Rapid detection of stand density, tree positions, and tree diameter with a 2D terrestrial laser scanner

被引:0
|
作者
Andreas Brunner
Belachew Gizachew
机构
[1] Norwegian University of Life Sciences,Department of Ecology and Natural Resource Management
来源
关键词
Tree detection; Algorithm; Thinning operation; Occlusion; Variable scanning range;
D O I
暂无
中图分类号
学科分类号
摘要
Harvester operators that decide about tree removal during thinnings have currently no instruments to measure stand density continuously before and after the operation. We tested whether basal area can be measured rapidly for this purpose with a 2D terrestrial laser scanner. An algorithm was developed, which automatically detects trees from laser scanner point clouds, measures their position and diameter, and calculates basal area. A field test included 18 laser scans in two Norway spruce stands with a wide range of stand densities, representing situations before and after thinning. Occlusion is a problem of single laser scans, and about one-third of the trees within the scanning range were not detected. Occlusion varies with stem density and branchiness. We therefore applied a flexible scanning range, which is detected automatically based on the laser hit density distribution for each scan. Scanning ranges were between 5.5 and 8.4 m (mean = 7.3 m) in the test scans, which is below the reach of the harvester crane, but still large enough to estimate local stand density. Basal area measured with the laser scanner was unbiased only in one of the two stands. Trees not detected or trees falsely detected caused only small bias of the basal area measurement in one of the two stands. Measurement errors for individual scans were, however, often around 10 m2 ha−1.
引用
收藏
页码:819 / 831
页数:12
相关论文
共 50 条
  • [31] A model for predicting mean diameter at breast height from mean tree height and stand density
    Umemi, Kohtaro
    Inoue, Akio
    JOURNAL OF FOREST RESEARCH, 2024, 29 (03) : 186 - 195
  • [32] TREE-BASED 2D INDEXING
    Zdarek, Jan
    Melichar, Borivoj
    INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE, 2011, 22 (08) : 1893 - 1907
  • [33] Comparing terrestrial laser scanners' ability to measure tree height and diameter in a managed forest environment
    Brack, C.
    Schaefer, M.
    Jovanovic, T.
    Crawford, D.
    AUSTRALIAN FORESTRY, 2020, 83 (03) : 161 - 171
  • [34] 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
  • [35] The influence of scan mode and circle fitting on tree stem detection, stem diameter and volume extraction from terrestrial laser scans
    Pueschel, Pyare
    Newnham, Glenn
    Rock, Gilles
    Udelhoven, Thomas
    Werner, Willy
    Hill, Joachim
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2013, 77 : 44 - 56
  • [36] The influence of scanner parameters on the extraction of tree metrics from FARO Photon 120 terrestrial laser scans
    Pueschel, Pyare
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2013, 78 : 58 - 68
  • [37] Estimation of historical soil erosion rates in dehesas using exposed tree roots and terrestrial laser scanner
    Rubio-Delgado, J.
    Schnabel, S.
    Gomez-Gutierrez, A.
    Berenguer, F.
    CUATERNARIO Y GEOMORFOLOGIA, 2014, 28 (3-4): : 69 - 84
  • [38] Effects of diameter distribution errors on stand management decisions according to a simulated individual tree detection
    Jari Vauhkonen
    Annals of Forest Science, 2020, 77
  • [39] Effects of diameter distribution errors on stand management decisions according to a simulated individual tree detection
    Vauhkonen, Jari
    ANNALS OF FOREST SCIENCE, 2020, 77 (02)
  • [40] Change Detection of Tree Biomass with Terrestrial Laser Scanning and Quantitative Structure Modelling
    Kaasalainen, Sanna
    Krooks, Anssi
    Liski, Jari
    Raumonen, Pasi
    Kaartinen, Harri
    Kaasalainen, Mikko
    Puttonen, Eetu
    Anttila, Kati
    Makipaa, Raisa
    REMOTE SENSING, 2014, 6 (05) : 3906 - 3922