A Comparative Assessment of the Performance of Individual Tree Crowns Delineation Algorithms from ALS Data in Tropical Forests
A Comparative Assessment of the Performance of Individual Tree Crowns Delineation Algorithms from ALS Data in Tropical Forests
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DOI：
10.3390/rs11091086
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发表时间：
2019-05-01
期刊：
影响因子：
5
通讯作者：
Vincent, Gregoire
中科院分区：
文献类型：
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作者：
Aubry-Kientz, Melaine;Dutrieux, Raphael;Vincent, Gregoire
热带森林冠层由形状和高度各不相同的多个物种的树冠组成，地面调查通常不能可靠地描述其结构。机载激光扫描数据可用于确定这些树冠的特征，但为北方或温带森林开发的分析工具可能需要调整，然后才能应用于热带环境。因此，我们比较了从六个不同的分割方法应用到六个地块（39公顷）在法属圭亚那的研究地点的结果。我们测量了自动分割牙冠投影与高分辨率摄影上手动描绘的选定牙冠的重叠。我们还评估了拟合优度以下自动匹配与实地调查数据使用模型连接树直径树冠宽度。在该基准中测试的不同方法分割了具有不同特征的高度不同数量的牙冠。基于点云的分割方法（AMS 3D和Graph-Cut）在全局上优于基于冠层高度模型的方法，特别是对于小冠; AMS 3D方法优于用于重叠分析的其他测试方法，AMS 3D和Graph-Cut在自动匹配验证方面表现最佳。然而，其他方法的冠层高度模型的基础上进行更好的非常大的紧急冠。热带潮湿森林的茂密的树叶阻止足够的点密度在林下部分sub树冠树木准确，无论分割方法。
Tropical forest canopies are comprised of tree crowns of multiple species varying in shape and height, and ground inventories do not usually reliably describe their structure. Airborne laser scanning data can be used to characterize these individual crowns, but analytical tools developed for boreal or temperate forests may require to be adjusted before they can be applied to tropical environments. Therefore, we compared results from six different segmentation methods applied to six plots (39 ha) from a study site in French Guiana. We measured the overlap of automatically segmented crowns projection with selected crowns manually delineated on high-resolution photography. We also evaluated the goodness of fit following automatic matching with field inventory data using a model linking tree diameter to tree crown width. The different methods tested in this benchmark segmented highly different numbers of crowns having different characteristics. Segmentation methods based on the point cloud (AMS3D and Graph-Cut) globally outperformed methods based on the Canopy Height Models, especially for small crowns; the AMS3D method outperformed the other methods tested for the overlap analysis, and AMS3D and Graph-Cut performed the best for the automatic matching validation. Nevertheless, other methods based on the Canopy Height Model performed better for very large emergent crowns. The dense foliage of tropical moist forests prevents sufficient point densities in the understory to segment subcanopy trees accurately, regardless of the segmentation method.