基于机载和车载LiDAR集成的公路多视角三维可视化方法

随着越来越多的公路投入到运营、养护和管理,公路信息化运营管理需要建立全可视化、高精度的数字公路平台。本文提出了机载和车载三维激光扫描技术集成的公路快速三维可视化方法,研究了机载和车载LiDAR快速获取公路多尺度三维地形技术流程,提出了基于机载LiDAR建立的公路高精度数字表面模型、高分辨率正射影像和车载LiDAR获取的可量测360度全景影像搭建数字公路空地一体的三维可视化平台的方法。以广梧高速公路三维可视化平台为例,开展基于机载和车载LiDAR集成公路快速三维可视化实践,表明本文提出的方法的有效性和广泛的应用前景。     

轻型机载激光雷达航测在公路勘测设计中的工程应用实践

以载人直升机这一轻型平台为飞行载体,轻型机载激光雷达航测集成激光扫描、摄影测量、GPS、惯性导航等技术,可直接获取地表三维空间数据,快速生成数字高程模型、数字正射影像、数字线划图等测绘产品,并在已有的数字高程模型基础上实现高精度中桩横断面提取。轻型机载激光雷达航测不需要运12等大型固定翼飞行平台,起降场地灵活,可快速生成基础测绘产品,制作的数字高程模型高程精度高,可支撑面向高精度中桩横断面提取的设计线路动态选线,实现了初勘定测一体化,在高速公路勘测设计领域具有广泛的市场推广价值。     

LiDAR点的精度检验

LiDAR机载激光扫描测高或激光雷达(LiDAR)是一种安装在飞机上的机载激光探测和测距系统,可以量测地面物体的三维坐标,在三维地理空间信息的数据采集方面有广阔的发展前景和应用需求。本文介绍了LiDAR测量技术的优越性及其应用,提出了LiDAR点精度的检验方法,并运用实例对加拿大OPTECH公司的ALTM3100系统的Li-DAR点的高程、平面精度进行内符合、外符合检验,并提出了提高LiDAR点精度的方法。     

无人机载LiDAR在水利工程测量中的应用探究

机载激光雷达航测(LiDAR)是集成激光扫描、摄影测量、全球定位系统(GPS)、惯性导航系统(IMU)等测绘高新技术的数据采集技术,能够直接得到高精度的三维坐标信息。相比传统航测技术,有其突出特点和优势,介绍了该技术在水利工程测量中的应用,对比探究了其长处与缺点,并对其未来的应用方向作了分析和憧憬。     

基于机载LiDAR技术的高速公路勘测方法研究

结合新泰至台儿庄高速公路勘察设计项目,对机载LiDAR技术数据获取、数据处理及在高速公路勘测中的应用进行了详细的研究,成功完成了线路的地形图、数字高程模型、纵横断面的制作,并对其进行了精度分析,论证了机载LiDAR技术在高速公路勘测中的可行性。     

基于机载LiDAR数据测绘大比例尺地形图的研究与应用——以山地城市为例

传统大范围的大比例尺地形图测制多采用航测的方法,但基于航摄影像匹配的航测方法本身存在着一定的局限性,机载Li DAR通过激光回波获取信息,激光具有一定的穿透性,在植被覆盖的区域也能获取一定数量的地面反射激光点;激光点云本身记录了三维坐标信息,各种物体顶部的激光点不存在投影差的问题,Li DAR数据的特点正好能弥补航摄影像的不足之处。本文通过研究基于机载Li DAR数据配合高分辨率数字正射影像在山地城市测制大比例尺地形图,探索出一套生产方法流程,以重庆测区为例,分析了该方法的可行性并对测图成果精度进行了系统性分析,结果表明,本试验中要素精度和DEM精度可以达到1∶2 000的测图要求。     

消费级无人机摄影测量大比例尺地形图测绘方法研究

无人机以其机动灵活、实时性强、低成本等优势,迅速成为快速获取地理数据的有效平台。以防灾科技学院为例,通过小型多旋翼高精度航测无人机,辅助RTK技术获取高重叠度影像,利用摄影测量软件生成数字正射影像(DOM)和数字表面模型(DSM),基于三维立体测图系统实现地形图要素的提取,结果表明,该技术方案能够满足1∶500数字地形图测绘的需要,极大地提高了制图效率。     

机载LiDAR航空摄影测量在三维建模中的应用分析

结合广东云浮西江新城三维模型、数字高程模型制作项目的实际情况,通过机载LiDAR技术与倾斜摄影测量技术相结合的方式,通过应用流程、地面建模、建筑物建模、模型整合4方面对机载LiDAR航空摄影测量在三维建筑中的应用进行分析。     

