Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees
Tree precise classification and identification of forest species is a core issue of forestry resource monitoring and ecological effect assessment. In this paper, an independent tree species classification method based on fractal features of terrestrial laser point cloud is proposed. Firstly, the ter...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Fractal and Fractional |
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| Online Access: | https://www.mdpi.com/2504-3110/5/1/14 |
| _version_ | 1797417200442671104 |
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| author | Ju Zhang Qingwu Hu Hongyu Wu Junying Su Pengcheng Zhao |
| author_facet | Ju Zhang Qingwu Hu Hongyu Wu Junying Su Pengcheng Zhao |
| author_sort | Ju Zhang |
| collection | DOAJ |
| description | Tree precise classification and identification of forest species is a core issue of forestry resource monitoring and ecological effect assessment. In this paper, an independent tree species classification method based on fractal features of terrestrial laser point cloud is proposed. Firstly, the terrestrial laser point cloud data of an independent tree is preprocessed to obtain terrestrial point clouds of independent tree canopy. Secondly, the multi-scale box-counting dimension calculation algorithm of independent tree canopy dense terrestrial laser point cloud is proposed. Furthermore, a robust box-counting algorithm is proposed to improve the stability and accuracy of fractal dimension expression of independent tree point cloud, which implementing gross error elimination based on Random Sample Consensus. Finally, the fractal dimension of a dense terrestrial laser point cloud of independent trees is used to classify different types of independent tree species. Experiments on nine independent trees of three types show that the fractal dimension can be stabilized under large density variations, proving that the fractal features of terrestrial laser point cloud can stably express tree species characteristics, and can be used for accurate classification and recognition of forest species. |
| first_indexed | 2024-03-09T06:15:21Z |
| format | Article |
| id | doaj.art-1e5c23699167464381f8e4064f9feea1 |
| institution | Directory Open Access Journal |
| issn | 2504-3110 |
| language | English |
| last_indexed | 2024-03-09T06:15:21Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fractal and Fractional |
| spelling | doaj.art-1e5c23699167464381f8e4064f9feea12023-12-03T11:53:51ZengMDPI AGFractal and Fractional2504-31102021-02-01511410.3390/fractalfract5010014Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent TreesJu Zhang0Qingwu Hu1Hongyu Wu2Junying Su3Pengcheng Zhao4School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaChang Guang Satellite Technology Co., Ltd., Changchun 251500, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaTree precise classification and identification of forest species is a core issue of forestry resource monitoring and ecological effect assessment. In this paper, an independent tree species classification method based on fractal features of terrestrial laser point cloud is proposed. Firstly, the terrestrial laser point cloud data of an independent tree is preprocessed to obtain terrestrial point clouds of independent tree canopy. Secondly, the multi-scale box-counting dimension calculation algorithm of independent tree canopy dense terrestrial laser point cloud is proposed. Furthermore, a robust box-counting algorithm is proposed to improve the stability and accuracy of fractal dimension expression of independent tree point cloud, which implementing gross error elimination based on Random Sample Consensus. Finally, the fractal dimension of a dense terrestrial laser point cloud of independent trees is used to classify different types of independent tree species. Experiments on nine independent trees of three types show that the fractal dimension can be stabilized under large density variations, proving that the fractal features of terrestrial laser point cloud can stably express tree species characteristics, and can be used for accurate classification and recognition of forest species.https://www.mdpi.com/2504-3110/5/1/14independent treedense terrestrial laser point cloudfractal featurefractal dimensiontree species classification |
| spellingShingle | Ju Zhang Qingwu Hu Hongyu Wu Junying Su Pengcheng Zhao Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees Fractal and Fractional independent tree dense terrestrial laser point cloud fractal feature fractal dimension tree species classification |
| title | Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees |
| title_full | Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees |
| title_fullStr | Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees |
| title_full_unstemmed | Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees |
| title_short | Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees |
| title_sort | application of fractal dimension of terrestrial laser point cloud in classification of independent trees |
| topic | independent tree dense terrestrial laser point cloud fractal feature fractal dimension tree species classification |
| url | https://www.mdpi.com/2504-3110/5/1/14 |
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