Urban Treetop Detection and Tree-Height Estimation from Unmanned-Aerial-Vehicle Images
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Aerial Image Collection and Pre-Processing
2.3. Field Investigation
2.4. Improvement to Local-Maximum Algorithm
2.4.1. CHM Optimization Using Dual Gaussian Filtering
2.4.2. Selection of Suitable Window Size for Improved LM Algorithm
2.4.3. Fine Extraction
2.5. Accuracy Assessment
3. Results
3.1. Treetop Detection and Accuracy Assessment
3.2. Tree-Height Estimation and Accuracy Evaluation
4. Discussion
4.1. The Influences of Parameter Settings in the LMC Algorithm
4.2. Error Analysis
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Group | Number | Indicator | Minimum (m) | Maximum (m) | Mean (m) | S.D. | Group |
---|---|---|---|---|---|---|---|
≤12 m | 329 | Tree height | 3.00 | 12.00 | 7.95 | 2.35 | 3.00 |
Canopy radius | 0.25 | 5.50 | 1.96 | 0.84 | 0.25 | ||
>12 m | 225 | Tree height | 12.00 | 38.00 | 20.12 | 5.42 | 12.00 |
Canopy radius | 0.88 | 5.75 | 2.57 | 0.95 | 0.88 |
Group | Fitting Equation | R² | AIC |
---|---|---|---|
≤12 m | y= −2.86598 × 10−4x5 + 8.27 × 10−3x4 − 0.08274 × x3 + 0.32921 × x2 − 0.29568 × x + 0.05897 | 0.8896 | − |
72.15 | |||
>12 m | y= 1.86478 × 10−6x5 − 2.17364 × 10−4x4 + 9.4 × −3 × x3 − 0.18446 × x2 + 1.62422 × x − 3.87244 | 0.5207 | − |
53.35 |
Sample Plot | Canopy Closure | Actual Tree Number | NDT | CE (%) | OE (%) | UA (%) | PA (%) | DET (%) | OA (%) |
---|---|---|---|---|---|---|---|---|---|
A | 0.5 | 84 | 93 | 13.98 | 23.66 | 86.02 | 76.34 | 84.52 | 90.32 |
B | 0.5 | 28 | 28 | 17.86 | 17.86 | 82.14 | 82.14 | 82.14 | 100 |
C | 0.5 | 34 | 37 | 13.51 | 13.51 | 86.49 | 86.49 | 85.29 | 91.89 |
D | 0.5 | 153 | 168 | 5.36 | 13.69 | 94.64 | 86.31 | 94.12 | 91.07 |
Mean (±SD) | 12.68 (±2.55) | 17.18 (±7.12) | 87.32 (±7.55) | 82.82 (±2.12) | 86.52 (±6.54) | 93.32 (±3.90) | |||
E | 1 | 49 | 42 | 26.19 | 9.52 | 73.81 | 90.48 | 77.55 | 83.33 |
F | 1 | 89 | 121 | 4.96 | 31.4 | 95.04 | 68.6 | 93.26 | 73.55 |
G | 1 | 65 | 43 | 74.42 | 23.26 | 25.58 | 76.74 | 50.77 | 48.84 |
H | 1 | 85 | 122 | 0.82 | 31.15 | 99.18 | 68.85 | 98.82 | 69.67 |
I | 1 | 111 | 171 | 0.58 | 35.67 | 99.42 | 64.33 | 99.1 | 64.91 |
Mean (±SD) | 21.39 (±31.47) | 26.2 (±10.34) | 78.61 (±31.47) | 73.8 (±10.34) | 83.9 (±20.49) | 68.06 (±12.70) | |||
OM | 17.52 | 22.19 | 82.48 | 77.81 | 85.06 | 79.29 |
Statistical Measure | NDT | Nv | UA | PA | DET | OA |
---|---|---|---|---|---|---|
F | 0.032 | 0.208 | 0.292 | 2.552 | 0.061 | 14.055 |
p-value | 0.863 | 0.662 | 0.605 | 0.154 | 0.813 | 0.007 |
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Wu, H.; Zhuang, M.; Chen, Y.; Meng, C.; Wu, C.; Ouyang, L.; Liu, Y.; Shu, Y.; Tao, Y.; Qiu, T.; et al. Urban Treetop Detection and Tree-Height Estimation from Unmanned-Aerial-Vehicle Images. Remote Sens. 2023, 15, 3779. https://doi.org/10.3390/rs15153779
Wu H, Zhuang M, Chen Y, Meng C, Wu C, Ouyang L, Liu Y, Shu Y, Tao Y, Qiu T, et al. Urban Treetop Detection and Tree-Height Estimation from Unmanned-Aerial-Vehicle Images. Remote Sensing. 2023; 15(15):3779. https://doi.org/10.3390/rs15153779
Chicago/Turabian StyleWu, Hui, Minghao Zhuang, Yuanchi Chen, Chen Meng, Caiyan Wu, Linke Ouyang, Yuhan Liu, Yi Shu, Yuzhong Tao, Tong Qiu, and et al. 2023. "Urban Treetop Detection and Tree-Height Estimation from Unmanned-Aerial-Vehicle Images" Remote Sensing 15, no. 15: 3779. https://doi.org/10.3390/rs15153779