数字化测绘技术在工程测量中的应用

文章对数字化测绘技术的优越性进行了分析,简述了数字化测绘技术常用的作业模式,对地面数字测图、原图数字化、航测数字成图等常用的数字测图技术、地籍测量中的数字测图技术以及数字地球中的数字化测绘技术进行了具体的探讨与分析。     

基于PPK的机载LiDAR在大比例尺地形图测绘中的应用

传统全站仪加RTK测图方式人工量大且效率低下,受通视条件和GPS信号弱的影响,较难获取植被深厚茂密地区的地形地貌数据;而搭载相机的机载激光扫描仪可以穿透部分植被,快速主动获取海量点云数据和原始影像,经过后处理可以快速获取DEM、DOM数据。本文通过重庆某地区大比例尺地形图测绘项目,介绍基于PPK的机载LiDAR测量技术进行大比例尺地形图测量的作业流程,经检查点精度验证,表明基于PPK的机载LiDAR测量技术能满足丘陵山区(植被茂密)大比例尺地形图测绘精度要求,相比传统测量方式具有精度和效率方面的优势。     

公路沿线不良地质现象勘测技术研究

从公路沿线不良地质研究背景及意义出发,对RS技术、机载LiDAR技术的特点及不良地质勘测的工作流程进行了详细论述,并重点分析RS技术和机载LiDAR技术的应用特点,以期为勘测人员选择提供依据。     

基于LiDAR点云的城区地表变化检测

随着摄影测量与遥感对地观测技术的快速发展,数据获取与生产越来越简单,快速准确的变化检测得到变化率和变化图斑,对于维护数据时效性有重要意义.本文通过实验总结出了一种采用两期机载LiDAR点云数据,快速检测城区地表变化的技术方法:首先对机载LiDAR点云进行坐标转换配准等数据预处理后,先将数据分类,然后利用分层聚类差值法进...     

移动激光扫描测量系统在海岛海岸带测量中的应用

以海岛海岸带为研究对象,对移动激光扫描测量系统的原理、组成、优势和关键技术进行了分析,对机载和船载移动激光扫描测量在海岛海岸带测量中的技术流程、应用方法及注意事项进行了探讨,并对其当前的发展进行了初步总结,对其未来良好的应用前景进行了展望。     

山猫(Lynx)车载激光移动测量系统精度分析

利用山猫(Lynx)车载激光移动测量系统采集了5条实验路段的激光点云数据,通过数据联合解算,采用不同间距的检校点纠正方案,得出了有益的结论:车载激光移动测量系统沿带状线路进行测量时,对沿线GPS基站的要求较高,数据采集位置距基站的平均距离不应大于系统的标称值,超过标称基站距离的激光点云高程精度将大幅下降。要提高激光点云的位置精度,可布设检校点对激光点云进行纠正,应根据不同的成图精度选择不同间距的检校点布设方案。     

三维激光扫描灰度信息在结构变形场计算中的应用

非接触测量技术是结构测量领域的最新进展之一，这类测量方法无需在被测对象上安装传感器，因而在结构试验以及土木工程现场实测中具有一定的优势。三维激光扫描作为一种非接触测量新技术，可以直接获取目标物表面点密集的三维坐标和灰度值，受测试环境干扰小，因而在土木工程领域的应用日益受到关注。在激光扫描技术的基础上，提出一种同名点的匹配方法，以提高变形场计算的精度。这种方法利用激光扫描的灰度信息，对扫描得到的点云坐标和灰度数据进行像素化处理，然后用相关系数法确定同名点并计算位移场。通过一钢梁试验对该方法进行验证，将结果与导杆位移计以及有限元分析的结果作了比对，结果显示该方法可以提高同名点识别的精度，进而提高结构变形计算的准确性，且可以同时获得构件包括平面内和平面外的变形。     

多源数据模型下大比例尺地形测图精度分析与研究

以小区域光伏电站大比例尺地形测图为研究背景,将无人机倾斜摄影测量和轻型机载LiDAR作为数据来源,分别进行大比例尺地形图生产,分析了作业过程中的关键方法,并将成果与人工实测数据进行精度对比,实验结果表明利用无人机倾斜摄影测量与轻型机载LiDAR技术,完全能生产满足规范精度要求的大比例尺地形图,有效破解了在多植被山区无法高效获取高精度地形要素的难题。     

Development of an elliptical fitting algorithm to improve change detection capabilities with applications for deformation monitoring in circular tunnels and shafts

