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随着以激光扫描、倾斜摄影为主的各种现实采集(reality capture)装备的快速发展,点云已成为继矢量地图和影像数据之后的第三类重要的时空数据源,并在地球科学、空间认知、智慧城市等科学研究和工程建设中发挥越来越重要的作用。如何从点云大数据中快速、准确获取精准有效的三维地理信息成为测绘地理信息领域的科学前沿和地学应用研究的迫切需求,也是三维地理信息获取与建模面临的重大难题。点云智能应运而生,并成为突破上述难题的科学途径。本文围绕点云智能中的三个重要方向:点云大数据处理的理论方法,点云大数据智能处理关键技术和重大工程应用,阐述点云采集装备、智能化处理,以及科学研究与工程应用的最新进展,最后对点云智能的重要发展方向趋势予以展望,希望为点云研究相关人员提供科学参考。 相似文献
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三维激光扫描技术由于可快速获取高精度、高密度点云数据,可将拟验收建筑及周边情况几乎完全无差地复制到电脑中,是规划验收测量特别是复杂建筑规划验收测量的理想方法,但是其数据处理一直是影响甚至制约其应用的瓶颈。本文简述了规划验收测量要点,以及三维激光扫描点云数据初步处理流程,并针对制作规划验收测量各类图件的不同需求,提出了分别通过直接取线、切片、投影等方法制作成果图件的工作思路及各方法的特点。但是还需研究和解决海量点云的数据处理,以及根据验收测量特点获得测量成果图件的问题。 相似文献
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三维激光扫描技术具有速度快、精度高、自动化程度高并且不与物体直接接触等诸多优点,现已应用于古建筑保护、数字城市、工业生产、地形测绘等不同领域。本文利用地面三维激光扫描仪对校内樱花园手形建筑物进行扫描,获取该目标物的点云数据,并对获取的点云数据进行拼接、去噪处理。同时,利用点云数据处理软件Geomagic对目标物进行快速的三维模型重建并达到了预期的效果。 相似文献
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郭海乐 《测绘与空间地理信息》2023,(12):199-201+204
以某建筑物为例,进行三维激光扫描,研究三维激光扫描的系统组成与其工作原理、特点,采集建筑物点云数据,处理建筑物点云数据等数据处理方法,分析建筑物三维建模的方法,重建建筑物模型。 相似文献
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研究了在Geomagic环境中通过三维点云数据重建三维实体模型的过程,详细介绍了复杂实体点云数据在Geomagic中点云数据处理的全过程,包括点云匹配、点云预处理、封装形成三角面、在多边形阶段破洞修补以及优化处理,最终生成了NURBS曲面。三维重建过程表明,在Geomagic中重建三维模型不仅效率高、精度高,而且软件易于操作。本文涉及的数据处理方法也可以用于三维激光扫描技术在数字矿山、数字城市中应用。 相似文献
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点云数据直接缩减方法及缩减效果研究 总被引：1，自引：0，他引：1
分析了国外点云数据处理中数据缩减方法的研究现状,针对实际工程中三维激光扫描数据采集的过密情况,提出利用扫描间隔进行点云数据直接缩减的方法,并编程实现所提出的算法。通过对真实的三维激光扫描点云数据的缩减处理,建立点云数据直接缩减的预测模型。 相似文献
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针对运营隧道检测无全球导航卫星系统(GNSS)信号，移动激光扫描难以获取绝对坐标系下三维点云数据的问题，该文提出一种顾及靶标控制的高精度隧道移动扫描方法。并将三维激光扫描仪、惯导、里程计、倾角仪集成为自移动三维激光扫描系统，利用倾角仪静态测量姿态角约束惯导数据，结合控制点坐标纠正测量线路轨迹，生成绝对坐标系下的三维点云数据。通过与组合导航对比以及现场实验验证，该方法绝对定位点位偏差可以控制在0.06 m以内。研究方法解决了隧道场景绝对定位难题，有效避免了由于卫星信号遮挡隧道移动扫描点云明显变形和误差急剧变大等情况，为轨道交通隧道三维显示、病害检测等后续分析提供了良好的数据支撑。 相似文献
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胡超伦 《测绘与空间地理信息》2017,(8)
三维激光扫描技术相对于传统的数据采集方式具有更高精度、远距离获取等优势。本文介绍了三维激光扫描技术的工作原理,并结合地质剖面分析了点云数据的采集以及获取的流程,结合生成的地质剖面模型讨论了点云数据在地质剖面分析方面的优势以及存在的问题。 相似文献
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为了进行平地区域原基础测绘产品高程的更新,我省进行了针对平地区域的机载LiDAR测高项目,为了获取高精度的DSM和DEM成果,在实际生产中开展了机载LiDAR数据处理及DEM成果的制作方法研究。本文将利用TerraSolid软件,从LiDAR点云数据的高程精度控制、点云滤波分类要求和如何利用特征线进行无点云数据区域的DEM精度控制等关键技术方面进行研究。 相似文献
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Semantic labelling of LiDAR point cloud is critical for effective utilization of 3D points in numerous applications. 3D segmentation, incorporation of ancillary data, feature extraction and classification are the key stages in object-based point cloud labelling. The choice of algorithms and tuning parameters adopted in these stages has substantial impact on the quality of results from object-based point cloud labelling. This paper critically evaluates the performance of object-based point cloud labelling as a function of different 3D segmentation approaches, incorporation of spectral data and computational complexity of the point cloud. The designed experiments are implemented on the datasets provided by the ISPRS and the results are independently validated by the ISPRS. Results indicate that aggregation of dense point cloud into higher-level object analogue (e.g. supervoxels) before 3D segmentation stage offers superior labelling results and best computational performance compared to the popular surface growing-based approaches. 相似文献
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《International Journal of Digital Earth》2013,6(1):13-53
