Mobile Lidar System Research Articles

Metrological evaluation of vessel-based mobile lidar for survey of coastal structures

Surveying of coastal structures is necessary to ensure that the structures are in good operating condition. Mobile lidar systems could be installed on vessels to monitor the coastal structures, eve...

Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds

This paper proposes a novel algorithm for extracting street light poles from vehicleborne mobile light detection and ranging (LiDAR) point-clouds. First, the algorithm rapidly detects curb-lines and segments a point-cloud into road and nonroad surface points based on trajectory data recorded by the integrated position and orientation system onboard the vehicle. Second, the algorithm accurately extracts street light poles from the segmented nonroad surface points using a novel pairwise 3-D shape context. The proposed algorithm is tested on a set of point-clouds acquired by a RIEGL VMX-450 mobile LiDAR system. The results show that road surfaces are correctly segmented, and street light poles are robustly extracted with a completeness exceeding 99%, a correctness exceeding 97%, and a quality exceeding 96%, thereby demonstrating the efficiency and feasibility of the proposed algorithm to segment road surfaces and extract street light poles from huge volumes of mobile LiDAR point-clouds.

A new mobile and portable scanning lidar for profiling the lower troposphere

Abstract. An in-house developed mobile and portable three-dimensional scanning lidar system is discussed in this work. The system uses a stimulated Raman-scattering technique for the continuous observation of atmospheric aerosols, clouds and trace gases. This system has a fast scanning technique with a high-speed data acquisition, and permits the real-time measurement of atmospheric pollutants with the temporal resolution of 1 min. This scanning lidar system provides typical horizontal coverage of about 8–10 km while scanning; however, in zenith mode, good quality backscattered signals can be from 20 km, depending upon the laser power and sky conditions. This versatile lidar system has also overcome the drawbacks which are popular in the traditional scanning lidar systems such as complicated operation, overlap height between laser beam and telescope field of view In this system, the optical damage is reduced by using an integral coaxial transmitter and receiver. Some of the initial results obtained from the scanning lidar system are also presented. This study shows that boundary-layer structure and land–sea breeze circulation can be resolved from the developed scanning lidar system. The application of this lidar system to measure the pollutants over an industrial area is also discussed.

Setting up a mobile Lidar (DIAL) system for detecting chemical warfare agents

The mobile light detection and ranging DIAL system of Malek Ashtar University of Technology has been developed for the detection of chemical warfare agents whose absorption wavelengths are in the range of 9.2–10.8 μm tunable CO2 lasers of the system. In this paper, this system is first described and then ammonia detection is analyzed experimentally. Also, experimental results of detecting a sarin agent simulant, dimethyl–methyl phosphonate (DMMP), are presented. The power levels received from different ranges to detect specific concentrations of NH3 and DMMP have been measured and debated. The primary test results with a 150 ns clipped pulse width by passive pinhole plasma shutter indicate that the system is capable of monitoring several species of pollutants in the range of about 1 km, with a 20 m spatial and 2 min temporal resolution.

Rail Sensor: A Mobile Lidar System for 3D Archiving the Bas-reliefs in Angkor Wat

This paper presents a mobile Lidar system for efficiently and accurately capturing the 3D shape of the Bas-reliefs in Angkor Wat. The sensor system consists of two main components: 1) a panoramic camera and 2) a 2D 360-degree laser line scanner, which moves slowly on the rails parallel to the reliefs. In this paper, we first propose a new but simple method to accurately calibrate the panoramic camera to the 2D laser scan lines. Then the sensor motion can be estimated from the sensor-fused system using the 2D/3D features tracking method. Furthermore, to reduce the drifting error of sensor motion we adopt bundle adjustment to globally optimize and smooth the moving trajectories. In experiments, we demonstrate that our moving Lidar system achieves substantially better performance for accuracy and efficiency in comparison to the traditional stop-and-go methods.

Surface-Based Registration of Airborne and Terrestrial Mobile LiDAR Point Clouds

Light Detection and Ranging (LiDAR) is an active sensor that can effectively acquire a large number of three-dimensional (3-D) points. LiDAR systems can be equipped on different platforms for different applications, but to integrate the data, point cloud registration is needed to improve geometric consistency. The registration of airborne and terrestrial mobile LiDAR is a challenging task because the point densities and scanning directions differ. We proposed a scheme for the registration of airborne and terrestrial mobile LiDAR using the least squares 3-D surface registration technique to minimize the surfaces between two datasets. To analyze the effect of point density in registration, the simulation data simulated different conditions and estimated the theoretical errors. The test data were the point clouds of the airborne LiDAR system (ALS) and the mobile LiDAR system (MLS), which were acquired by Optech ALTM 3070 and Lynx, respectively. The resulting simulation analysis indicated that the accuracy of registration improved as the density increased. For the test dataset, the registration error of mobile LiDAR between different trajectories improved from 40 cm to 4 cm, and the registration error between ALS and MLS improved from 84 cm to 4 cm. These results indicate that the proposed methods can obtain 5 cm accuracy between ALS and MLS.

