Accuracy Evaluation and Comparison of Mobile Laser Scanning and Mobile Photogrammetry Data

Abstract

Abstract Mobile mapping systems (MMS) are becoming used in standard geodetic tasks more common in the last years. This paper deals with the accuracy evaluation of two types of data acquired by MMS RIEGL VMX-450, and their comparison. The first type is data from mobile laser scanning (MLS). The second type is mobile photogrammetry data. The new high accurate test point field was built in area of Advanced Materials, Structures and Technologies (AdMaS) research centre that is part of Brno University of Technology. Geodetic network and test point field were measured by Trimble R8s GNSS system and Trimble S8 HP total station. The estimate of the 3D standard deviation determined by an adjustment is 2 mm. The accuracy of MLS and mobile photogrammetry data was tested based on the differences between the coordinates of the points determined from the MMS data and determined by before mentioned high precise measurement. The resulting coordinates from photogrammetric data were determined by manual detection of targets in the images. The estimate of the 3D standard deviation is 0.017 m from the MLS data, and 0.061 m from the mobile photogrammetry data. As we supposed, the mobile laser scanning data are significantly more accurate than mobile photogrammetry data. Achieved accuracy of MLS exceeds the original expectations with respect to the GNSS/IMU positioning accuracy, which is according to the manufacturer RIEGL between 0.02-0.05 m. The same scene is often scanned with multiple scanning passes to ensure high quality of the scanned point cloud, therefore we tested the relative accuracy of mobile laser scanning data from two MMS vehicle passes in the same locality of interest. Two different data sets were evaluated, first data set contains points on roads, second data set on buildings. The standard deviation estimate does not exceed 0.008 m and the maximum absolute deviation does not exceed 0.030 m for both data sets. The difference between the two passes is not significant in comparison with the accuracy criteria required for standard mapping purposes. We also compared automatic point cloud production from photogrammetry data processed in Bentley ContextCapture to the point cloud from laser scanning. The MLS data has been used as a reference because it is significantly more accurate as mentioned before. This comparison was done only on the second data set (buildings). The standard deviation estimate is 0.16 m and the maximum absolute deviation is 0.25 m. Our evaluation contains also statistical testing of outliers and stragglers. In contrast to many authors, we don’t use the simplified approach 3σ rule, and in 1D. We use more exact approach using critical values of the statistics for significance levels α = 5 % and α = 1 % to stragglers and outliers test in 3D.