机载/地面海量点云数据组织与集成可视化方法研究
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摘要
机载和地面激光雷达(LiDAR)是一种新型的遥感测量系统,它可以快速获取地球表面及其上面各种目标的三维点云数据,从而生成数字表面模型、数字高程模型、三维构筑模型、数字树冠模型等。由于LiDAR获取地面三维数据的方法比传统的测量方法具有效率高和成本低等优点,目前正在城市、林业、交通、电力、水利等领域得到广泛应用。
在LiDAR数据处理与应用中,机载和地面激光雷达数据的管理与可视化是一个基础性研究问题,虽然前人做了大量的研究,但是机载和地面激光雷达数据的混合管理与大规模数据的可视化的问题仍然没有完全解决。在实际应用中,激光雷达数据往往需要与其它的空间数据配合使用,例如水利施工测量数据、道路施工测量数据和工程设计数据等。因此,激光雷达点云数据和其它工程测量数据、工程设计数据的集成与应用也是一个需要研究解决的问题。
本文以机载和地面激光雷达数据点云数据为基础,兼顾其它测量数据和工程设计数据,深入研究大规模机载和地面点云数据的组织与快速可视化方法。并在在此基础上,研究了基于虚拟地球平台的多种类空间数据的集成方法,及其点云数据在水利工程中的应用问题。本文的主要贡献和创新点如下：
(1)针对海量机载LiDAR点云数据,提出了四叉树和局部KD树相结合的混合空间索引结构,不仅在全局可以通过四叉树金字塔模型实现快速的检索调度,在局部也能够通过内存中构建的KD树实现高效的查询,既保证了点云数据的精度和密度,又提高了数据的调度效率,为大规模点云数据的可视化奠定了基础；
(2)针对真三维的地面点云数据,提出了基于面元拟合的三维R树索引方法,在对点云数据进行递归分割和面元拟合的过程中形成R树节点的包罗盒,通过对传统R树的改进,使之更好地保留平面特征,以更适合点云数据的管理。对于地面测量点云数据中的重要点特征和线特征数据,则采用了四叉树与三角网相结合的数据管理方法,较好地解决了数字地形模型、工程设计模型和工程施工测量动态模型可视化与分析问题；
(3)为了解决各种点云数据的集成与可视化问题,研究了多源点云数据的集成方法,提出了基于混合索引机制的机载点云数据与地面点云数据集成方法,以及与虚拟地球集成的方法,解决了多类型(机载激光雷达、地面激光雷达、GPS、全站仪等获取的数据)、多源(不同单位、不同厂家仪器获取的数据)、多区域、多文件点云数据在虚拟地球上的集成管理问题,并通过局部KD树索引和LoD方法实现了点云数据的快速可视化,为点云数据的广泛应用奠定了良好的方法与技术基础；
(4)基于虚拟地球平台GeoGlobe研发了机载和地面点云数据组织管理与集成显示模块,形成了点云数据管理与服务平台,实现了从虚拟地球到机载点云数据到地面点云数据的无缝浏览；依托作者本人主持的实际工程项目,研发了“两河口水电站施工测量数据采集及数据仓库建立和应用系统”,演示验证了本文提出的数据组织和管理方法,实例研究表明本文提出的方法不仅具有理论意义,而且具有实用价值。
LiDAR(Light detection and ranging) technology, including airborne and terrestrial laser scanning, is a new remote sensing technology for fast acquisition of accurate three dimensional spatial information of Earth's surface and other targets. The three-dimensional point cloud is an important data source of digital surface models, digital elevation model, three-dimensional building model reconstruction and forests estimation. Compared to traditional measuring technology, LiDAR technology has advantages of high efficacy and low cost. Thus, LIDAR is currently used in the digital city, forestry management, transportation line and power line detection, cultural heritage documentation and other area.
Point cloud management and visualization is a basic research question, which influence the following data processing and application significantly. In spite of many previous relate work, this problem has always been a challenge, especially for the terrestrial laser scanning data and combination with airborne data. In addition, the approach to manage other surveying point cloud data from construction projects is also an issue.
