0.62 ** | 0.23 | 0.37 * | 0.37 * | 0.48 ** | 0.65 ** | 0.59 ** |
GLI | 0.41 * | 0.64 ** | 0.55 ** | −0.15 | 0.01 | 0.01 | 0.27 * | 0.45 ** | 0.43 * |
Texture parameters | |||||||||
Mean | 0.55 ** | −0.58 ** | 0.57 ** | 0.47 ** | −0.41 * | 0.35 * | 0.59 ** | −0.53 ** | 0.51 ** |
Variance | −0.01 | −0.17 | −0.02 | 0.05 | 0.24 | 0.27 * | −0.03 | −0.09 | 0.15 |
Homogeneity | 0.04 | 0.21 | 0.01 | −0.01 | −0.13 | −0.19 | 0.12 | 0.25 | 0.01 |
Contrast | 0.02 | −0.16 | −0.08 | 0.13 | 0.25 | 0.12 | −0.03 | −0.18 | −0.02 |
Dissimilarity | 0.00 | −0.18 | −0.07 | 0.10 | 0.20 | 0.14 | −0.06 | −0.23 | −0.03 |
Entropy | 0.04 | −0.09 | 0.14 | 0.00 | 0.11 | 0.18 | −0.18 | −0.22 | 0.10 |
Second Moment | −0.06 | 0.09 | −0.15 | 0.00 | −0.09 | −0.20 | 0.20 | 0.19 | −0.15 |
Correlation | −0.29 * | −0.08 | 0.13 | −0.34 * | −0.10 | 0.29 * | −0.31 * | −0.22 | 0.14 |
DAP Metrics | Correlation Coefficients (r) |
---|---|
Structural parameters | |
Tree height | 0.74 ** |
Crown width | 0.72 ** |
Crown area | 0.69 ** |
Crown volume | 0.68 ** |
Height-related metrics | |
H25 | 0.40 * |
H50 | 0.45 ** |
H75 | 0.50 ** |
H95 | 0.61 ** |
Hcv | 0.42 * |
Hmean | 0.53 ** |
Density-related metrics | |
D3 | 0.26 |
D4 | 0.31 * |
D5 | 0.18 |
D7 | 0.08 |
D9 | −0.37 * |
Metrics | PLSR Models | GPR Models | ||||||
---|---|---|---|---|---|---|---|---|
CV-R2 | RMSE (g/Plant) | rRMSE (%) | SelectedMetrics | CV-R2 | RMSE (g/Plant) | rRMSE (%) | Selected Metrics | |
Image_AL_30m | 0.33 | 17.01 | 45.12 | B, NBI | 0.33 | 17.00 | 45.09 | BMR |
Image_AL_60m | 0.51 | 14.49 | 38.44 | BMR, VIB,R, G, B, NGI, GMR, Homogeneity | 0.57 | 13.57 | 35.99 | B, GMR, Homogeneity |
Image_AL_90m | 0.38 | 16.34 | 43.36 | b*, R/B, B, G/R | 0.40 | 16.05 | 42.58 | BMR, b*, NBI, G/R |
DAP_30m | 0.62 | 12.85 | 34.10 | Tree height, Crown width, H25, H95, Hcv, Hmean, D9 | 0.60 | 13.05 | 34.63 | Tree height, Crown width, D4 |
Image_AL_30m+DAP_30m | 0.62 | 12.77 | 33.87 | NBI, Tree height, Crown width, Crown volume, D9 | 0.64 | 12.44 | 32.99 | G, B, Crown width, H50 |
Image_AL_60m+DAP_30m | 0.71 | 11.18 | 29.67 | NGI, Homogeneity, Tree height, Crown width, D9 | 0.79 | 9.63 | 25.56 | G, NGI, Homogeneity, Crown width, H25, Hmean |
Image_AL_90m+DAP_30m | 0.65 | 12.32 | 32.68 | G, B, Tree height, Crown width, Crown volume, D3, D9 | 0.67 | 11.95 | 31.69 | G, Tree height, Crown width, H50 |
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Qiu, S.; Zhu, X.; Zhang, Q.; Tao, X.; Zhou, K. Enhanced Estimation of Crown-Level Leaf Dry Biomass of Ginkgo Saplings Based on Multi-Height UAV Imagery and Digital Aerial Photogrammetry Point Cloud Data. Forests 2024, 15, 1720. https://doi.org/10.3390/f15101720
Qiu S, Zhu X, Zhang Q, Tao X, Zhou K. Enhanced Estimation of Crown-Level Leaf Dry Biomass of Ginkgo Saplings Based on Multi-Height UAV Imagery and Digital Aerial Photogrammetry Point Cloud Data. Forests. 2024; 15(10):1720. https://doi.org/10.3390/f15101720
Chicago/Turabian StyleQiu, Saiting, Xingzhou Zhu, Qilin Zhang, Xinyu Tao, and Kai Zhou. 2024. "Enhanced Estimation of Crown-Level Leaf Dry Biomass of Ginkgo Saplings Based on Multi-Height UAV Imagery and Digital Aerial Photogrammetry Point Cloud Data" Forests 15, no. 10: 1720. https://doi.org/10.3390/f15101720
APA StyleQiu, S., Zhu, X., Zhang, Q., Tao, X., & Zhou, K. (2024). Enhanced Estimation of Crown-Level Leaf Dry Biomass of Ginkgo Saplings Based on Multi-Height UAV Imagery and Digital Aerial Photogrammetry Point Cloud Data. Forests, 15(10), 1720. https://doi.org/10.3390/f15101720