基于激光点云数据的树木枝叶分割和三维重建

针对目前树木点云三维重建方法仅仅实现树木三维形态结构的重建,而忽视了树木表面纹理和细节的问题,本研究提出了一种超体素分割和基于kd-tree纹理映射的贪婪投影三角化算法相结合的树木点云重建方法。首先根据点云的颜色、法线和空间距离等特征,利用体素云连通性分割算法生成超体素块;然后基于不同超体素块之间的凹凸关系,利用局部凸包连接算法对点云进行聚类分割,从而实现枝干和树叶点云分割;最后利用贪婪投影三角化算法分别对枝干和树叶点云进行三维重建,并基于点云RGB信息,利用kd-tree算法对枝干和树叶模型添加真实的纹理色彩。结果表明,树木点云重建方法能实现枝干表面和树叶等细节模型的构建,还原真实的树木形状结构和纹理色彩;通过对不同抽稀层次下的点云进行测试,发现核桃楸树木模型主要枝干结构得到了很好的保留,这说明建模算法对点密度的变化具有鲁棒性。     

基于机载LiDAR落叶松树冠几何形状三维重建关键技术研究

森林冠层的三维重建研究能够更加直观反映森林空间结构,提高森林参数的测量精度。目前小光斑激光雷达已经广泛应用于林业研究中。为建立落叶松树冠三维形状模型,以长春净月潭实验区落叶松机载LiDAR(LiDAR,Light Detection And Ranging)数据为基础,采用K-means算法提取建模参数。该算法以单木树冠顶点作为初始聚类中心,经过4次迭代估测出单木树高和单木树冠直径,通过与试验区的单木实测数据对比,进行相关性分析,得到估测树高和估测树冠与实测数据相关系数分别为0.892 4和0.769 0,经过验证,估测树高和估测树冠的精度为94.06%和82.21%。利用激光雷达提取出的单木坐标、树高、树冠和冠基高采用旋转抛物线方法重建森林尺度三维模型呈现森林结构。     

基于点云数据的植物叶片三维重建

叶片是植物最重要的器官之一,为构建植物叶片的高精度几何模型,提出了一种基于三维点云数据的植物叶片几何建模方法。针对植物叶片形态特征,选定最适三维扫描仪进行叶片点云数据获取,通过点云的配准、简化及去噪等操作得到高质量叶片点云数据,在此基础上进行叶片网格生成与网格优化,最终得到高精度植物叶片网格模型。利用该方法分别对黄瓜、玉米和两个品种的葡萄叶片进行几何建模,结果表明,所构建的叶片模型能够较好地保持叶片形态特征,且较以前的方法在精确度和真实感方面有了较大的提高。该研究对于推动数字植物几何建模及进一步基于几何模型的可视化计算具有重要意义。     

基于机载LiDAR点云估测林分的平均树高

以内蒙古上库力农场为研究区,基于高程归一化后的植被点云数据计算了植被点云高度阈值平均值,建立林分平均树高线性回归模型,并进行精度评定。结果表明,模型估测平均树高精度最高为99.81%,最低为87.09%,总体平均精度为94.56%。利用植被点云高度阈值平均值估测林分平均树高具有较高的可靠性。     

基于LiDAR点云能量信息的樟子松郁闭度反演方法

为提高小光斑激光雷达估测针叶林郁闭度的精度,采用回归分析法建立多变量回归模型,通过对小光斑激光 雷达点云数据进行处理,分别提取3 个数量比值变量、3 个能量比值变量,并建立郁闭度单变量反演模型,接着在单 变量的基础上进行多元线性回归分析,建立郁闭度多变量反演模型,最后用剩余数据对所建立的反演模型进行精 度评价。结果表明:在郁闭度单变量反演模型中I2反演模型最好, 拟合相关性为R2 =0.818, Adj R2 =0.810, RMSE = 0.016,模型精度为P =0.978;多变量反演模型中LPI' 和I'3 组合的模型最好, 拟合相关性为R2 = 0.898, AdjR2= 0.889, RMSE =0.012,模型精度为P =0.972。由最终所得模型可知,能量比值变量模型所得结果相对数量比值变 量模型结果要好且稳定,多变量反演模型的拟合相关性及精度都比单变量模型要高。本研究所提取的参数相对较 少,且能量比值变量的提取有一定的局限性,未来研究中应提取更多的高效参数且进一步加强能量比值变量的探究。      

