Three-Dimensional Modeling and Visualization of Single Tree LiDAR Point Cloud Using Matrixial Form
Article
Tarsha Kurdi, Fayez, Lewandowicz, Elżbieta, Shan, Jie and Gharineiat, Zahra. 2024. "Three-Dimensional Modeling and Visualization of Single Tree LiDAR Point Cloud Using Matrixial Form." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17, pp. 3010-3022. https://doi.org/10.1109/JSTARS.2024.3349549
Article Title | Three-Dimensional Modeling and Visualization of Single Tree LiDAR Point Cloud Using Matrixial Form |
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ERA Journal ID | 200605 |
Article Category | Article |
Authors | Tarsha Kurdi, Fayez, Lewandowicz, Elżbieta, Shan, Jie and Gharineiat, Zahra |
Journal Title | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Journal Citation | 17, pp. 3010-3022 |
Number of Pages | 13 |
Year | 2024 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
ISSN | 1939-1404 |
2151-1535 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/JSTARS.2024.3349549 |
Web Address (URL) | https://ieeexplore.ieee.org/document/10380663 |
Abstract | Tree modeling and visualization still represent a challenge in the light detecting and ranging area. Starting from the segmented tree point clouds, this article presents an innovative tree modeling and visualization approach. The algorithm simulates the tree point cloud by a rotating surface. Three matrices, X, Y , and Z , are calculated by considering the middle of the projected tree point cloud on the horizontal plane. This mathematical form not only allows tree modeling and visualization but also permits the calculation of geometric characteristics and parameters of the tree. The superimposition of the tree point cloud over the constructed model confirms its high accuracy where all the points of the tree cloud are within the constructed model. The tests with multiple single trees demonstrate an overall average fit between 0.3 and 0.89 m. The built tree models are also compliant with the Open Geospatial Consortium CityGML standards at the level of a physical model. This approach opens a door to numerous applications for visualization, computation, and study of forestry and vegetation in urban as well as rural areas. |
Keywords | Light detection and ranging (LiDAR); Open Geospatial Consortium (OGC) CityGML physical model; tree model; vegetation; visualization |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 401399. Geomatic engineering not elsewhere classified |
Byline Affiliations | School of Surveying and Built Environment |
University of Warmia and Mazury, Poland | |
Purdue University, United States |
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License: CC BY-NC-ND 4.0 | ||
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