ABSTRACTBig Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers – Big Data and cloud computing – and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications. 相似文献
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The development of robust and accurate methods for automatic registration of optical imagery and 3D LiDAR data continues to be a challenge for a variety of applications in photogrammetry, computer vision and remote sensing. This paper proposes a new approach for the registration of optical imagery with LiDAR data based on the theory of Mutual Information (MI), which exploits the statistical dependency between same- and multi-modal datasets to achieve accurate registration. The MI-based similarity measures quantify dependencies between aerial imagery, and both LiDAR intensity data and 3D point cloud data. The needs for specific physical feature correspondences, which are not always attainable in the registration of imagery with 3D point clouds, are avoided. Current methods for registering 2D imagery to 3D point clouds are first reviewed, after which the mutual MI approach is presented. Particular attention is given to adoption of the Normalised Combined Mutual Information (NCMI) approach as a means to produce a similarity measure that exploits the inherently registered LiDAR intensity and point cloud data so as to improve the robustness of registration between optical imagery and LiDAR data. The effectiveness of local versus global similarity measures is also investigated, as are the transformation models involved in the registration process. An experimental program conducted to evaluate MI-based methods for registering aerial imagery to LiDAR data is reported and the results obtained in two areas with differing terrain and land cover, and with aerial imagery of different resolution and LiDAR data with different point density are discussed. These results demonstrate the potential of the MI and especially the CMI methods for registration of imagery and 3D point clouds, and they highlight the feasibility and robustness of the presented MI-based approach to automated registration of multi-sensor, multi-temporal and multi-resolution remote sensing data for a wide range of applications. 相似文献
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Volkan Yilmaz Berkant Konakoglu Cigdem Serifoglu Oguz Gungor Ertan Gökalp 《国际地球制图》2018,33(3):310-320
With the advent of unmanned aerial vehicles (UAVs) for mapping applications, it is possible to generate 3D dense point clouds using stereo images. This technology, however, has some disadvantages when compared to Light Detection and Ranging (LiDAR) system. Unlike LiDAR, digital cameras mounted on UAVs are incapable of viewing beneath the canopy, which leads to sparse points on the bare earth surface. In such cases, it is more challenging to remove points belonging to above-ground objects using ground filtering algorithms generated especially for LiDAR data. To tackle this problem, a methodology employing supervised image classification for filtering 3D point clouds is proposed in this study. A classified image is overlapped with the point cloud to determine the ground points to be used for digital elevation model (DEM) generation. Quantitative evaluation results showed that filtering the point cloud with this methodology has a good potential for high-resolution DEM generation. 相似文献
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谭金石 《测绘与空间地理信息》2015,(6):81-83
机载LiDAR作为一种新兴的对地观测技术,能够快速地获取地表三维信息。如何从海量LiDAR点云数据中提取建筑物是数据处理中的一项关键工作。本文结合LiDAR数据和航空影像的数据特点,提出了一种航空影像辅助的LiDAR点云建筑物提取方法,首先,采用面向对象方法从航空影像中提取建筑物的轮廓;然后,以建筑轮廓信息为参考,从LiDAR点云中提取建筑物的点云数据;最后,通过实验证明该方法的有效性与可行性。 相似文献
