Abstract
Mobile mapping systems (MMS) are becoming widely used in standard geodetic tasks more commonly in the last years. The paper is focused on the influence of control points (CPs) number and configuration on mobile laser scanning accuracy. The mobile laser scanning (MLS) data was acquired by MMS RIEGL VMX-450. The resulting point cloud was compared with two different reference data sets. The first reference data set consisted of a high-accuracy test point field (TPF) measured by a Trimble R8s GNSS system and a Trimble S8 HP total station. The second reference data set was a point cloud from terrestrial laser scanning (TLS) using two Faro Focus3D X 130 laser scanners. The coordinates of both reference data sets were determined with significantly higher accuracy than the coordinates of the tested MLS point cloud. The accuracy testing is based on coordinate differences between the reference data set and the tested MLS point cloud. There is a minimum number of 6–7 CPs in our scanned area (based on MLS trajectory length) to achieve the declared relative accuracy of trajectory positioning according to the RIEGL datasheet. We tested two types of ground control point (GCP) configurations for 7 GCPs, using TPF reference data. The first type is a trajectory-based CPs configuration, and the second is a geometry-based CPs configuration. The accuracy differences of the MLS point clouds with trajectory-based CPs configuration and geometry-based CPs configuration are not statistically significant. From a practical perspective, a geometry-based CPs configuration is more advantageous in the nonlinear type of urban area such as our one. The following analyzes are performed on geometry-based CPs configuration variants. We tested the influence of changing the location of two CPs from ground to roof. The effect of the vertical configuration of the CPs on the accuracy of the tested MLS point cloud has not been demonstrated. The effect of the number of control points on the accuracy of the MLS point cloud was also tested. In the overall statistics using TPF, the accuracy increases significantly with increasing the number of GCPs up to 6. This number corresponds to a requirement of the manufacturer. Although further increasing the number of CPs does not significantly increase the global accuracy, local accuracy improves with increasing the number of CPs up to 10 (average spacing 50 m) according to the comparison with the TLS reference point cloud. The accuracy test of the MLS point cloud was divided into the horizontal accuracy test on the façade data subset and the vertical accuracy test on the road data subset using the TLS reference point cloud. The results of this paper can help improve the efficiency and accuracy of the mobile mapping process in geodetic praxis.
Highlights
Mobile laser scanning (MLS) methods have become widely used to capture accurate 3D point clouds for many applications, for example, urban planning, 3D city modeling, civil engineering, and road surveying [1, 2, 3]
This paper aims to determine the influence of control points (CPs) number and configuration on mobile laser scanning local and global accuracy
The point clouds were divided into the façade data subset and the road data subset in the terrestrial laser scanning (TLS)-based accuracy testing
Summary
Mobile laser scanning (MLS) methods have become widely used to capture accurate 3D point clouds for many applications, for example, urban planning, 3D city modeling, civil engineering, and road surveying [1, 2, 3]. Published under licence by IOP Publishing Ltd depends on a large number of factors. These factors are the input data accuracy, density, and the algorithms used. The accuracy of MLS data can be divided into absolute and relative components, which correspond to the positioning subsystem and mapping subsystem of the mobile mapping system (MMS). The result of GNSS, IMU, and DMI data combination in a Kalman filter is Smoothed Best Estimated Trajectory (SBET). The mapping subsystem performs the spatial data acquisition and typically consists of one or more LIDAR sensors and cameras. Accurate calibration of both subsystems is a prerequisite for accurate georeferenced LIDAR data
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IOP Conference Series: Earth and Environmental Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.