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Forest and Grassland Resources Research >

2021 , Vol. 0 >Issue 1: 164 - 172

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2021.01.021

Technical Application

Study on the Extraction of Individual Tree Height Based on UAV Visual Spectrum Remote Sensing

  • Mingxiong BAI ,
  • Chao ZHANG ,
  • Qi CHEN ,
  • Juan WANG ,
  • Huayu LI ,
  • Xiaorong SHI ,
  • Xianyun TIAN ,
  • Yuwei ZHANG
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  • College of Forestry,Southwest Forestry University,Kunming 650224,China

Received date: 2020-11-06

  Revised date: 2020-12-25

  Online published: 2021-03-30

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Abstract

The feasibility of using the watershed segmentation algorithm to extract tree height based on the canopy height model(CHM) generated by high-resolution imagery of UAV was discussed.Tree height data were obtained from Pinus yunnanensis Franch in Fuming County of Yunnan Province.Remote sensing imagery in the study area of the near ground was obtained through the DJI Phantom 4 Pro drone remote sensing system.Pix4D Mapper software was used to preprocess UAV images and reconstruct the research area in three dimensions and 3D point cloud.LiDAR360 software was used to process 3D point cloud and build a DSM(Digital Surface Model),DEM(Digital elevation Model)and CHM were generated.Then,for different canopy density of CHM,the watershed segmentation algorithm was used to divide and extract tree height.The accuracies of the results were elevated.Results showed that CHM could be accurately divided by the watershed segmentation algorithm and it was feasible that UAV imagery was used to extract the height of Pinus yunnanensis Franch.The comparative analysis of the data on the height of trees acquired from the UAV image and the field measurement shows that the R 2,RMSE,rRMSE is 0.893,1.23m,12.42%.At the same time,the measurement of tree height was affected by canopy density with the R2 and root mean squared error(RMSE)value for the least density being R2=0.939,RMSE=1.097m,for the next one was R2=0.921,RMSE=0.896m,and for the largest was R2=0.857,RMSE=1.450m.The accuracy of the measured height of the larger density was higher than that of the smaller density.

Key words： individual tree height; extraction; 3D point cloud; visual spectrum remote sensing; UAV

Cite this article

Mingxiong BAI , Chao ZHANG , Qi CHEN , Juan WANG , Huayu LI , Xiaorong SHI , Xianyun TIAN , Yuwei ZHANG . Study on the Extraction of Individual Tree Height Based on UAV Visual Spectrum Remote Sensing[J]. Forest and Grassland Resources Research, 2021 , 0(1) : 164 -172 . DOI: 10.13466/j.cnki.lyzygl.2021.01.021

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