Semiautomatic Extraction of Road Horizontal Alignment from a Mobile LiDAR System

AbstractThis article proposes a method to semiautomatically extract the road axis through a mobile LiDAR system, a recent popular technology for transportation‐related applications, road estimation and even to enhance driver safety. In particular, the approach developed has two components: (1) the feature extraction from LiDAR data to model the road axis, and (2) the estimation of the horizontal alignment that meets the requirements and practice for a transportation authority. Given the massive and complex character of the data captured by the system, a hierarchical (coarse‐to‐fine) and robust strategy based on segmentation, parameterization and filtering, which determine the road centerline together with the geometric elements that compose its horizontal alignment, such as straight lines, circular arcs, and clothoids, has been developed and implemented. Test results using a simulated and a real data are discussed and validated. The experimental results obtained with real cases guarantying relative accuracies under 2%, being a useful approach to produce accurate estimations of the horizontal geometric features of the road alignment.

An automated approach to vertical road characterisation using mobile LiDAR systems: Longitudinal profiles and cross-sections

The characterisation the vertical profiles and cross-sections of roads is important for the verification of proper construction and road safety assessment. The goal of this paper is the extraction of geometric parameters through the automatic processing of mobile LiDAR system (MLS) point clouds. Massive and complex datasets provided by the MLS are processed using a hierarchical strategy that includes segmentation, principal component analysis (PCA)-based orthogonal regression, filtering and parameter extraction procedures. Best-fit geometric parameters act as a vertical road model for both linear parameters (slope and vertical curves) and cross-sections (superelevations). The proposed automatic processing approach gives satisfactory results for the analysed scenario.

Geometric Modelling of Octagonal Lamp Poles

Abstract. Lamp poles are one of the most abundant highway and community components in modern cities. Their supporting parts are primarily tapered octagonal cones specifically designed for wind resistance. The geometry and the positions of the lamp poles are important information for various applications. For example, they are important to monitoring deformation of aged lamp poles, maintaining an efficient highway GIS system, and also facilitating possible feature-based calibration of mobile LiDAR systems. In this paper, we present a novel geometric model for octagonal lamp poles. The model consists of seven parameters in which a rotation about the z-axis is included, and points are constrained by the trigonometric property of 2D octagons after applying the rotations. For the geometric fitting of the lamp pole point cloud captured by a terrestrial LiDAR, accurate initial parameter values are essential. They can be estimated by first fitting the points to a circular cone model and this is followed by some basic point cloud processing techniques. The model was verified by fitting both simulated and real data. The real data includes several lamp pole point clouds captured by: (1) Faro Focus 3D and (2) Velodyne HDL-32E. The fitting results using the proposed model are promising, and up to 2.9 mm improvement in fitting accuracy was realized for the real lamp pole point clouds compared to using the conventional circular cone model. The overall result suggests that the proposed model is appropriate and rigorous.

Automatic filtering of vehicles from mobile LiDAR datasets

This manuscript presents a new filter to automatically remove vehicles from point clouds of roads captured by a mobile LiDAR system. The algorithm works in two main steps. The first one consists of the normalization and segmentation of the point cloud in order to homogenize the density of points in all areas corrected as function of vehicle speed. The second step is based on detecting changes of slope on the transversal profiles of the roads digitalized by LiDAR, inside the contours defined by the traffic lines that limit the road space. Profiles are produced by the rotation of the LiDAR mirror. Once detected those points of the LiDAR echoes that correspond to the vehicle they are automatically removed. Finally, the point cloud is regenerated using commercial software that creates new points based on parametric surfaces, fitting the points of the neighborhood of each hole produced by the elimination of vehicle points.The algorithms developed are tested by checking the successful of the vehicle detection and the geometric comparison of longitudinal profiles and cross sections, before and after the filter application. Results show as all the vehicles were successfully detected and corresponding echoes cleaned. Road profile and cross sections reveal that the generated geometries are in agreement with the real geometries of the road.

