A Local Projection-Based Approach to Individual Tree Detection and 3-D Crown Delineation in Multistoried Coniferous Forests Using High-Density Airborne LiDAR Data
A Local Projection-Based Approach to Individual Tree Detection and 3-D Crown Delineation in Multistoried Coniferous Forests Using High-Density Airborne LiDAR Data
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DOI：
10.1109/tgrs.2018.2865014
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发表时间：
2019-02
影响因子：
8.2
通讯作者：
A. Harikumar;F. Bovolo;L. Bruzzone
中科院分区：
文献类型：
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作者：
A. Harikumar;F. Bovolo;L. Bruzzone
准确的树冠检测和优势树和次优势树的划分对于在单棵树水平上准确清查森林至关重要。最先进的树木检测和树冠描绘方法在主要针对优势树木时具有良好的性能，而在处理次优势树木时则表现出较低的准确性。在本文中，我们提出了一种新方法，使用小足迹高密度机载光检测和测距数据来准确检测和描绘以针叶树为主的多层森林中的主导树冠和次主导树冠。在这里，使用冠层高度模型分割技术描绘的 3D 候选云段被投影到一个新颖的 3D 空间上，在该空间中，可以准确地检测和描绘主导树冠和次主导树冠。使用从投影数据导出的二维特征来检测树冠。借助从云段导出的 2D 特征和 3D 纹理信息，在体素级别上进行牙冠的描绘。纹理信息通过使用 3-D 灰度共生矩阵进行建模。性能评估是在一组六个圆形图上进行的，这些图上有参考数据。与现有技术相比所获得的高检测和描绘精度证明了所提出方法的性能。
Accurate crown detection and delineation of dominant and subdominant trees are crucial for accurate inventorying of forests at the individual tree level. The state-of-the-art tree detection and crown delineation methods have good performance mostly with dominant trees, whereas exhibits a reduced accuracy when dealing with subdominant trees. In this paper, we propose a novel approach to accurately detect and delineate both the dominant and subdominant tree crowns in conifer-dominated multistoried forests using small footprint high-density airborne Light Detection and Ranging data. Here, 3-D candidate cloud segments delineated using a canopy height model segmentation technique are projected onto a novel 3-D space where both the dominant and subdominant tree crowns can be accurately detected and delineated. Tree crowns are detected using 2-D features derived from the projected data. The delineation of the crown is performed at the voxel level with the help of both the 2-D features and 3-D texture information derived from the cloud segment. The texture information is modeled by using 3-D Gray Level Co-occurrence Matrix. The performance evaluation was done on a set of six circular plots for which reference data are available. The high detection and delineation accuracies obtained over the state of the art prove the performance of the proposed method.