ISPRS-Archives The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprs-archives-XLVIII-5-W2-2023-43-2023 MEASURING ROAD STRUCTURES USING A MOBILE MAPPING SYSTEM Grešla O. 1 2 Jašek P. 1 Geodetická kancelář Nedoma & Řezník, s.r.o., 10200 Prague 10, Plukovnika Mraze 1425/1, Czech Republic Czech Technical University in Prague, Faculty of Civil Engineering, 16629 Prague 6, Thakurova 7, Czech Republic 13 06 2023 XLVIII-5/W2-2023 43 48 Copyright: © 2023 O. Grešla 2023 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-5-W2-2023/43/2023/isprs-archives-XLVIII-5-W2-2023-43-2023.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-5-W2-2023/43/2023/isprs-archives-XLVIII-5-W2-2023-43-2023.pdf

The purpose of this thesis is to provide a detailed description of the Riegl VMX-2HA mobile mapping systém (MMS), its functions, composition and the data acquisition and processing procedure. In addition, this work presents a comparative analysis of the systém‘s height accuracy in relation to measurements made with the Leica NOVA MS50 multi-station. Using an experimental method, this study also shows that the order in which the described steps are performed can significantly affect the accuracy of the collected data. The results show that the use of the MMS in combination with appropriate data processing techniques can result in highly accurate data that can be used for a wide range of applications in the field of transportation infrastructure management and development. By providing a deeper understanding of the functions and capabilities of the MMS, this thesis describes valuable knowledge for professionals in the field seeking to optimize their data collection and analysis methods.