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机载激光雷达（LiDAR）是近10年出现的高新技术之一,能迅速获取密集的地面3维数据,并广泛应用于各个领域。本文主要介绍了我院通过试验,获取及处理ALS70机栽激光雷达点云数据的方法。 相似文献
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The topographic mapping products of airborne light detection and ranging (LiDAR) are usually required in the national coordinates (i.e., using the national datum and a conformal map projection). Since the spatial scale of the national datum is usually slightly different from the World Geodetic System 1984 (WGS 84) datum, and the map projection frame is not Cartesian, the georeferencing process in the national coordinates is inevitably affected by various geometric distortions. In this paper, all the major direct georeferencing distortion factors in the national coordinates, including one 3D scale distortion (the datum scale factor distortion), one height distortion (the earth curvature distortion), two length distortions (the horizontal-to-geodesic length distortion and the geodesic-to-projected length distortion), and three angle distortions (the skew-normal distortion, the normal-section-to-geodesic distortion, and the arc-to-chord distortion) are identified and demonstrated in detail; and high-precision map projection correction formulas are provided for the direct georeferencing of the airborne LiDAR data. Given the high computational complexity of the high-precision map projection correction approach, some more approximate correction formulas are also derived for the practical calculations. The simulated experiments show that the magnitude of the datum scale distortion can reach several centimeters to decimeters for the low (e.g., 500 m) and high (e.g., 8000 m) flying heights, and therefore it always needs to be corrected. Our proposed practical map projection correction approach has better accuracy than Legat’s approach,1 but it needs 25% more computational cost. As the correction accuracy of Legat’s approach can meet the requirements of airborne LiDAR data with low and medium flight height (up to 3000 m above ground), our practical correction approach is more suitable to the high-altitude aerial imagery. The residuals of our proposed high-precision map projection correction approach are trivial even for the high flight height of 8000 m. It can be used for the theoretical applications such as the accurate evaluation of different GPS/INS attitude transformation methods to the national coordinates. 相似文献
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Oscar Martinez-Rubi Maurice de Kleijn Stefan Verhoeven Niels Drost Jisk Attema Maarten van Meersbergen 《International Journal of Digital Earth》2016,9(12):1135-1152
This article discusses the use of 3D technologies in digital earth applications (DEAs) to study complex sites. These are large areas containing objects with heterogeneous shapes and semantic information. The study proposes that DEAs should be modular, have multi-tier architectures, and be developed as Free and Open Source Software if possible. In DEAs requiring high reliability in the 3D measurements, point clouds are proposed as basis for the 3D Digital digital earth representation. For the development of DEAs, we propose to follow a workflow with four components: data acquisition and processing, data management, data analysis and data visualization. For every component, technological challenges of using 3D technologies are identified and solutions applied for a case study are presented. The case study is a modular 3D DEA developed for the archaeological project Mapping the Via Appia. The 3D DEA allows archaeologists to virtually analyze a complex study area. 相似文献