Next Article in Journal
Validation of a Methodology for Confidence-Based Participatory Forest Management
Next Article in Special Issue
Sensitivity of Codispersion to Noise and Error in Ecological and Environmental Data
Previous Article in Journal
Transcriptome and Small RNA Sequencing Analysis Revealed Roles of PaWB-Related miRNAs and Genes in Paulownia fortunei
Open AccessArticle

Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level

1,2,3, 1,2,3,*, 4, 1,2,3 and 1,2,3
1
College of Tourism and Geographic Sciences, Yunnan Normal University, Kunming 650500, China
2
Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan, Kunming 650500, China
3
Center for Geospatial Information Engineering and Technology of Yunnan Province, Kunming 650500, China
4
Department of Geography and the Environment, University of North Texas, 1155 Union Circle #305279, Denton, TX 76203, USA
*
Author to whom correspondence should be addressed.
Forests 2018, 9(7), 398; https://doi.org/10.3390/f9070398
Received: 12 June 2018 / Revised: 28 June 2018 / Accepted: 2 July 2018 / Published: 4 July 2018
  |  
PDF [5703 KB, uploaded 4 July 2018]
  |  

Abstract

Abundant and refined structural information under forest canopy can be obtained by using terrestrial laser scanning (TLS) technology. This study explores the methods of using TLS to obtain point cloud data and estimate individual tree height and diameter at breast height (DBH) at plot level in regions with complex terrain. Octree segmentation, connected component labeling and random Hough transform (RHT) are comprehensively used to identify trunks and extract DBH of trees in sample plots, and tree height is extracted based on the growth direction of the trees. The results show that the topography, undergrowth shrubs, and forest density influence the scanning range of the plots and the accuracy of feature extraction. There are differences in the accuracy of the results for different morphological forest species. The extraction accuracy of Yunnan pine forest is the highest (DBH: Root Mean Square Error (RMSE) = 1.17 cm, Tree Height: RMSE = 0.54 m), and that of Quercus semecarpifolia Sm. forest is the lowest (DBH: RMSE = 1.22 cm, Tree Height: RMSE = 1.23 m). At plot scale, with the increase of the mean DBH or tree height in plots, the estimation errors show slight increases, and both DBH and height tend to be underestimated. View Full-Text
Keywords: diameter at breast height (DBH); tree height; random Hough transform; point cloud; terrestrial laser scanning diameter at breast height (DBH); tree height; random Hough transform; point cloud; terrestrial laser scanning
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Liu, G.; Wang, J.; Dong, P.; Chen, Y.; Liu, Z. Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level. Forests 2018, 9, 398.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Forests EISSN 1999-4907 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top