A Mobile Laser Scanning System (MLSS) is a kinematic platform combining different sensors, namely: GPS, IMU and laser scanner. These sensors are integrated and synchronised to a common time base providing 3D geo-referenced data. MLSS is used in several areas; such as 3D urban and landscape modelling for visualisation in planning and road design, simulations for environmental management, and to support land use decision-making. The accuracy of 3D geo-referenced points, achieved via Mobile Laser Scanning (MLS) under normal conditions, can reach the level of 3cm. However, this accuracy tends to be degraded in urban areas, because of trajectory errors of the laser scanner (IMU drift due to the limited availability of GPS signal). This, also, can be attributed to the difficulty of matching natural features in the point cloud. Previous researches have tried to overcome the problems in urban laser scanning by focusing on enhancing the performance of the navigation system (NGS). This can be costly and may not achieve the high accuracy level required for some engineering application. When the navigation solution is degraded, the accuracy of the point cloud results will be degraded. Using different data sources is another way to improve accuracy in urban areas. For example using airborne LiDAR, terrestrial imagery, and unmanned aerial vehicle (UAV) but these are very time consuming as well as costly compared to MLS systems. Targets are used in a number of ways in MLS and are often chosen from natural detail points. These can be difficult to define, particularly when high accuracy requirements need to be met, for example, when matching scans together or fitting scans to existing surveys as used in this project, and calibrating the system. The accuracy of MLS in the urban area was tested using three methods, namely ground control points (GCPs), surface to surface comparing, and additional source of data. Also, the effect of range, incidence angle (IA), resolution and brightness on different types of targets (sphere, cone, pyramid and flat target) was studied to explore the optimal target design. Moreover, an algorithm for automatic target detection was developed to detect the optimal target. Then, for each target in the point cloud, the centre/apex was calculated using least squares surface fitting. Tests show that the accuracy of 3D coordinates, obtained from MLS in an urban area is about 2-5 cm. Tests also show that using targets with MLS can improve the quality of results reaching 5 mm levels of accuracy even in the urban area, based on the use of check points to assess the quality and reliability of the outputs Almost all work on this project was carried out using the software packages available at the Nottingham Geospatial Institute (NGI) and MLS data provided by 3D Laser Mapping Ltd. (3DLM). Two terrestrial laser scanners, namely: HDS 3000 and Faro Focus3D have been used for testing the designed targets. The findings of this research will contribute easy, cost effective and improved accuracies in MLS data. This enhances usefulness in applications, such as change detection, deformation monitoring, cultural heritage and the process of 3D modelling, particularly in urban areas.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:594661 |
| Date | January 2013 |
| Creators | Abdulrahman, Farsat Heeto |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/13563/ |
Page generated in 0.0151 seconds