Knowledge Network Node
Chinese Journal of Applied Ecology. 2021, (07) Core

Extraction of branch factors and model construction for Larix plantation using terrestrial laser scanning （TLS）Chinese Full TextEnglish Full Text (MT)

ZHANG Ying;JIA Wei-wei;School of Forestry, Northeast Forestry University/Key Laboratory of Sustainable Forest Ecosystem Management of Ministry of Education;

Abstract: Forest parameters could be estimated without damage using terrestrial laser scanning（TLS）. In this study, 1266 sets of branch parameters, including branch height, branch chord length, branch length, branch angle, branch diameter and the branch arc height, of 26 Larix trees were extracted based on TLS using point cloud processing software in the way of human-computer interaction. The average of extracted maximum relative height of the branches was 0.83. The accuracy of the extracted branch attributes followed the order of branch height ＞ branch chord length ＞ branch length ＞ branchdiameter（with the branch diameter ＞20 mm） ＞ branch arc height. After dividing the crown into four parts, it proved that the density of the branches increased while the extraction ratio and precision of branches decreased with the increase of crown height. Due to the low accuracy of branch diameter extraction, we developed a base diameter prediction model using the branch chord length, the height of branch, diameter at breast height and tree height as independent variables. The measured, extracted and model predicted values of different base diameter were compared, and discovered that accuracy of model prediction was greater than that of extraction by TLS. For timber production, the most worthy wood was the middle and lower section of the tree. The method could accurately extract tree height, diameter at breast height（DBH） and the branch attributes with the relative branch height of less than 0.8, providing the parameters that are necessary to develop a wood quality model.
Keywords：

terrestrial laser scanning; branch factor; extraction of 3D point cloud data; wood quality;

  • DOI：

    10.13287/j.1001-9332.202107.034

  • Series：

    (A) Mathematics/ Physics/ Mechanics/ Astronomy; (D) Agriculture

  • Subject：

    Forestry

  • Classification Code：

    S758

Download the mobile appuse the app to scan this coderead the article.

Tips: Please download CAJViewer to view CAJ format full text.

Download: 492 Page: 2505-2513 Pagecount: 9 Size: 1295K

Related Literature
  • Similar Article
  • Reader Recommendation
  • Associated Author