Extracting individual trees from lidar point clouds using treeseg
Extracting individual trees from lidar point clouds using treeseg
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DOI：
10.1111/2041-210x.13121
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发表时间：
2019-03-01
影响因子：
6.6
通讯作者：
Calders, Kim
中科院分区：
文献类型：
--
作者：
Burt, Andrew;Disney, Mathias;Calders, Kim
最近的研究表明，激光雷达衍生的方法在植物生态学和林业的潜力。这些方法的一个局限性是访问点云的信息内容，从中可以检索树尺度度量。目前，这是通过从更大面积的点云中手动分割树级点云来进行的，这是一项在数千个茎中不可行的工作。在这里，我们介绍了Treeseg，这是一款用于自动化此任务的开源软件。该方法利用了通用的点云处理技术，包括欧几里德聚类，主成分分析，基于区域的分割，形状拟合和连通性测试。这种数据驱动的方法使用很少的先验假设的树架构，和激光雷达仪器之间的可转移性仅受数据质量要求。我们证明了treeseg算法在这里获得的数据从一个结构简单的开放式森林和一个复杂的热带森林。在这些数据中，我们分别成功地自动提取了96%和70%的树，其余的需要一些简单的手动分割。treeseg允许随时快速访问激光雷达点云中包含的树级信息。treeseg应有助于更广泛地采用激光雷达衍生的方法，将其应用于从估计碳储量到描述植物形态和功能的各种应用。
Recent studies have demonstrated the potential of lidar-derived methods in plant ecology and forestry. One limitation to these methods is accessing the information content of point clouds, from which tree-scale metrics can be retrieved. This is currently undertaken through laborious and time-consuming manual segmentation of tree-level point clouds from larger-area point clouds, an effort that is impracticable across thousands of stems. Here, we present treeseg, an open-source software to automate this task. This method utilises generic point cloud processing techniques including Euclidean clustering, principal component analysis, region-based segmentation, shape fitting and connectivity testing. This data-driven approach uses few a priori assumptions of tree architecture, and transferability across lidar instruments is constrained only by data quality requirements. We demonstrate the treeseg algorithm here on data acquired from both a structurally simple open forest and a complex tropical forest. Across these data, we successfully automatically extract 96% and 70% of trees, respectively, with the remainder requiring some straightforward manual segmentation. treeseg allows ready and quick access to tree-scale information contained in lidar point clouds. treeseg should help contribute to more wide-scale uptake of lidar-derived methods to applications ranging from the estimation of carbon stocks through to descriptions of plant form and function.