Towards Tree Green Crown Volume: A Methodological Approach Using Terrestrial Laser Scanning

被引:15
|
作者
Zhu, Zihui [1 ]
Kleinn, Christoph [1 ]
Noelke, Nils [1 ]
机构
[1] Univ Gottingen, Fac Forest Sci & Forest Ecol, Forest Inventory & Remote Sensing, Busgenweg 5, D-37077 Gottingen, Germany
关键词
urban trees; green crown volume; point cloud; k-means; CLASSIFICATION; SCALE; LEAF; WOOD;
D O I
10.3390/rs12111841
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Crown volume is a tree attribute relevant in a number of contexts, including photosynthesis and matter production, storm resistance, shadowing of lower layers, habitat for various taxa. While commonly the total crown volume is being determined, for example by wrapping a convex hull around the crown, we present here a methodological approach towards assessing the tree green crown volume (TGCVol), the crown volume with a high density of foliage, which we derive by terrestrial laser scanning in a case study of solitary urban trees. Using the RGB information, we removed the hits on stem and branches within the tree crown and used the remaining leaf hits to determine TGCVol from k-means clustering and convex hulls for the resulting green 3D clusters. We derived a tree green crown volume index (TGCVI) relating the green crown volume to the total crown volume. This TGCVI is a measure of how much a crown is "filled with green" and scale-dependent (a function of specifications of the k-means clustering). Our study is a step towards a standardized assessment of tree green crown volume. We do also address a number of remaining methodological challenges.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Automated Determination of the Volume of Loose Engineering Deposits Using Terrestrial Laser Scanning
    Lu, Bo
    Zhu, Jichen
    Ge, Yunfeng
    Chen, Qian
    Wen, Zhongxu
    Liu, Geng
    Li, Liangquan
    REMOTE SENSING, 2023, 15 (18)
  • [32] Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve
    Næsset, E
    Okland, T
    REMOTE SENSING OF ENVIRONMENT, 2002, 79 (01) : 105 - 115
  • [33] TERRESTRIAL LASER SCANNING IN VOLUME AND BIOMASS MODELLING - OVERVIEW
    Kankare, Ville
    Saarinen, Ninni
    Pyorala, Jiri
    Liang, Xinlian
    Holopainen, Markus
    Hyyppa, Juha
    Vastaranta, Mikko
    PAPERS OF THE 26TH EUROPEAN BIOMASS CONFERENCE: SETTING THE COURSE FOR A BIOBASED ECONOMY, 2018, : 247 - 252
  • [34] Predicting tree structure from tree height using terrestrial laser scanning and quantitative structure models
    Krooks, Anssi
    Kaasalainen, Sanna
    Kankare, Ville
    Joensuu, Marianna
    Raumonen, Pasi
    Kaasalainen, Mikko
    SILVA FENNICA, 2014, 48 (02)
  • [35] Tree crown volume calculation based on 3-D laser scanning point clouds data
    Feng, Z. (fengzhongke@126.com), 2013, Chinese Society of Agricultural Machinery (44):
  • [36] Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data
    Kandare, Kaja
    Orka, Hans Ole
    Dalponte, Michele
    Naesset, Erik
    Gobakken, Terje
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2017, 60 : 72 - 82
  • [37] Tree crown segmentation based on a tree crown density model derived from Airborne Laser Scanning
    Holmgren, Johan
    Lindberg, Eva
    REMOTE SENSING LETTERS, 2019, 10 (12) : 1143 - 1152
  • [38] Quantifying Crown Morphology of Mixed Pine-Oak Forests Using Terrestrial Laser Scanning
    Uzquiano, Sara
    Barbeito, Ignacio
    San Martin, Roberto
    Ehbrecht, Martin
    Seidel, Dominik
    Bravo, Felipe
    REMOTE SENSING, 2021, 13 (23)
  • [39] Estimating single-tree branch biomass of Norway spruce with terrestrial laser scanning using voxel-based and crown dimension features
    Hauglin, Marius
    Astrup, Rasmus
    Gobakken, Terje
    Naesset, Erik
    SCANDINAVIAN JOURNAL OF FOREST RESEARCH, 2013, 28 (05) : 456 - 469
  • [40] Exploring tree growth allometry using two-date terrestrial laser scanning
    Yrttimaa, T.
    Luoma, V
    Saarinen, N.
    Kankare, V
    Junttila, S.
    Holopainen, M.
    Hyyppa, J.
    Vastaranta, M.
    FOREST ECOLOGY AND MANAGEMENT, 2022, 518