(英)改进的三角网构网算法用于LiDAR树冠体积提取
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北京林业大学、国家测绘地理信息局第一航测遥感院,北京林业大学,北京林业大学,国家测绘地理信息局第一航测遥感院,国家测绘地理信息局第一航测遥感院

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国家自然科学基金(41371001)


Extraction of crown volume using triangulated irregular network algorithm based on LiDAR
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Beijing Forestry University, Research and development center,The First Institute of Photo-grammetry and Remote Sensing,State Bureau of Surveying and Mapping,Beijing Forestry University,Beijing Forestry University,The First Institute of Photo-grammetry and Remote Sensing, State Bureau of Surveying and Mapping,The First Institute of Photo-grammetry and Remote Sensing, State Bureau of Surveying and Mapping

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    摘要:

    在分析现存点云处理方法的特性后,通过改进三角网构网算法的算法机制,提出了一种基于空间分割的分块优先级机制的三角网表面重建算法,用于重构树冠表面,实现树冠体积的准确提取.通过可视化方法对比了多种算法的点云构网效果,以实验区选定的30棵树为研究对象,利用T-LiDAR获取树冠点云数据,通过人工方法、传统算法和本文的改进算法计算树冠体积,对这些结果进行了对比分析.分析发现: 四种方法之间均显示出较好的相关性(R2>=0.831), 其中所提出的改进Delaunay方法拥有理想的精度,较好稳定性和最少的耗费时间.实验结果表明,提出的算法在点云(尤其是T-LiDAR数据)树冠的体积提取中具有很大的优势.结合T-LiDAR数据还可以实现树冠表面积和生物量等树冠因子的高精度快速提取.

    Abstract:

    To improve the precision and effectiveness of crown-volume measurement and calculation, the authors have analyzed the characteristics of existing methods for processing the point cloud and have proposed a crown-surface reconstruction algorithm using a triangulated irregular network and voxel-based volumetric algorithms. This algorithm, after reconstructing the surface of the point-cloud crown, can extract the crown volume. This paper compares classic Delaunay grid-construction results with those from the proposed algorithm using a visualization method and carries out algorithm complexity analysis. These efforts have confirmed that the method presented in this paper is better than the traditional algorithm from the viewpoints of grid-construction accuracy and efficiency. This research, examined 30 trees in the study area. T-LiDAR was used to obtain point-cloud data for the crown. The classical manual dendrometric method, the point-cloud measurement method, the classical Delaunay algorithm, and the method proposed in this paper were used to calculate crown volume, and the results were compared. The four methods showed a good correlation (R2>=0.831), while the improved Delaunay method presented in this paper achieved good precision, good stability, and the least calculation time. The results of these experiments proved that the proposed algorithm has a considerable advantage in crown-volume extraction from point clouds (especially from T-LiDAR data). The combination of the proposed algorithm with T-LiDAR data could extract crown properties such as surface area and biomass quickly and precisely.

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巩垠熙,闫飞,冯仲科,刘云峰,薛文星,谢飞.(英)改进的三角网构网算法用于LiDAR树冠体积提取[J].红外与毫米波学报,2016,35(2):177~183]. GONG Yin-Xi, YAN Fei, FENG Zhong-Ke, LIU Yun-Feng, XUE Wen-Xing, XIE Fei. Extraction of crown volume using triangulated irregular network algorithm based on LiDAR[J]. J. Infrared Millim. Waves,2016,35(2):177~183.]

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  • 收稿日期:2015-03-12
  • 最后修改日期:2015-12-15
  • 录用日期:2015-09-23
  • 在线发布日期: 2016-05-11
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