基于激光点云和视觉计算的阔叶树林学参数反演研究

项目名称： 基于激光点云和视觉计算的阔叶树林学参数反演研究

项目编号： No.31300472

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 农业科学

项目作者： 云挺

作者单位： 南京林业大学

项目金额： 21万元

中文摘要： 本课题运用地面激光扫描仪作为阔叶树信息计测的手段，并结合林学与计算机视觉的理论方法从激光点云数据中挖掘精确的阔叶树林学指标。具体的研究思路为：首先，设计三维点云的特征提取与分类算法，实现阔叶树不同植物器官的识别与分类；其次，结合计算机图形学理论研究离散点云到三维曲面的映射算法，重构阔叶树真实的三维形态模型，进而获取阔叶树树干的干形指数、节瘤、分枝位置等参数；再次，基于植物学与物理学原理，实现阔叶树叶片在不同生态环境下的真实感绘制，旨在为叶面积指数和树木冠层结构参数的测量提供依据；最后，与叶面积测量仪、高光谱辐射仪、机载激光雷达等其它途径获取的阔叶树林学指标进行类比，验证结果的有效性并修正误差。本课题以最新的测量技术丰富了传统的阔叶树数据获取的方法，并借鉴不同学科的理论挖掘蕴含其中的生物量参数，进而为阔叶树林学指标的计测研究和我国"数字化林业"的建设进程拓宽了思路。

中文关键词： 激光点云；林学参数反演；机器视觉算法；精准林业；

英文摘要： This topic take terrestrial laser scanner (TLS) as the means for physiological information measurement of broad-leaved trees, also combine with forest science and computer vision theory to calculate accurate forestry parameters of broad-leaved trees from point cloud data of laser scanner. Specific research plan include: Firstly, three-dimensional point cloud feature extraction and classification algorithms are designed for classification and identification of broad-leaved trees organs; Secondly, combing the computer graphics theory, algorithms are proposed for mapping discrete point cloud to the 3D surface of real trees, thus the real morphological models of broad-leaved trees are reconstructed in order to calculate tree parameters include stem form exponents, branches and knots positions; Thirdly, based on the botany and physics principle, realistic rendering methods of broad-leaved tree leaves under different ecological conditions and natural environment are realized, which aim to provide scientific evidence for leaf area index and canopy structure parameters estimate; Lastly, compared with the forestry index that acquired by leaf area measurement Instrument, hyper spectral radiometer and Airborne Lidar, validity of our method are verified and error correction are considered. In brief, this topic use the lates

英文关键词： Laser point cloud；Forest parameter retrieval；Computer vision method；Precision forestry；