This paper focuses on the management of airborne and terrestrial laser scanning point cloud data at the beginning, then extend to other types of measuring data. Plus, the paper also pays a lot of attentions on the combination methods of multi-source data. Finally, the implementation system of virtual globe platform and the application in a hydraulic engineering project are briefly disused. The main contributions of this thesis are as follows:
1. Based on the analysis of multi-source point cloud data, we have proposed a pyramid data organization model of airborne LiDAR point cloud data. This pyramid model is a multi-resolution data structure which combines the global quadtree index with local KD-tree. We use quadtree index to organize the overall data, which construct the upper layers of the multi-resolution structure. However, we can't guarantee all the leaf nodes contain limited points and thus KD-tree is used to index the local region where the spatial distribution is uneven. This is the basis for large-scale visualization of point cloud data.
2. We have also proposed the multi-resolution data structure for terrestrial laser scanning point clouds and other surveying point cloud. The terrestrial laser scanning data is indexed by R-tree and plane features are also considered in the process of data partition, which is the most significant feature in TLS data sets. For other surveying point data, we build multi-resolution triangulation data structure to construct three dimensional models. The methods are useful for efficient rendering.
3. The above data structures are used to implement a LiDAR data management and display module in the virtual earth system-GeoGlobe, which is developed as a spatial information sharing platform by Wuhan University. The integration methods of airborne and terrestrial point cloud on virtual globe are discussed. Two different rendering approaches based on LoD are also described.
4. We examine the methods on virtual globe platform by airborne and terrestrial point cloud data in the City of Dunhuang(Gansu Province) and power line data in the City of Yichang(Hubei Province). The methods are also be used in a hydraulic engineering project.
在LiDAR数据处理与应用中,机载和地面激光雷达数据的管理与可视化是一个基础性研究问题,虽然前人做了大量的研究,但是机载和地面激光雷达数据的混合管理与大规模数据的可视化的问题仍然没有完全解决。在实际应用中,激光雷达数据往往需要与其它的空间数据配合使用,例如水利施工测量数据、道路施工测量数据和工程设计数据等。因此,激光雷达点云数据和其它工程测量数据、工程设计数据的集成与应用也是一个需要研究解决的问题。
本文以机载和地面激光雷达数据点云数据为基础,兼顾其它测量数据和工程设计数据,深入研究大规模机载和地面点云数据的组织与快速可视化方法。并在在此基础上,研究了基于虚拟地球平台的多种类空间数据的集成方法,及其点云数据在水利工程中的应用问题。本文的主要贡献和创新点如下：
(1)针对海量机载LiDAR点云数据,提出了四叉树和局部KD树相结合的混合空间索引结构,不仅在全局可以通过四叉树金字塔模型实现快速的检索调度,在局部也能够通过内存中构建的KD树实现高效的查询,既保证了点云数据的精度和密度,又提高了数据的调度效率,为大规模点云数据的可视化奠定了基础；
(2)针对真三维的地面点云数据,提出了基于面元拟合的三维R树索引方法,在对点云数据进行递归分割和面元拟合的过程中形成R树节点的包罗盒,通过对传统R树的改进,使之更好地保留平面特征,以更适合点云数据的管理。对于地面测量点云数据中的重要点特征和线特征数据,则采用了四叉树与三角网相结合的数据管理方法,较好地解决了数字地形模型、工程设计模型和工程施工测量动态模型可视化与分析问题；
(3)为了解决各种点云数据的集成与可视化问题,研究了多源点云数据的集成方法,提出了基于混合索引机制的机载点云数据与地面点云数据集成方法,以及与虚拟地球集成的方法,解决了多类型(机载激光雷达、地面激光雷达、GPS、全站仪等获取的数据)、多源(不同单位、不同厂家仪器获取的数据)、多区域、多文件点云数据在虚拟地球上的集成管理问题,并通过局部KD树索引和LoD方法实现了点云数据的快速可视化,为点云数据的广泛应用奠定了良好的方法与技术基础；
(4)基于虚拟地球平台GeoGlobe研发了机载和地面点云数据组织管理与集成显示模块,形成了点云数据管理与服务平台,实现了从虚拟地球到机载点云数据到地面点云数据的无缝浏览；依托作者本人主持的实际工程项目,研发了“两河口水电站施工测量数据采集及数据仓库建立和应用系统”,演示验证了本文提出的数据组织和管理方法,实例研究表明本文提出的方法不仅具有理论意义,而且具有实用价值。
LiDAR(Light detection and ranging) technology, including airborne and terrestrial laser scanning, is a new remote sensing technology for fast acquisition of accurate three dimensional spatial information of Earth's surface and other targets. The three-dimensional point cloud is an important data source of digital surface models, digital elevation model, three-dimensional building model reconstruction and forests estimation. Compared to traditional measuring technology, LiDAR technology has advantages of high efficacy and low cost. Thus, LIDAR is currently used in the digital city, forestry management, transportation line and power line detection, cultural heritage documentation and other area.
