ESTIMATION OF FOREST TREES DIAMETER FROM TERRESTRIAL LASER SCANNING POINT CLOUDS BASED ON A CIRCLE FITTING METHOD

被引:0
|
作者
Wu, Rongren [1 ]
Chen, Yiping [1 ]
Wang, Cheng [1 ]
Li, Jonathan [1 ,2 ,3 ]
机构
[1] Xiamen Univ, Sch Informat Sci & Engn, Fujian Key Lab Sensing & Comp Smart Cities, Xiamen 361005, Fujian, Peoples R China
[2] Univ Waterloo, Dept Geog & Environm Management, Waterloo, ON N2L 3G1, Canada
[3] Univ Waterloo, Dept Syst Engn, Waterloo, ON N2L 3G1, Canada
来源
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年
基金
中国国家自然科学基金;
关键词
Terrestrial laser scanning; 3D point clouds; stem detection; DBH; forestry; STEM;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In forest monitoring and management, any rational decision needs to be based on forest parameters. The diameter at breast height (DBH) of a tree is considered to be the most significant parameter among them. This paper presents a novel method for extracting tree stems and estimating DBH of trees in a forest environment from 3D point clouds data acquired by a terrestrial laser scanning (TLS) system. In the proposed method, a downward-growing algorithm is used to extract individual tree stems and DBH of trees are estimated by the circle fitting algorithm. This proposed method can avoid errors caused from tilted trees by estimating a plane perpendicular to the tree stem. With this method, 17 trees were extracted from single-scan point cloud data consisting of 21 trees. The estimated DBH had a bias of 0.38 cm and a root mean squared error of 1.76 cm. These experiment results show the feasibility of the proposed method.
引用
收藏
页码:2813 / 2816
页数:4
相关论文
共 50 条
  • [1] Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods
    Koren, Milan
    Mokros, Martin
    Bucha, Tomas
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2017, 63 : 122 - 128
  • [2] Adaptive circle-ellipse fitting method for estimating tree diameter based on single terrestrial laser scanning
    Bu, Guochao
    Wang, Pei
    JOURNAL OF APPLIED REMOTE SENSING, 2016, 10
  • [3] Shape classification guided method for automated extraction of urban trees from terrestrial laser scanning point clouds
    Xiaojuan Ning
    Ge Tian
    Yinghui Wang
    Multimedia Tools and Applications, 2021, 80 : 33357 - 33375
  • [4] Shape classification guided method for automated extraction of urban trees from terrestrial laser scanning point clouds
    Ning, Xiaojuan
    Tian, Ge
    Wang, Yinghui
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (24) : 33357 - 33375
  • [5] BENCHMARKING INSTANCE SEGMENTATION IN TERRESTRIAL LASER SCANNING FOREST POINT CLOUDS
    Cherlet, Wout
    Cooper, Zane
    Van den Broeck, Wouter A. J.
    Disney, Mathias
    Origo, Niall
    Calders, Kim
    IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024, 2024, : 4511 - 4515
  • [6] Automatic Forest Mapping at Individual Tree Levels from Terrestrial Laser Scanning Point Clouds with a Hierarchical Minimum Cut Method
    Yang, Bisheng
    Dai, Wenxia
    Dong, Zhen
    Liu, Yang
    REMOTE SENSING, 2016, 8 (05):
  • [7] Tree Diameter at Breast Height Automatic Estimation Based on Forest Terrestrial Laser Scanning
    Wu H.
    Wang X.
    Liu C.
    Tongji Daxue Xuebao/Journal of Tongji University, 2022, 50 (07): : 947 - 954
  • [8] Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning
    Ritter, Tim
    Schwarz, Marcel
    Tockner, Andreas
    Leisch, Friedrich
    Nothdurft, Arne
    FORESTS, 2017, 8 (08)
  • [9] An automated method to register airborne and terrestrial laser scanning point clouds
    Yang, Bisheng
    Zang, Yufu
    Dong, Zhen
    Huang, Ronggang
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 109 : 62 - 76
  • [10] Estimation of vertical plant area density from single return terrestrial laser scanning point clouds acquired in forest environments
    Nguyen, Van-Tho
    Fournier, Richard A.
    Cote, Jean-Francois
    Pimont, Francois
    REMOTE SENSING OF ENVIRONMENT, 2022, 279