Terrestrial laser scanning, also known as Light Detection and Ranging (LiDAR) is an emerging technology that has many proven uses in the geotechnical engineering community including rockmass characterization, discontinuity measurement and landslide monitoring. One of the newer applications of LiDAR scanning is deformation monitoring and change detection. In tunnels, deformation is traditionally measured using a series of five or more control points installed around the diameter of the tunnel with measurements recorded at regular time intervals. LiDAR provides the ability to obtain a more complete characterization of the tunnel surface, allowing for determination of the mechanism and magnitude of tunnel deformation, as the entire surface of the tunnel is being modeled rather than a fixed set of points. This paper discusses terrestrial LiDAR scanning for deformation mapping of a surface and for cross-sectional closure measurements within an active tunnel using an elliptical fit to data for profile analysis. The methods were found to be accurate to within a few millimeters when measuring 58 mm of diametric difference over an 18.3 m diameter circular profile, even when some sections of the data were removed from the analysis.     

Mapping of the water quality of Lake Erken, Sweden, from imaging spectrometry and Landsat Thematic Mapper

Hyperspectral data have been collected by the Compact Airborne Spectrographic Imager (CASI) and multispectral data by the Landsat Thematic Mapper (TM) instrument for the purpose of mapping lake water quality. Field campaigns have been performed on Lake Erken in Sweden during the summer of 1997. Water samples have been collected and analysed in laboratory. Continuously measured variables from a boat have added a spatial dimension to the ground truth dataset. The data have been used to construct algorithms, based on remotely sensed data, for the retrieval of water quality parameters. The correlation between the continuous data and the collected CASI data has been investigated. Algorithms using both the point sampling results and the continuous data have been developed. Maps based on data from each instrument, showing the distribution of chlorophyll, are presented. Problems of having few water sampling stations, and the potential of using sub-water optics models are addressed as well. Tests were performed on MERIS bands and found useful for mapping chlorophyll and turbidity, and algorithms have been suggested for future use with MERIS.     

Monitoring tunnel deformations by means of multi-epoch dispersed 3D LiDAR point clouds: An improved approach

Monitoring tunnel deformations is a crucial task when evaluating tunnel stability and safety. This task requires an accurate and high-resolution spatial technique to precisely capture the meticulous anomalies on a tunnel surface. As a response, the light detection and ranging (LiDAR) technique, which collects detailed spatial data in a fast and automatic manner, was recently proposed by Han et al. (2013) for monitoring the deformation of a 2D tunnel profile. Although the proposed approach successfully uses this modern spatial technique in tunnel analysis, the benefits of the 3D LiDAR technique have not been fully exposed. This study improved the technique as a real 3D approach. The associated uncertainties can be reduced by avoiding the 3D to 2D profile projection step. The minimum-distance projection (MDP) was then estimated using directly the 3D dispersed point clouds so that any deformation signal (point displacement) along the entire tunnel surface can be immediately identified. Furthermore, a rigorous covariance propagation approach was introduced to provide explicit quality indications on the obtained solution. The results of simulation tests and a real case study of a highway tunnel showed that the spatial implications of the 3D LiDAR technique can be fully explored by implementing the improved approach. Consequently, a more accurate and comprehensive solution for monitoring tunnel deformations can be achieved.     

Improved Floodplain Delineation Method Using High‐Density LiDAR Data

Abstract: With the improvements in sensor technologies over the past decade, there has been a significant decrease in the cost of acquisition and increase in the density and accuracy of Light Detection and Ranging (LiDAR) data. Due to its advantages over traditional surveying techniques, LiDAR data are widely preferred for floodplain delineation. But, processing dense LiDAR data is time‐consuming and memory intense. Therefore, it is divided into manageable areas/tiles or simplified to raster DEM (Digital Elevation Model) format for feature extraction process such as floodplain delineation. This results in increase in processing time and decrease in accuracy due to loss of true elevation. Furthermore, as floodplain boundaries are unknown prior to delineation, processing time also increases as LiDAR data over larger extent is processed. Hence, there is a need of improved, automated method that will process only the LiDAR data that contribute to the floodplain. This article, describes a time‐efficient floodplain delineation method that divides the LiDAR data into regular tiles and processes only the tiles that contribute to floodplain. This method is experimented using LiDAR data saved in ArcGIS “Terrain” format at 0.0, 0.1, and 0.3 m pyramid levels. These data are then preprocessed to obtain elevation information which is used to filter and process only LiDAR data tiles that truly contribute to the floodplain boundary; thus, reducing processing time. Results from two pilot hydraulic models showed that this method saved 12–34% of processing time compared to the conventional method.