基于计算机视觉的水稻三维重建方法

利用多幅多角度的拍摄方法对二维图像进行采集,通过数字化处理得到单株水稻各视角侧面投影及轮廓图像。然后使用基于计算机视觉的三维重建方法,构造单株水稻的可视立体包络,从而得到单株水稻的三维立体像素模型。使用移动立方体算法对单株水稻立体像素模型进行外围表面重建,最后得到单株水稻三维重建模型。     

树木枝干点云数据的等值线提取

通过三维激光扫描技术得到的树木枝干点云数据,不仅数据量大,而且特征复杂,不适合采用传统的方法提取等值线。对此,首先把点云数据中树木的枝和干分为不同的部分,然后建立点云的分层模型,并分析点云在树高方向上的数据量分布。在高精度采样下,将分层点云作为等值线的采样数据,对每层数据中不同部分的树木枝干点云分别采用凸包算法进行连接,建立树木枝干的等值线模型。结果表明:在没有先验等值线知识和建立点云对象模型的条件下,利用迭代的凸包算法可以有效地对树木枝干离散点云数据进行连接,得到的等值线符合一般等值线的特点。最后通过实例验证了方法的适用性。图8表1参11     

利用LiDAR离散点云估测针叶林叶面积指数

通过对小光斑激光雷达离散点云数据进行处理,提取了6个变量参数分别用于估测针叶林叶面积指数,为了提高模型估测精度及弥补单变量模型的不足,在单变量模型的基础上尝试多变量组合共同用于估测森林叶面积指数,经过对比得出单变量模型中OGF模型最好,拟合相关性R=0.897,预测精度p=0.959;多变量预测模型结果差异不大,拟合相关性均＞0.905,估测精度均＞0.957。同时为了验证模型的推广性,对点云数据进行随机稀释操作获得4种不同密度的点云数据,分别用于验证点云密度对OGF模型及OGF与LPI组合模型的影响,结果表明点云密度对模型结果的影响不大,即使在0.125倍点云密度时模型仍能较好的估测针叶林叶面积指数,满足生产需要。     

基于三维激光点云数据建立三维树木模型方法的研究

提出一种基于三维地面激光测距仪（Terrestrial LiDAR,TLiDAR）所获取点云数据重建三维树木模型的方法。利用TLiDAR点云数据构建三维树木模型的优势在于可以精确重构树木模型,精确量取树木任意部位尺寸,且免于或受到较小的外界干扰。利用这种模型可以对树木枝叶冠幅的状况以及树干的横截面积等进行评估,在三维绿量和生物量计算上具有显著优势。     

基于激光雷达和Kinect相机点云融合的单木三维重建

为了更好地建立单木三维彩色模型，获得准确表型参数，提出了一种基于Kinect v2相机和激光雷达的单木点云信息融合检测方法。首先由激光雷达采集樱树单木所在区域的完整环境点云，生成点云地图；由Kinect相机采集樱树单木多视角点云得到完整的三维彩色点云；然后以激光雷达点云位置为基准，通过选取对应同名点的方式对2种点云进行初始配准，使点云之间具有良好的初始位置关系，再使用最近点迭代（iterative closest point, ICP）算法对点云进行精配准；最后使用彩色点云对雷达点云进行点云着色融合处理，实现樱树单木的三维重建。结果显示：与只使用Kinect v2相机生成的樱树单木表型参数对比，融合后的樱树单木的株高、冠幅和胸径的平均相对误差分别降低了1.52、6.46和18.17个百分点。研究结果表明，Kinect v2深度彩色相机和激光雷达在单木三维重建上能实现优势互补，提升点云配准精度，同时，既能降低光照气候条件的影响，又能增加测量距离，单木表型参数更准确。     

