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As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like—“can ALS now work better on the task of LAI prediction?” As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R2 = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding. 相似文献
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分析了地面三维激光雷达点云误差来源，提出了相应的误差校正模型。通过实测数据验证，该模型能够消除系统误差，提高了点云精度。 相似文献
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在GPS接收机产生机动时,运动模型的不匹配会给跟踪算法带来性能损失。本文提出一种机动检测、Unscented Kalman Filter(UKF)以及总体最小二乘(Total Least Square,TLS)相结合的解算方法用于接收机机动的GPS跟踪解算。首先,通过机动检测算法对目标的机动性进行判别,当目标机动较小时,利用UKF的最优检测性能进行跟踪,而当目标机动较大时,结合TLS的强跟踪性能,采用TLS和UKF联合进行跟踪。从而,在不增加方程维数的情况下,实现机动目标的实时、快速跟踪。仿真结果表明该方法对机动目标具有良好的跟踪性能。 相似文献
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针对传统的应用最小二乘法建立高斯-马尔科夫(G-M)模型实现坐标系统转换的方法导致转换模型参数精度低下的问题,该文提出一种基于总体最小二乘算法的坐标系统转换方法。考虑到粗差会导致控制点坐标精度差异较大,因此根据稳健估计理论进行迭代定权,在总体最小二乘算法下建立G-M模型,以便求解转换模型参数,并通过算例比较不同算法的转换精度。实验结果表明:基于稳健估计的总体最小二乘抗差算法实现的空间坐标转换精度高于传统方法的转换精度。 相似文献
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快速获取活断层的高精度微地貌形态和对应的浅层三维结构是揭示活断层浅地表形迹与活动特征的关键。文中综合利用地面三维激光扫描仪和地质雷达技术,以川西理塘地区毛垭坝盆地北缘主边界断裂禾尼段的正断层崖为研究对象,获取了该处正断层错动2期最新地貌面的精确地表垂直位移量和浅层二维地质雷达图像,并初步建立了基于地面三维激光与地质雷达的活断层微地貌精细化三维测量方法,构建了断层崖微地貌的精细三维模型和浅表三维图像,揭示了正断层崖处发育的伸展地堑结构,同时初步实现了断层微地貌地表地下三维数据的一体化融合显示及相互解译。应用结果表明,该方法可以同时快速、高效、无损地获取大范围内的活断层微地貌及浅层结构的多层次、多视觉的空间数据,极大地提高了对活动断层微地貌形态与浅层结构进行快速调查与研究的精度和认识水平,也为更全面地认识和理解活断层的空间分布与变形特征、活动习性和多期古地震遗迹等提供重要的数据和方法支持。因此,对该方法的继续探索和完善,将显著提升和扩展其在活断层定量化和精细化研究中的实用性及应用前景。 相似文献
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王乐洋 《大地测量与地球动力学》2013,33(3):106-110
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以四川理县一地质滑坡为例,分析扫描点空间位置的理论精度,探讨点云数据获取以及点云过滤、点云拼接、地理参考等数据预处理的关键技术,给出一套比较直观、全面的滑坡形变分析方法,包括基于点云比较的形变分析、基于TIN比较的形变分析、基于特征点的形变分析以及基于DEM的形变分析。为了充分利用非地面点云数据,提出一种提取滑坡区域电线杆、树干的几何特征来分析滑坡水平变化的新方法。通过分析得到的滑坡形变量与GNSS远程实时监测结果基本一致。 相似文献