دورية أكاديمية
INDIVIDUAL TREE SEGMENTATION FROM BLS DATA BASED ON GRAPH AUTOENCODER
| العنوان: | INDIVIDUAL TREE SEGMENTATION FROM BLS DATA BASED ON GRAPH AUTOENCODER |
|---|---|
| المؤلفون: | R. Fekry, W. Yao, A. Sani-Mohammed, D. Amr |
| المصدر: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-1-W1-2023, Pp 547-553 (2023) |
| بيانات النشر: | Copernicus Publications, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Applied optics. Photonics |
| مصطلحات موضوعية: | Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820 |
| الوصف: | In the last two decades, Light detection and ranging (LiDAR) has been widely employed in forestry applications. Individual tree segmentation is essential to forest management because it is a prerequisite to tree reconstruction and biomass estimation. This paper introduces a general framework to extract individual trees from the LiDAR point cloud based on a graph link prediction problem. First, an undirected graph is generated from the point cloud based on K-nearest neighbors (KNN). Then, this graph is used to train a convolutional autoencoder that extracts the node embeddings to reconstruct the graph. Finally, the individual trees are defined by the separate sets of connected nodes of the reconstructed graph. A key advantage of the proposed method is that no further knowledge about tree or forest structure is required. Seven sample plots from a plantation forest with poplar and dawn redwood species have been employed in the experiments. Though the precision of the experimental results is up to 95 % for poplar species and 92 % for dawn redwood trees, the method still requires more investigations on natural forest types with mixed tree species. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2194-9042 2194-9050 |
| Relation: | https://isprs-annals.copernicus.org/articles/X-1-W1-2023/547/2023/isprs-annals-X-1-W1-2023-547-2023.pdf; https://doaj.org/toc/2194-9042; https://doaj.org/toc/2194-9050 |
| DOI: | 10.5194/isprs-annals-X-1-W1-2023-547-2023 |
| URL الوصول: | https://doaj.org/article/b4474b4ee8034f0fb2348b2ef051b53f |
| رقم الأكسشن: | edsdoj.b4474b4ee8034f0fb2348b2ef051b53f |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 21949042 21949050 |
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| DOI: | 10.5194/isprs-annals-X-1-W1-2023-547-2023 |