基于机载LiDAR数据的林下地形提取算法比较与组合分析

激光雷达(LiDAR)克服了传统测量技术的缺点, 成为了获取DEM的新型手段。针对不同地形林区,选择合理的点云滤波算法,是提取林下地形的关键步骤。本研究在黑龙江省凉水自然保护区内选择了3块具有代表性的区域,分别为平缓山地林区、陡峭山地林区和复杂地区。以1:10 000地形图矢量化生成的高精度DEM为参考,评价了迭代线性最小二乘法、基于坡度法、不规则三角网法(TIN)点云滤波算法在3种地形的适应性。结果表明:不同算法有不同的适应区域。3种方法在平缓山地林区都具有良好的效果,决定系数(R2)均达到了0.98,均方根误差(RMSE)均低于0.21 m。迭代线性最小二乘法在复杂地区滤波效果最好,R2为0.94,RMSE为0.21 m;不规则三角网法在陡峭山地林区效果最好,R2为0.99,RMSE为1.43 m。但是,单一的方法在复杂区域情况下、陡峭山地林区,有明显的分类误差,会将植被分为地面点。为提高林下地形提取精度,本文提出不同滤波方法的组合双重滤波,结果表明,迭代线性最小二乘法和不规则三角网方法组合可以在减少参数调整情况下得到良好滤波效果,对复杂地区、陡峭山地林区滤波效果大大改善。      

Leaf Area Index evaluation in vineyards using 3D point clouds from UAV imagery

Precision Agriculture - The Leaf Area Index (LAI) is an ecophysiology key parameter characterising the canopy-atmosphere interface where most of the energy fluxes are exchanged. However, producing...     

Multi-temporal analysis of terrestrial laser scanning data to detect basal stem rot in oil palm trees

Terrestrial laser scanning technology is an advanced active remote sensing ranging method that is well suited for yielding high-resolution scans of the morphology of a tree, which is an indicator of the health of the plant. The Ganoderma boninense fungus causes basal stem rot (BSR), which threatens the oil palm industry in Malaysia. To date, the current practice of inspection in a plantation is conducted every 6 months. Monitoring the progress with a closer gap is required to comprehend if any changes can be seen earlier than 6 months. Therefore, the objectives of this study were to identify the most suitable parameters of the oil palm trees to detect the BSR disease based on temporal laser scanning data and to identify suitable time frames for monitoring the progress of the symptoms of the disease. Terrestrial laser scanning data was used to analyse changes in the crown and frond metrics of oil palm trees with two different scan durations i.e., 2- and 4-months after the first scan. This spatio-temporal data is important in the precision agriculture field for better oil palm management, to understand the disease development for long-term solutions and also to provide a fast response so that appropriate treatment can be given to the palm as early as possible. Statistical analyses, i.e., the Kruskal–Wallis test with α?=?0.05 and the Wilcoxon post-hoc test, were conducted to determine significant differences in the parameters at different points in time. The results show that crown strata number 17 (850 cm from the top) and the crown area were the most suitable parameters to be used. Furthermore, the oil palm trees with BSR can be detected by comparing the 4-month scan or the second 2-month scan. The results have shown that the effect of Ganoderma boninense infection can be differentiated at the later stage. In conclusion, the changes can be measured at 4-months after the first inspection, thus helping to preventing crop losses.

     

应用LSCM和SEM鉴定银杏花粉的倍性

以经秋水仙碱诱导获得的银杏大花粉为材料,以未经处理的正常银杏花粉为对照,利用扫描电子显微镜和激光扫描共聚焦显微镜分别观察2种花粉表面形态,并分析对比其细胞内的DNA相对荧光量与银杏大花粉核内染色体倍性关系,为正确检出银杏二倍体花粉奠定重要工作基础。研究结果表明,此方法用于花粉粒的倍性鉴定科学准确,所需试验样本少,实用性强,在植物花粉倍性鉴定中有着较好的应用前景。      

Identifying the ploidy of ginkgo pollen using laser scanning confocai and scanning electron microscope.

以经秋水仙碱诱导获得的银杏大花粉为材料,以未经处理的正常银杏花粉为对照,利用扫描电子显微镜和激光扫描共聚焦显微镜分别观察2种花粉表面形态,并分析对比其细胞内的DNA相对荧光量与银杏大花粉核内染色体倍性关系,为正确检出银杏二倍体花粉奠定重要工作基础。研究结果表明,此方法用于花粉粒的倍性鉴定科学准确,所需试验样本少,实用性强,在植物花粉倍性鉴定中有着较好的应用前景。     

Mobile terrestrial laser scanner applications in precision fruticulture/horticulture and tools to extract information from canopy point clouds

