Investigation of the Riegl terrestial scanners - uses and limitations

Terrestrial laser scanners are becoming more familiar in the surveying industry due to the significant technological advances in equipment over the past 10 – 20 years introducing many new types of equipment and methods for the capture of point data in a variety of environments. The introduction of the terrestrial laser scanner in the surveying industry has been slowed by a lack of understanding in comparison with traditional surveying methods. This poses the question to the surveying industry of whether the relative accuracies and potential uses of terrestrial laser scanning systems can be of significant value to the surveying industry much like GPS has become over the last decade. For this project I have conducted testing on various facets of terrestrial laser scanning operation, specifically confirmation of specifications and the ability to establish a method providing legal traceability of measurements obtained from these systems. This project utilised the RIEGL LMS-Z620 terrestrial laser scanner and a Trimble S8 total station. The results from the various scan sessions were then analysed to compare the obtained data to the specified accuracies published by the manufacturer as well as extracting information that members of the surveying industry can use to evaluate the capabilities of this instrument for traditional and non-traditional scanning applications. Terrestrial laser scanning is a relatively new concept for surveyors, with scanners capable of capturing large amounts of three-dimensional coordinated data quickly and very accurately without having to physically access objects and / or environments that may be hazardous or impractical to access. In Australia surveyors have not embraced the technology as quickly as other countries due to the unknown capabilities and questions about the accuracies that can be achieved, when compared to existing equipmen

Special issue on 'Terrestrial laser scanning': editors' notes

In this editorial, we provide an overview of the content of the special issue on 'Terrestrial Laser Scanning'. The aim of this Special Issue is to bring together innovative developments and applications of terrestrial laser scanning (TLS), understood in a broad sense. Thus, although most contributions mainly involve the use of laser-based systems, other alternative technologies that also allow for obtaining 3D point clouds for the measurement and the 3D characterization of terrestrial targets, such as photogrammetry, are also considered. The 15 published contributions are mainly focused on the applications of TLS to the following three topics: TLS performance and point cloud processing, applications to civil engineering, and applications to plant characterization

Establishment of Accuracy Testing Facilities for Terrestrial Laser Scanners

Measurement instruments that are required for high precision and reliable work need to have regular checks to ensure they are always performing at the required level of accuracy. A Terrestrial Laser Scanner is one such instrument and with the vast amount of information that this machine is able to capture, it is especially important to run regular accuracy checks. This research is building on the work that has been done by previous researchers on the assessment of instrument accuracy and the establishment of facilities specialized for this assessment. Theoretical principles are investigated in the form of Least Squares Adjustments, similarities to panorama photography and photogrammetric accuracy. Terrestrial Laser Scanners are reviewed with respect to their scanning principles and data acquisition. The methodology incorporated in this research encompasses the positioning of targets, their survey to establish high accuracy coordinates through various methods of adjustment and thereafter the scanning of those targets. Comparisons were done using derived angles and distances between the targets to discover the point accuracy of the Laser Scanner. This was done for two facilities; a short range facility (1 to 15 meters) and a medium range facility (1 to 75 meters). The medium range facility also included a range testing baseline for distance accuracy assessments. The outcomes from the comparisons between the surveyed control data and the laser scanner observed data indicated that the laser scanner is performing below the accuracy of the surveyed data. The laser scanner was further compared against the manufacturer quoted performance specifications and revealed the laser scanner to be performing below the quoted values. The laser scanner in question showed stronger results in the horizontal measurements over the vertical measurements. All results suggested the laser scanner was delivering weak results in the vertical observations due to a mis-alignment of individual scan halves. This research was able to establish two accuracy assessment facilities specialized for Terrestrial Laser Scanners under these same conditions. Both facilities were used in conjunction, to analyze the Z+F Imager 5010C laser scanner and determine the point accuracy in terms of the observed angles and distances from this machine. The results are also able to identify errors in the performance of the laser scanner and whether or not it is performing within the manufacturer specifications by noticing any large values such as in the case of the vertical observations for this instrument

Dam deformation surveys with modern technology

Dam deformation surveys are repetitive surveys that must be undertaken periodically on high risk structures such as large earthfill dams. This dissertation is to examine and test the ability of the Leica Nova MS50 terrestrial laser scanner (TLS) and utilise these findings to develop a dam deformation survey procedure that can be amplified by the inclusion of TLS. The Leica Nova MS50 is an instrument that has only recently come onto the market. It provides the latest technology by combining a high precision total station technology with the capability of capturing highly accurate scanned data. The existing dam deformation survey methods require manually placing survey targets on predefined stations located across the surveyed surface, placing the surveyor in danger from slips, trips and falls on often steep and unstable ground. There is an identified need for an automated remote process to be developed, providing safety for the surveyor whilst not compromising the survey accuracy. It will be possible to determine the accuracy of the Leica Nova MS50 and its suitability to be utilised in dam deformation surveys by developing three separate testing scenarios: Angle of incidence test – determining the effect the angle of incidence has on a distance read; Difference in length detection – examine the accuracy of the instrument and determine the difference in length measurement capabilities at nominal lengths; and Laser Dot Size – to examine the size of the measuring laser at nominal lengths. This dissertation found the Leica Nova MS-50 to be a very accurate and capable machine. It was determined from the testing conducted that scanning at 1000 hertz for deformation scanning had to be limited to distances less than 100 metres (m). It was also verified that survey control pillars would need to be constructed in the most suitable location; ensuring scanning procedures are conducted from the same location for each epoch. This dissertation also found, the rabble rock surface that earthfill dam walls are covered by, creates exaggerated error when scanning due to the uneven surface. Therefore it was determined this survey method may be best suited to concrete structures are surfaces that are flat

