Tree Species Classifications of Urban Forests Using UAV-LiDAR Intensity Frequency Data
Abstract
:1. Introduction
2. Study Area and Method
2.1. Study Area
2.2. Field Data
2.3. LiDAR Data Acquisition and Processing
2.4. ITC Information Acquisition
2.4.1. Extraction of ITC
2.4.2. Intensity Correction of ITCs and Resampling
2.5. Intensity Frequency Feature Calculation and Difference Analysis
2.6. Random Forest and Tree Species Classification
2.7. Tree Species Classification Process
2.8. Accuracy Evaluation
3. Results
3.1. ITC Extraction Results
3.2. Intensity Correction Results
3.3. Results of Intensity Frequency of Different Species
3.4. Intensity Frequency Difference Analysis Results
3.5. Screening Results of Important Random Forest Features
3.6. Tree Species Classification Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Parameters | Information | Parameters | Information |
---|---|---|---|
Sensor | Velodyne Puck LITE ™ | Ranging Accuracy | 3 cm |
Date of Acquisition | 2021.4.17, 2021.5.15 | Mean Point Density | 230 points/m² |
Height | 60 m | Wavelength | 903 nm |
Data Set Name | Sampling Rate | Mean Point Density |
---|---|---|
D1 | 100% | 230 points/m2 |
D2 | 80% | 184 points/m2 |
D3 | 50% | 115 points/m2 |
D4 | 30% | 69 Points/m2 |
Tree Species | Nt | No | Nc | R (%) | P (%) | F (%) |
---|---|---|---|---|---|---|
M.F | 85 | 6 | 10 | 93.4% | 89.5% | 91.4% |
C.C | 167 | 24 | 19 | 87.4% | 89.8% | 88.6% |
C.S | 51 | 5 | 7 | 91.1% | 87.9% | 89.5% |
S.B | 81 | 10 | 8 | 89.0% | 91.0% | 90.0% |
A.B | 62 | 11 | 13 | 84.9% | 82.7% | 83.8% |
G.B | 435 | 54 | 67 | 89.0% | 86.7% | 87.8% |
M.G | 39 | 8 | 11 | 83.0% | 78.0% | 80.4% |
G.L | 56 | 12 | 15 | 82.4% | 78.9% | 80.6% |
Sampling Rate | 100% | 80% | 50% | 30% | |||||
---|---|---|---|---|---|---|---|---|---|
p | H(k) | p | H(k) | p | H(k) | p | H(k) | ||
Intraspecies | M.F | 0.474 | 51 | 0.474 | 51 | 0.474 | 51 | 0.474 | 51 |
C.C | 0.476 | 63 | 0.476 | 63 | 0.476 | 63 | 0.476 | 63 | |
C.S | 0.462 | 25 | 0.462 | 25 | 0.462 | 25 | 0.462 | 25 | |
A.B | 0.478 | 70 | 0.478 | 70 | 0.478 | 70 | 0.478 | 70 | |
S.B | 0.479 | 77 | 0.479 | 77 | 0.479 | 77 | 0.479 | 77 | |
G.L | 0.470 | 40 | 0.470 | 40 | 0.470 | 40 | 0.470 | 40 | |
M.G | 0.463 | 26 | 0.463 | 26 | 0.463 | 26 | 0.463 | 26 | |
G.B | 0.480 | 85 | 0.480 | 85 | 0.480 | 85 | 0.480 | 85 | |
Interspecies | <0.01 | 181.590 | <0.01 | 133.241 | <0.01 | 106.956 | <0.01 | 87.638 |
Tree Species | Important Intensity Frequency Features in D1 |
---|---|
M.F | |
C.C | |
C.S | |
A.B | |
S.B | |
G.L | |
M.G | |
G.B |
Name | M.F n = 16 | C.C n = 19 | C.S n = 8 | A.B n = 21 | S.B n = 23 | Gl. n = 12 | M.G n = 8 | G.B n = 26 | UA (%) | CE (%) |
---|---|---|---|---|---|---|---|---|---|---|
Num. | ||||||||||
M.F | 12 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 85.7 | 14.3 |
C.C | 1 | 19 | 1 | 0 | 2 | 0 | 2 | 0 | 82.6 | 17.4 |
C.S | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 100.0 | 0 |
A.B | 0 | 0 | 0 | 20 | 0 | 0 | 0 | 0 | 100.0 | 0 |
S.B | 3 | 0 | 2 | 0 | 21 | 0 | 0 | 0 | 100.0 | 0 |
Gl. | 0 | 0 | 0 | 0 | 0 | 9 | 0 | 1 | 90.0 | 10.0 |
M.G | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 100 | 0 |
G.B | 1 | 0 | 0 | 0 | 0 | 2 | 1 | 23 | 85.1 | 14.9 |
PA (%) | 85.7 | 95.0 | 87.5 | 95.2 | 91.3 | 75.0 | 75.0 | 88.5 | OA: 86.7% | |
OE (%) | 14.3 | 5.0 | 12.5 | 4.8 | 8.7 | 25.0 | 25.0 | 11.5 | SCI: 117 |
Name | M.F n = 16 | C.C n = 19 | C.S n = 8 | A.B n = 21 | S.B n = 23 | Gl. n = 12 | M.G n = 8 | G.B n = 26 | UA (%) | CE (%) |