Automatic detection of road tunnel luminaires using a mobile LiDAR system

Over the past years, the importance of preserving existing transportation infrastructures has received increased focus. In particular, underground structures require routine inspections and maintenance processes for their optimal use. New possibilities exist now with the mobile terrestrial LiDAR systems, which can quickly scan and record huge data sets that need post-processing techniques to facilitate their efficient use.This paper describes an automatic method for the detection of tunnel luminaires as well as to easily obtain their 3D spatial location, using colored 3D point clouds. Detection performance was verified by experiments carried on real data acquired with the Lynx Mobile Mapper system in a highway tunnel in southern Galicia, Spain. The method gives promising results after data processing to automatize the detection of luminaires and improve the productivity of tunnel inspections.

Accuracy assessment of a mobile terrestrial lidar survey at Padre Island National Seashore

The higher point density and mobility of terrestrial laser scanning (light detection and ranging (lidar)) is desired when extremely detailed elevation data are needed for mapping vertically orientated complex features such as levees, dunes, and cliffs, or when highly accurate data are needed for monitoring geomorphic changes. Mobile terrestrial lidar scanners have the capability for rapid data collection on a larger spatial scale compared with tripod-based terrestrial lidar, but few studies have examined the accuracy of this relatively new mapping technology. For this reason, we conducted a field test at Padre Island National Seashore of a mobile lidar scanner mounted on a sport utility vehicle and integrated with a position and orientation system. The purpose of the study was to assess the vertical and horizontal accuracy of data collected by the mobile terrestrial lidar system, which is georeferenced to the Universal Transverse Mercator coordinate system and the North American Vertical Datum of 1988. To accomplish the study objectives, independent elevation data were collected by conducting a high-accuracy global positioning system survey to establish the coordinates and elevations of 12 targets spaced throughout the 12 km transect. These independent ground control data were compared to the lidar scanner-derived elevations to quantify the accuracy of the mobile lidar system. The performance of the mobile lidar system was also tested at various vehicle speeds and scan density settings (e.g. field of view and linear point spacing) to estimate the optimal parameters for desired point density. After adjustment of the lever arm parameters, the final point cloud accuracy was 0.060 m (east), 0.095 m (north), and 0.053 m (height). The very high density of the resulting point cloud was sufficient to map fine-scale topographic features, such as the complex shape of the sand dunes.

Design and Implementation of Multi-sensor Integrated 3D Laser Scanning Data Acquisition System

A LiDAR system is combined by various kinds of sensor systems. And the real-time data acquisition of multi-sensor is the basis of it. According to the characteristics of data acquisition for multi-sensor integrated mobile LiDAR system, we use Qt as development platform and adopt serial communication programming technology and multi-thread technology to achieve real-time data collection and preservation of the mobile 3D Laser Scanning Measuring system. Compared with the existing system, we designed 3D Laser Scanning Data Acquisition System overcame the inconvenience that we need to start each sensor data collection program individually and difficult for the data synchronization. In addition, this system also has superb portability. It can also be applied to other operating system supported by Qt such as Linux, Windows CE, etc. Finally, the experiment results show that this 3D Laser Scanning Data Acquisition System operation is stable and reliable, it could collect and preserve different kind of sensor data simultaneously and meet the application needs.

Performance testing of LiDAR exploitation software

Mobile LiDAR systems are being used widely in recent years for many applications in the field of geoscience. One of most important limitations of this technology is the large computational requirements involved in data processing. Several software solutions for data processing are available in the market, but users are often unknown about the methodologies to verify their performance accurately. In this work a methodology for LiDAR software performance testing is presented and six different suites are studied: QT Modeler, AutoCAD Civil 3D, Mars 7, Fledermaus, Carlson and TopoDOT (all of them in x64). Results depict as QTModeler, TopoDOT and AutoCAD Civil 3D allow the loading of large datasets, while Fledermaus, Mars7 and Carlson do not achieve these powerful performance. AutoCAD Civil 3D needs large loading time in comparison with the most powerful softwares such as QTModeler and TopoDOT. Carlson suite depicts the poorest results among all the softwares under study, where point clouds larger than 5 million points cannot be loaded and loading time is very large in comparison with the other suites even for the smaller datasets. AutoCAD Civil 3D, Carlson and TopoDOT show more threads than other softwares like QTModeler, Mars7 and Fledermaus.

