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Forest and Grassland Resources Research >

2022 , Vol. 0 >Issue 1: 132 - 141

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2022.01.016

Technical Application

Single Tree Parameters Extraction of Broad-Leaved Forest Based on UAV Tilting Photography

  • Zhoujuan CHEN ,
  • Guang CHENG ,
  • Yuankun BU ,
  • Wei HUANG ,
  • Jiahui CHEN ,
  • Weizhong LI
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  • 1. College of Forestry,Northwest A&F University,Yangling,Shaanxi 712100,China
    2. Shaanxi Academy of Forestry,Xi'an710082,China

Received date: 2021-12-15

  Revised date: 2021-12-31

  Online published: 2022-03-31

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Abstract

Extracting single tree parameters based on UAV tilting photography data is a hot topic in forestry research. Taking ginkgo(Ginkgo biloba L.) broad-leaved forest as the research object,based on UAV tilting photography data,this paper used the local maximum based algorithm to identify the single tree vertex and extract the single tree height under three detection windows(3m×3m、5m×5m、7m×7m),and the accuracies of recognition and extraction were verified respectively. Then,this paper applied the seed region growth algorithm and marker-controlled watershed algorithm for tree canopy extraction,and the extraction accuracies of two algorithms were compared. The results showed that: 1) Under the three single tree detection windows,the F scores of ginkgo tree vertex recognition were 0.87,0.88 and 0.83 respectively. The 5×5m window had the best recognition effect,and in its tree height prediction fitting equation,R2 reached 0.99 and RMSE was 1.91m;2) When the relative error threshold of predicted canopy was 30%,the accuracies of seed region growth algorithm and marker-controlled watershed algorithm in extracting crown area were 73.14% and 63.43% respectively. In establishing the linear regression relationship between predicted and measured canopy,the R 2 of the two algorithms were 0.98 and 0.97,and the RMSE were 1.79m 2 and 2.44m2 respectively. In general,the single tree canopy segmentation accuracy of seed region growth algorithm was higher than that of marker-controlled watershed algorithm. This study points out that the UAV tilting photography technology is feasible in the automatic and accurate single tree identification and segmentation of ginkgo broad-leaved forest,thus it has great application potential in forestry investigation.

Key words： tilting photography; tree height; canopy; local maximum algorithm; region growth algorithm; watershed algorithm

Cite this article

Zhoujuan CHEN , Guang CHENG , Yuankun BU , Wei HUANG , Jiahui CHEN , Weizhong LI . Single Tree Parameters Extraction of Broad-Leaved Forest Based on UAV Tilting Photography[J]. Forest and Grassland Resources Research, 2022 , 0(1) : 132 -141 . DOI: 10.13466/j.cnki.lyzygl.2022.01.016

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