---|---|---|---|---|---|---|---|---|---|---|
Num. | ||||||||||
M.F | 10 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 76.9 | 23.1 |
C.C | 1 | 15 | 0 | 0 | 0 | 0 | 0 | 0 | 93.3 | 6.7 |
C.S | 0 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 80.0 | 20.0 |
A.B | 0 | 0 | 0 | 19 | 0 | 0 | 0 | 1 | 95.0 | 5.0 |
S.B | 1 | 0 | 0 | 0 | 17 | 1 | 0 | 0 | 88.0 | 12.0 |
Gl. | 1 | 0 | 0 | 0 | 0 | 7 | 0 | 3 | 63.6 | 56.4 |
M.G | 0 | 1 | 0 | 0 | 0 | 0 | 6 | 0 | 85.7 | 14.3 |
G.B | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 19 | 95.0 | 5.0 |
PA (%) | 62.5 | 78.9 | 50.0 | 90.5 | 95.7 | 58.3 | 75.0 | 84.6 | OA: 87.4% | |
OE (%) | 37.5 | 21.1 | 50.0 | 9.5 | 4.3 | 41.7 | 25.0 | 15.4 | SCI: 97 |
Name | M.F n = 16 | C.C n = 19 | C.S n = 8 | A.B n = 21 | S.B n = 23 | Gl. n = 12 | M.G n = 8 | G.B n = 26 | UA (%) | CE (%) |
---|---|---|---|---|---|---|---|---|---|---|
Num. | ||||||||||
M.F | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 87.5 | 12.5 |
C.C | 3 | 12 | 1 | 0 | 0 | 0 | 0 | 2 | 66.7 | 33.3 |
C.S | 1 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 75.0 | 25.0 |
A.B | 0 | 0 | 0 | 20 | 0 | 0 | 0 | 1 | 100.0 | 0 |
S.B | 1 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 88.0 | 12.0 |
Gl. | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 75.0 | 25.0 |
M.G | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 80.0 | 20.0 |
G.B | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 17 | 85.0 | 15.0 |
PA (%) | 62.5 | 63.2 | 37.5 | 95.2 | 34.7 | 25.0 | 50.0 | 65.4 | OA: 84.1% | |
OE (%) | 37.5 | 36.8 | 62.5 | 4.8 | 65.3 | 75.0 | 50.0 | 34.6 | SCI: 74 |
Name | M.F n = 16 | C.C n = 19 | C.S n = 8 | A.B n = 21 | S.B n = 23 | Gl. n = 12 | M.G n = 8 | G.B n = 26 | UA (%) | CE (%) |
---|---|---|---|---|---|---|---|---|---|---|
Num. | ||||||||||
M.F | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 75.0 | 25 |
C.C | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 2 | 77.8 | 22.1 |
C.S | 0 | 2 | 4 | 0 | 0 | 0 | 0 | 0 | 66.7 | 33.3 |
A.B | 0 | 0 | 0 | 19 | 0 | 0 | 0 | 1 | 100.0 | 0 |
S.B | 0 | 0 | 2 | 0 | 11 | 0 | 0 | 0 | 84.6 | 15.4 |
Gl. | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 50.0 | 50.0 |
M.G | 0 | 1 | 0 | 0 | 0 | 0 | 4 | 0 | 80.0 | 20.0 |
G.B | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 94.1 | 5.9 |
PA (%) | 18.8 | 63.2 | 37.5 | 90.4 | 47.8 | 25.0 | 8.3 | 61.5 | OA: 85.5% | |
OE (%) | 81.2 | 36.8 | 62.5 | 9.6 | 52.2 | 75.0 | 91.7 | 38.5 | SCI: 65 |
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Gong, Y.; Li, X.; Du, H.; Zhou, G.; Mao, F.; Zhou, L.; Zhang, B.; Xuan, J.; Zhu, D. Tree Species Classifications of Urban Forests Using UAV-LiDAR Intensity Frequency Data. Remote Sens. 2023, 15, 110. https://doi.org/10.3390/rs15010110
Gong Y, Li X, Du H, Zhou G, Mao F, Zhou L, Zhang B, Xuan J, Zhu D. Tree Species Classifications of Urban Forests Using UAV-LiDAR Intensity Frequency Data. Remote Sensing. 2023; 15(1):110. https://doi.org/10.3390/rs15010110
Chicago/Turabian StyleGong, Yulin, Xuejian Li, Huaqiang Du, Guomo Zhou, Fangjie Mao, Lv Zhou, Bo Zhang, Jie Xuan, and Dien Zhu. 2023. "Tree Species Classifications of Urban Forests Using UAV-LiDAR Intensity Frequency Data" Remote Sensing 15, no. 1: 110. https://doi.org/10.3390/rs15010110
APA StyleGong, Y., Li, X., Du, H., Zhou, G., Mao, F., Zhou, L., Zhang, B., Xuan, J., & Zhu, D. (2023). Tree Species Classifications of Urban Forests Using UAV-LiDAR Intensity Frequency Data. Remote Sensing, 15(1), 110. https://doi.org/10.3390/rs15010110