LiDAR sensors are widely used in many areas and, in recent years, that includes agricultural tasks. In this work, a self-developed mobile terrestrial laser scanner based on a 2D light detection and ranging (LiDAR) sensor was used to scan an intensive olive orchard, and different algorithms were developed to estimate canopy volume. Canopy volume estimations derived from LiDAR sensor readings were compared to conventional estimations used in fruticulture/horticulture research and the results prove that they are equivalent with coefficients of correlation ranging from r = 0.56 to r = 0.82 depending on the algorithms used. Additionally, tools related to analysis of point cloud data from the LiDAR-based system are proposed to extract further geometrical and structural information from tree row crop canopies to be offered to farmers and technical advisors as digital raster maps. Having high spatial resolution information on canopy geometry (i.e., height, width and volume) and on canopy structure (i.e., light penetrability, leafiness and porosity) may result in better orchard management decisions. Easily obtainable, reliable information on canopy geometry and structure may favour the development of decision support systems either for irrigation, fertilization or canopy management, as well as for variable rate application of agricultural inputs in the framework of precision fruticulture/horticulture.     

Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners

Mapping the leaf area index (LAI) by using mobile terrestrial laser scanners (MTLS) is of significance for viticulture. LAI is related to plant vigour and foliar development being an important parameter for many agricultural practices. Since it may present spatial variability within vineyards, it is very interesting monitoring it in an objective repeatable way. Considering the possibility of using on-the-go sensors such as MTLS within an agricultural plot, it is necessary to set a proper length of the row to be scanned at each sample point for a reliable operation of the scanner. Three different row length sections of 0.5, 1, and 2 m have been tested. Data analysis has shown that models required to estimate LAI differ significantly depending on the scanned length of the row; the model required to estimate LAI for short sections (0.5 m) is different from that required for longer sections (1 and 2 m). Of the two models obtained, we recommend using MTLS for scanning row length sections of 1 m because the practical use of the sensor in the field is simplified without compromising the results (there is little variation in the model when the row length section changes from 1 to 2 m). In addition, a sufficient number of sampling points is obtained to support a map of the LAI. Linear regression models using as explanatory variable the tree area index, obtained from the data provided by the scanner, are used to estimate the LAI.     

基于三维激光点云的城市绿化树种材积及树干碳储量无损精确测算

城市森林是森林碳库的重要组成部分。为探索三维激光扫描技术（TLS）在无损精确测算城市绿化树种树干材积及碳储量方面的潜力,了解不同区分段长度对基于TLS测算树干材积的影响并对现有模型测算的树干材积及碳储量的精度进行了评估,采集30株无患子Sapindus mukorossi点云,并按径阶采集树干钻芯样本,研究在不同区分段长度下测算的树干材积及碳储量,并与现有模型的测算结果相比较。结果表明:①基于TLS能够提取高精度的立木胸径和树高（平均相对误差分别为1.97%和4.85%）,可实现城市绿化树种树干材积及碳储量的无损精确测算。②基于TLS在区分段长度小于0.50 m时能测算得到高精度的树干材积。③城市绿化树种的材积和树干碳储量与野外林分存在显著差异（P < 0.05）。现有模型并不适用于城市绿化树种。     

Critical point drying for scanning electron microscopic sthdy of ciliary motion

Scanning electron microscopic study of tile pattern of ciliary coordination and the form of the ciliary beat is now possible. Rapid fixation stops tile ciliary activity instantaneously, and critical point drying avoids distortion of the cilia by surface tension forces. Such stuidies have been made on the ciliate Opalina with this new technique.     

三维激光扫描系统在林业中的应用研究

该文介绍了三维激光扫描系统的组成、工作原理及仪器的性能指标、特点和操作方法.通过甘肃省小陇山林区实验,首次将三维激光扫描系统引入林业调查.通过三维激光扫描仪获取单株立木空间点云数据,利用软件建立了立木三维模型.从三维模型上可直接量测立木树高、胸径、冠幅和计算立木材积,利用获取的材积可进一步建立立木材积方程和编制立木材积表.通过与伐倒木实测数据对比,采用该系统获取的测树因子和立木材积均满足林业调查的精度要求.研究表明,采用三维激光扫描系统可实现对疏林单株立木的无损伤、高效、精准监测,可在森林资源调查中应用.