Point cloud management and visualization is a basic research question, which influence the following data processing and application significantly. In spite of many previous relate work, this problem has always been a challenge, especially for the terrestrial laser scanning data and combination with airborne data. In addition, the approach to manage other surveying point cloud data from construction projects is also an issue.
This paper focuses on the management of airborne and terrestrial laser scanning point cloud data at the beginning, then extend to other types of measuring data. Plus, the paper also pays a lot of attentions on the combination methods of multi-source data. Finally, the implementation system of virtual globe platform and the application in a hydraulic engineering project are briefly disused. The main contributions of this thesis are as follows:
1. Based on the analysis of multi-source point cloud data, we have proposed a pyramid data organization model of airborne LiDAR point cloud data. This pyramid model is a multi-resolution data structure which combines the global quadtree index with local KD-tree. We use quadtree index to organize the overall data, which construct the upper layers of the multi-resolution structure. However, we can't guarantee all the leaf nodes contain limited points and thus KD-tree is used to index the local region where the spatial distribution is uneven. This is the basis for large-scale visualization of point cloud data.
2. We have also proposed the multi-resolution data structure for terrestrial laser scanning point clouds and other surveying point cloud. The terrestrial laser scanning data is indexed by R-tree and plane features are also considered in the process of data partition, which is the most significant feature in TLS data sets. For other surveying point data, we build multi-resolution triangulation data structure to construct three dimensional models. The methods are useful for efficient rendering.
3. The above data structures are used to implement a LiDAR data management and display module in the virtual earth system-GeoGlobe, which is developed as a spatial information sharing platform by Wuhan University. The integration methods of airborne and terrestrial point cloud on virtual globe are discussed. Two different rendering approaches based on LoD are also described.
4. We examine the methods on virtual globe platform by airborne and terrestrial point cloud data in the City of Dunhuang(Gansu Province) and power line data in the City of Yichang(Hubei Province). The methods are also be used in a hydraulic engineering project.
引文
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邱航and陈雷霆(2009).”基于点的计算机图形学研究与进展.”计算机科学36(006)：10-15.
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路明月and何永健(2008).”三维海量点云数据的组织与索引方法.”地球信息科学10(002)：190-194.
蔡占川,梁延研,et al.(2010).”基于嫦娥一号卫星激光测高数据的月球数字高程模型.”地球物理学进展25(4)：1153-1160.
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刘艳丰(2009).基于kd-tree的点云数据空间管理理论与方法.中南大学硕士论文
刘艳丰,王守彬,et al.(2009).”基于kd树的机载LIDAR点云滤波处理.”测绘工程18(005)：59-62.
张明波,陆.,申排伟,程昌秀(2005).R树家族的演变和发展.计算机学报,2005年第3期
张齐勇(2009).”城区LiDAR点云的树木提取.”西南交通大学硕士学位论文
杨玲(2009).”顾及矢量特征的机载LiDAR点云数据压缩方法.”地理与地理信息科学25(4).
黄先锋(2006).利用机载LIDAR数据重建3D建筑物模型的关键技术研究.测绘遥感信息工程国家重点实验室.武汉,武汉大学.博士：144.
黄先锋,陶闯,et al.(2005).”机载激光雷达点云数据的实时渲染.”武汉大学学报：信息科学版30(011)：975-978.
钟良,马洪超,管海燕,刘鹏飞.利用安置角检校进行机载LiDAR点云数据与同步影像快速配准.武汉大学学报(信息科学版)2011年第09期
龚健雅(1993).整体SIS的数据组织,武汉测绘科技大学出版社
龚健雅(1999).当代GIS的若干理论与技术,武汉测绘科技大学出版社.
龚健雅(2001).地理信息系统基础,科学出版社.
龚健雅,刘学军(2001).约束数据域的Delaunay三角剖分与修改算法.测绘学报,2001年第1期.
庞勇,赵峰,李增元,周淑芳,邓广,刘清旺.机载激光雷达平均树高提取研究.遥感学报,2008年第1期