Khairulnizam M. Idris

Calibration and accuracy assessment of Leica ScanStation C10 terrestrial laser scanner

Requirement of high accuracy data in surveying applications has made calibration procedure a standard routine for all surveying instruments. This is due to the assumption that all observed data are impaired with errors. Thus, this routine is also applicable to terrestrial laser scanner (TLS) to make it available for surveying purposes. There are two calibration approaches: (1) component, and (2) system calibration. With the intention to specifically identify the errors and accuracy of the Leica ScanStation C10 scanner, this study investigates component calibration. Three components of calibration were performed to identify the constant, scale error, accuracy of angular measurement and the effect of angular resolution for distance measurement. The first calibration has been processed using closed least square solutions and has yielded the values of constant (1.2 mm) and scale error (1.000008879). Using variance ratio test (F-Test), angles observation (horizontal and vertical) for Leica C10 scanner and Leica TM5100A theodolite have shown significance difference. This is because the accuracy of both sensors are not similar and these differences are 0.01 and 0.0075o for horizontal and vertical measurements, respectively. Investigation on the resolution setting for Leica C10 scanner has highlighted the drawback of the tilt-and-turn target. Using the highest resolution, Leica Cyclone software only able to recognize the tilt-and-turn target up to 10 m distance compare to 200 m for the black and white target.

Application of low-cost tools and techniques for landslide monitoring

This paper proposes a low-cost landslide monitoring system using the Reverse Real-Time Kinematic (RRTK) technique. The server-based processing technique, which utilizes the two-way communication channel for the computation and transmission of the user’s accurate position, is discussed. The basic infrastructure requirements for RRTK in lowcost landslide monitoring application are described. In order to implement the proposed RRTK algorithm, real-time data streaming of raw Global Positioning System (GPS) data of both the reference and rover station(s) to the control centre, are performed. A high pass filtering technique was employed to detect outliers in the observations. Finally, the autocorrelation of GPS time series was investigated to validate the presence of white and coloured noises in the GPS observations.

Reverse RTK data streaming for low-cost landslide monitoring

This chapter describes the preliminary study of real-time data streaming in support of the proposed low-cost landslide monitoring system using the Reverse Real-Time Kinematic (RRTK) technique. The RRTK algorithm was implemented by streaming raw Global Positioning System (GPS) data of both the reference and roving station(s) to the control centre for processing, and transmission of the position solution to the roving station. The main purpose of the data streaming was to investigate the quality of the measurements, for utilization in landslide modelling and analysis in near real-time. A novel methodology using a high pass filtering technique was implemented, to detect outliers in the observations. Also, the autocorrelation of GPS time series was investigated.

3D Data Fusion Using Unmanned Aerial Vehicle (UAV) Photogrammetry and Terrestrial Laser Scanner (TLS)

Recognizing the various advantages offered by 3D new metric survey technologies for 3D modelling reconstruction, this study presents a method or procedure of complete 3D data acquisition, using different sensors, and their possible fusion. Besides, this involved a discussion of the capability of UAV photogrammetry in order to collect data for the rooftop of the building with the low cost and combine the data with terrestrial measurement technique. Meanwhile, the aim of this study is to identify the minimum network configuration as to combine TLS and UAV photogrammetry data fusion. Hence, some procedure has been done in the methodology by registering TLS and UAV point clouds by employing multinetwork configuration. Furthermore, the data fusions’ results were evaluated on the registration error of UAV towards TLS coordinate system via the various number of network configuration samples. Based on the experimental results, the sample of network configuration for the three registration points results in a good condition due to the well-distributed registration points and less errors of both point clouds’ registration. As conclusion, a good quality of data fusion between TLS and UAV photogrammetry is determined by a good selection number of the registration points via several samples of network configuration.

Terrestrial laser scanners self-calibration study: Datum constraints analyses for network configurations

Similar to other electronic instruments, terrestrial laser scanner (TLS) can also inherent with various systematic errors coming from different sources. Self-calibration technique is a method available to investigate these errors for TLS which were adopted from photogrammetry technique. According to the photogrammetry principle, the selection of datum constraints can cause different types of parameter correlations. However, the network configuration applied by TLS and photogrammetry calibrations are quite different, thus, this study has investigated the significant of photogrammetry datum constraints principle in TLS self-calibration. To ensure that the assessment is thorough, the datum constraints analyses were carried out using three variant network configurations: (1) minimum number of scan stations; (2) minimum number of surfaces for targets distribution; and (3) minimum number of point targets. Based on graphical and statistical, the analyses of datum constraints selection indicated that the parameter correlations obtained are significantly similar. In addition, the analysis has demonstrated that network configuration is a very crucial factor to reduce the correlation between the calculated parameters.

Data quality assurance for hybrid and panoramic scanners via self-calibration

Quality assurance (QA) is a crucial process to ensure the maximize accuracy of the data delivered to client. Equipped with many moving parts whose relative positions can change over time depending on use, handling frequency and care, the QA is essential for TLS. Furthermore, with rapid and dense three-dimensional (3D) data collection ability, TLS has gain interest for many accurate 3D applications (e.g. industrial surveying, deformation measurement and reverse engineering). The QA for TLS measurement can be performed through calibration procedures, whether via component or system calibrations. Due to the non-affordable facilities and tools by most TLS users required by component calibration, this study focussed on the latter approach which only requires a room with appropriate targets. By employing optimal network configuration, system calibration was performed through self-calibration for hybrid (Leica ScanStation C10) and panoramic (Faro Photon 120) scanners. Four calibration parameters (e.g. constant range (a0), collimation axis (b0), trunnion axis (b1) and vertical circle index (c0) errors) were derived from 138 well-distributed targets in a laboratory with dimensions of 15.5m (length) × 9m (width) × 3m (height). For accuracy assessment purpose, fifteen test points are established at calibration field using photogrammetric technique. Those test points then were used to graphically and statistically evaluate the improvement in accuracy between TLS raw and calibrated data. As expected, the outcomes of statistical analyses have indicated an accuracy enhancement, for both scanners, respectively of 11% for Leica ScanStation C10 (1.7mm) and 50% for Faro Photon 120 (1.8mm) scanners.

Improvement in Accuracy Through Self-Calibration for Panoramic Scanner

Currently, three-dimensional (3D) information has become a necessity for many purposes especially for documentation, management and analysis. With the rapid and dense 3D data (point clouds) and considerably at high accuracy has made terrestrial laser scanner (TLS) widely used for these purposes. However, similar to other 3D instruments, TLS measurements also cannot escape from the occurrence of various systematic errors. Through self-calibration, the significant systematic errors consisted in TLS can be modelled and subsequently removed to improve the accuracy of the data. To prove that statement, this study has performed self-calibration for panoramic scanner (Faro Photon 120) at a laboratory with dimensions of 15.5 m × 9 m × 3 m. By employing optimal network configuration, all 138 well-distributed planar targets were measured from seven scanner positions to derive four calibration parameters. Statistical analysis (e.g. t test) has shown that only two parameters, the constant rangefinder offset error (9.3 mm) and the vertical circle index error (9.4″) were significant for the calibrated scanner. To ensure that self-calibration can improve the accuracy of TLS data, photogrammetric technique was utilised to establish 15 3D test points at the calibration field. These test points were used to graphically and statistically demonstrate the improvement in accuracy between raw data and calibrated data of Faro Photon 120 scanner.