## 1 Introduction
Furthermore, the amount and type of data collected allow for more complex data analysis and visualisation, for example, in a virtual BIM environment [21; 22; 23]. As mentioned above, mobile mapping systems are used in many areas, not only in surveying. Handheld mobile scanners are suitable for measuring the dimensions of buildings, especially in old or complex buildings where manual measurement takes a significant amount of time. Mobile scanners are very useful in tight and poorly lit spaces, sewers, and mines, where data on the entire object can be obtained quickly. The data obtained in this way may not only be used for drawing 2D plans but they are suitable for 3D object modelling. Mobile mapping systems, where a carrier is a car, are used for mapping horizontal and vertical road signs, as sources for making Digital Technical Maps whose accuracy corresponds in Czechia to class 3 (the mean coordinate error is 14 cm), or they are used for linear structures surveying. A big issue in mobile mapping is accuracy. In particular, the dependence of accuracy on the frequency and distribution of control points [24; 25]. As this is a relativity new technology that is constantly rapidly developing, it is necessary to test this method and the behaviour of the devices in real conditions. With each instrument and new software, the accuracy and reliability parameters of the output change. A large amount of the literature has been written on mobile scanning, but only a small part of it has dealt with mobile mapping systems of the type Riegl VMX-2 HA. The work [26] compares mobile scanners in a point field that is 1.7 km long with a ground control point density of 1 point per 200 m. The determined accuracy is calculated from the differences between the measured MMS point cloud and the point cloud measured by the terrestrial static scanner and is around 2 cm. The papers [24; 27] deal mainly with comparisons between an MMS cloud and another cloud obtained by scanning with another device,dealing with point densities and relative accuracies. The calculated standard deviations are in the range of millimetres. The article [28] already deals with the accuracy against points measured by GNSS RTK (the spatial accuracy of a point is 7.4 cm), and a test area included up to 200 control points. The resulting mean standard deviations in this project ranged from 1.2 cm to 5.9 cm, with a maximum of 26 cm. It is important to mention that both checkpoints and MMS measurements are dependent on the GNSS method and the accuracy is of the same precision. Thus, the GNSS error is also reflected in the MMS accuracy result. Absolute accuracy is the focus of the paper [25]. In this paper, only a small area is surveyed, but the point field is dense and well-signalled, and the coordinates are accurately measured by an independent method. The standard deviation determined in this article is 1.7 cm. However, such conditions and precise points are impossible to achieve in practical use. This project aims to simulate commercial measurements (point field accuracy and signalling) as much as possible, and it is necessary to determine the accuracy of the final point cloud depending on the measurement conditions, location, and computational parameters. Multiple parameters enter the final quality and accuracy. The most influential are the accuracy of GNSS/INS and the accuracy and spacing of the control points. The goal of the project should be to determine the overall accuracy of the mobile mapping system, the problem spots in the measured locations, and the appropriate spacing of the control points. This article consists of several important parts. The first describes a detailed description of the testing, the devices used and their properties, the test field, the accuracy of the determination of the ground control points and checkpoints, and the expected accuracy of the MMS. Next, the chapter deals with how MMS data are processed and the approaches to their evaluation.