JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2018, Vol. 42 ›› Issue (01): 127-132.doi: 10.3969/j.issn.1000-2006.201701008

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Three-dimensional green biomass measurement for individual tree using mobile two-dimensional laser scanning

LI Qiujie, ZHENG Jiaqiang, ZHOU Hongping, SHU Yiping, XU Bo   

  1. College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China
  • Online:2018-03-30 Published:2018-03-30

Abstract: 【Objective】The effective measurement of three-dimensional green biomass for individual trees can provide useful information for forest resource survey, evaluating the environment benefit for forest ecosystem, and precision management of forests, which are great significance to the development of modern forestry. This paper proposed a low-cost measurement method for three-dimensional green biomass of individual tree using mobile two-dimensional laser scanning. 【Method】Firstly, the individual tree to be measured was scanned in straight lines from multiple angles by the mobile two-dimensional laser to capture three-dimensional morphology of the crown. Thereafter, the coordinate system and vector parameterization equation of moving trajectory were created to fuse the data from different angles. An automatic trunk recognition method based on line segment detection was proposed to derive two important parameters of vector parameterization equation of moving trajectory. Subsequently, vector parameterization equations of all the scanning lines were figured out. The space to be measured was discretized as a collection of voxels, whose size was consistent with scanning system resolution. The crown volume was regarded as the non-penetrating space of the laser scanning line. Finally, the voxels, which were penetrated by the scanning lines, were removed,and the remainder was the crown volume. 【Result】Six trees were selected and the results of the experiments showed that average time consumed for measuring individual trees was 105.94 s, and the average frame processing time was 0.039 s, with 0.022 m voxel resolution. The computational complexity of the proposed method increased linearly with the number of scan lines. The proposed method automatically processed the data without filtering the point cloud manually. 【Conclusion】The improved voxel model made full use of the measured data, which can truly reflect the internal volume and void of the canopy.

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