Surveying of road slopes using mobile LiDAR

Purpose The slope of roads is one of the most important elements to be monitored to prevent landslides and ensure the safety of vehicles. This fact is particularly relevant in areas such as Galicia (Spain), where, due to its orography, slopes always are a relevant factor in road construction projects. Method Typically, the slopes of the roads are visually monitored by road inspectors and only in case of important problems do they use measuring equipment (e.g. extensometer, inclinometer). The aim of this work is to introduce the routine use of mobile LiDAR systems for monitoring of slopes. Results & Discussion A filter based on the returns of the laser shot is used to remove vegetation of the slope and work only with ground level information. An algorithm that compares the slope surface between two different inspection periods was developed. This algorithm extracts the systematic error due to GPS and can display variations of a few centimeters.

Automated Extraction of Road Markings from Mobile Lidar Point Clouds

This paper proposes a method for extracting road markings from mobile lidar point clouds. Among implicit information of laser points, the strength of reflection of laser points is closely related to the property of road materials that helps in detecting road markings. An interpolation method is used first in order to generate a georeferenced feature image of the point clouds, which helps to isolate the points of road surfaces. An algorithm is used to separate these points within a range according to their strength of reflection. The separated points are further segmented to remove non-road points based on their height threshold. The outlines of road markings are extracted from the segmented points using the semantic knowledge of road markings. The results presented in the paper demonstrate that the method used was very promising for automatic extraction of road markings from lidar point clouds collected by a land-based mobile lidar system.

System description of the mobile LIDAR of the CSIR, South Africa

South Africa’s first mobile LIDAR (LIght Detection And Ranging) system is being developed at the National Laser Centre (NLC) of the Council for Scientific and Industrial Research (CSIR) in Pretoria (25°45’S; 28°17’E). The system is designed primarily for remote sensing of the atmosphere. At present, the system is being optimised for measuring vertical atmospheric backscatter profiles of aerosols and clouds. In this paper, we describe the complete LIDAR system, including laser transmission, telescope configuration, data acquisi

Documentation of soiled and biodeteriorated facades: A case study on the Coliseum, Rome, using hyperspectral imaging fluorescence lidars

Abstract Non-invasive documentation of historic facades with fluorescence lidar techniques can provide helpful information for the cultural heritage sector, especially when large areas outdoors are to be examined. This paper presents a case study of the Coliseum, Rome, where both cleaned and heavily soiled areas of the monument were scanned and analysed with two fluorescence lidar systems. Biodeterioration processes were also addressed during the experiment, with the aim of assessing the colonisation extent on selected areas of the monument. Results show the usefulness of a mobile fluorescence lidar system for documentation and survey of large surfaces with complex conditions without limiting the public access to the monument.

3-dimensional observations of atmospheric variables during the field campaign COPS

The Convective and Orographically-induced Precipitation Study (COPS) has the aim to advance the quality of forecasts of orographically-induced precipitation in complex terrain. COPS is a Research and Development Project of the World Weather Research Program and considered to be one of the largest field campaigns on quantitative precipitation forecasting that has been performed so far. A network of state-of-the-art active and passive remote sensing systems was combined with in total 10 airborne platforms, Meteosat rapid scans and dense networks of standard meteorological instruments during the three months long field phase (June-August, 2007) in south-western Germany/eastern France to observe atmospheric variables in the three spatial dimensions and in time. By the University of Hohenheim, two novel ground-based mobile scanning lidar systems were deployed: a scanning rotational Raman lidar which provides combined measurements of the field of atmospheric temperature and aerosol optical properties, and a water-vapour differential absorption lidar (DIAL). During COPS, both lidar systems were located at Hornisgrinde, the highest peak of the northern Black Forest together with a large suite of other remote sensing systems. In this contribution we present and discuss highlights of these measurements.

Lidar research in South Africa

Lasers offer great advantages over conventional light sources in terms of peak power and narrow spectral bandwidth. Advancements in both laser and detector technology along with improvements in data-acquisition and analysis techniques have made laser radar or ‘lidar’ (for light detection and ranging) a very reliable tool for active atmospheric remote sensing. Although ground-based lidar systems are routinely used in many developed countries, the techique is still novel for South Africa (and other African countries). Two lidar configurations are currently available in South Africa, located in Pretoria and Durban. They are similar in operation and specifications, thus permitting simultaneous measurements. The Durban device is operated at the University of KwaZulu-Natal, as a collaborative project with Reunion University and the Service d’Aeronomie of the Centre National de la Recherche Scientifique (CNRS)/Institut Pierre Simon Laplace (France) for climate-research studies. The second device is a mobile lidar system aimed at contributing to atmospheric research in southern Africa, which was recently designed and developed by the National Laser Centre of the Council for Scientific and Industrial Research (CSIR) in South Africa.