Extraction of Individual Tree Parameters by Using Terrestrial Laser Scanner Data in Hyricanian Forest | ||
| ECOPERSIA | ||
| Article 3, Volume 5, Issue 3 - Serial Number 21, 2017, Pages 1837-1847 PDF (909.06 K) | ||
| Authors | ||
| Iman Pazhouhan1; Akbar Najafi* 2; Abolghasem Kamkar Rouhani3; Javad Vahidi4 | ||
| 1Ph.D. Student, Department of Forestry, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran | ||
| 2Associate Professor, Department of Forestry, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran | ||
| 3Associate Professor, Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran | ||
| 4Assistant Professor, Department of Mathematics, Iran University of Science and Technology, Tehran, Iran | ||
| Abstract | ||
| Background: In this study for the first time terrestrial laser scanning survey was implemented on upland Hyrcanian forest, through which a and new method was applied to automatically extract DBH and tree position as a necessary step for height calculation and fitting the clustering as a circle. Materials and Methods: Tree height extracted by fixing a cylinder around the trees center. The accuracies of these methods were investigated by field measurement. Among 4 shapes fitting algorithm, Monte Carlo had more suitable result to fitting circle in each height above the ground. Results: Tree detection rates were 85% for Carpinus betulus and 87% for Diyospyrus lotus with respect to field measurement. R2 and RMSE for DBH measurement were 0.98, 2.06 cm for Carpinus betulus and 0.98, 1.26 cm for Diyospyrus lotus. Value of R2 and RMSE for height measurement were 0.96, 3.37 meters and 0.93, 3.02 meters for Carpinus betulus and Diyospyrus lotus, respectively. Conclusions: The accuracy of DBH by TLS is very suitable, and about the height of trees we extracted underestimated value in comparison to field measurement and that we need to develop more effective algorithms in order to reach more accurate measurement of trees’ height in Hyrcanian forest. | ||
| Keywords | ||
| Breast height; DTM; Forest inventory; LiDAR; Point cloud | ||
| References | ||
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