Monitoring capabilities of a mobile mapping system based on navigation qualities

Mobile mapping systems are becoming increasingly popular as they can build 3D models of the environment rapidly by using a laser scanner that is integrated with a navigation system. 3D mobile mapping has been widely used for applications such as 3D city modelling and mapping of the scanned environments. However, accurate mapping relies on not only the scanner’s performance but also on the quality of the navigation results (accuracy and robustness) . This paper discusses the potentials of using 3D mobile mapping systems for landscape change detection, that is traditionally carried out by terrestrial laser scanners that can be accurately geo-referenced at a static location to produce highly accurate dense point clouds. Yet compared to conventional surveying using terrestrial laser scanners, several advantages of mobile mapping systems can be identified. A large area can be monitored in a relatively short period, which enables high repeat frequency monitoring without having to set-up dedicated stations. However, current mobile mapping applications are limited by the quality of navigation results, especially in different environments. The change detection ability of mobile mapping systems is therefore significantly affected by the quality of the navigation results. This paper presents some data collected for the purpose of monitoring from a mobile platform. The datasets are analysed to address current potentials and difficulties. The change detection results are also presented based on the collected dataset. Results indicate the potentials of change detection using a mobile mapping system and suggestions to enhance quality and robustness

Laser scanning for forest structure analysis

Terrestrial laser scanning is one of the most recent technological advancements within the spatial science industry. Its current use within the forest analysis field is limited. Collecting data to create a forest inventory can be a long and strenuous process with current procedures relying on outdated and inefficient techniques. Terrestrial laser scanning is a technique that has the potential to greatly enhance this data collection process. In this study, a forested area of 6700m2 in eastern Toowoomba has been scanned to extract tree height, diameter at breast height, basal area and volume. The same data has been collected using contemporary techniques so that terrestrial laser scanning's suitability can be assessed. The measured components were compared and discrepancies were identified. When compared to traditional methods, laser scanning overestimated height by 0.196m (2.42%). Diameter at breast height, basal area and volume were all underestimated by 0.061m (13.33%), 0.044m2 (24.35%) and 0.374m3 (22.47%) respectively. The differences in height and diameter at breast height are acceptable. The differences in excess of 20%, namely basal area and volume, are unacceptable with further research required to identify both the cause and solution

Uncertainty Modelling of Laser Scanning Point Clouds Using Machine-Learning Methods

Terrestrial laser scanners (TLSs) are a standard method for 3D point cloud acquisition due to their high data rates and resolutions. In certain applications, such as deformation analysis, modelling uncertainties in the 3D point cloud is crucial. This study models the systematic deviations in laser scan distance measurements as a function of various influencing factors using machine-learning methods. A reference point cloud is recorded using a laser tracker (Leica AT 960) and a handheld scanner (Leica LAS-XL) to investigate the uncertainties of the Z+F Imager 5016 in laboratory conditions. From 49 TLS scans, a wide range of data are obtained, covering various influencing factors. The processes of data preparation, feature engineering, validation, regression, prediction, and result analysis are presented. The results of traditional machine-learning methods (multiple linear and nonlinear regression) are compared with eXtreme gradient boosted trees (XGBoost). Thereby, it is demonstrated that it is possible to model the systemic deviations of the distance measurement with a coefficient of determination of 0.73, making it possible to calibrate the distance measurement to improve the laser scan measurement. An independent TLS scan is used to demonstrate the calibration results

Evaluation of surface defect detection in reinforced concrete bridge decks using terrestrial LiDAR

Routine bridge inspections require labor intensive and highly subjective visual interpretation to determine bridge deck surface condition. Light Detection and Ranging (LiDAR) a relatively new class of survey instrument has become a popular and increasingly used technology for providing as-built and inventory data in civil applications. While an increasing number of private and governmental agencies possess terrestrial and mobile LiDAR systems, an understanding of the technology’s capabilities and potential applications continues to evolve. LiDAR is a line-of-sight instrument and as such, care must be taken when establishing scan locations and resolution to allow the capture of data at an adequate resolution for defining features that contribute to the analysis of bridge deck surface condition. Information such as the location, area, and volume of spalling on deck surfaces, undersides, and support columns can be derived from properly collected LiDAR point clouds. The LiDAR point clouds contain information that can provide quantitative surface condition information, resulting in more accurate structural health monitoring. LiDAR scans were collected at three study bridges, each of which displayed a varying degree of degradation. A variety of commercially available analysis tools and an independently developed algorithm written in ArcGIS Python (ArcPy) were used to locate and quantify surface defects such as location, volume, and area of spalls. The results were visual and numerically displayed in a user-friendly web-based decision support tool integrating prior bridge condition metrics for comparison. LiDAR data processing procedures along with strengths and limitations of point clouds for defining features useful for assessing bridge deck condition are discussed. Point cloud density and incidence angle are two attributes that must be managed carefully to ensure data collected are of high quality and useful for bridge condition evaluation. When collected properly to ensure effective evaluation of bridge surface condition, LiDAR data can be analyzed to provide a useful data set from which to derive bridge deck condition information