Biomass; Forest; Geometric Feature; Leaf-Wood Separation; Segmentation; Tree Information Modeling; Circle fitting; Geometric feature; Information Modeling; Leaf-wood separation; Stem-volume; Tree information modeling; Tree stems; Wood separations; Information Systems; Geography, Planning and Development
Abstract :
[en] Developing a precise tree stem curve and robust estimation of stem volume are crucial for forest inventories with various applications. Laser scanned point clouds have been recognized as the most practical data for tree information modeling. Many methods for stem curve development involve estimating stem diameters at different heights and determining stem volume by utilizing fitted cylinders based on these diameters and the associated heights. The estimation of diameter depends on circle fitting. However, many circle fitting methods are non-robust and inaccurate in the presence of noise, outliers, and significant data gaps, resulting in faulty diameters and imprecise stem volume. Limited scanning, occlusions from the physical complexity, high tree density, and adjacent branches may cause data incompleteness, and generate outliers. To address these challenges, we employ robust statistical approaches to restrain the influence of outliers and data gaps. This paper contributes by (i) exploring the problems of robust diameter estimation for partial data, and in the presence of noise and outliers, (ii) understanding the impacts of using erroneous diameters in cylinder fitting, and later for stem curve and volume estimation, and (iii) developing a robust method that couples robust circle and cylinder fittings to derive precise stem curve and estimation of stem volume in the presence of outliers and partial data. We demonstrate the performance of the proposed algorithm through terrestrial laser scanning point clouds.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
NURUNNABI, Abdul Awal Md ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Teferle, Felicia ; Geodesy and Geospatial Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, Luxembourg
Novo, Ana; Forest Research Centre of Lourizán, Xunta de Galicia, Pontevedra, Spain
Balado, Jesús ; CINTECX, GeoTECH Group, University of Vigo, Vigo, Spain
Ientilucci, Emmett; Chester F. Carlson Center for Imaging Science, Rochester Inst. of Technology, Rochester, United States
External co-authors :
yes
Language :
English
Title :
Derivation of Tree Stem Curve and Volume Using Point Clouds
Publication date :
27 June 2024
Event name :
19th 3D GeoInfo Conference 2024, 1–3 July 2024, Vigo, Spain
Event date :
01-07-2024 => 03-07-2024
Audience :
International
Journal title :
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
ISSN :
1682-1750
Publisher :
International Society for Photogrammetry and Remote Sensing
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