Impact of Terrain and Environment on the Accuracy of Vehicle-Based Mobile Mapping Systems
DOI:
https://doi.org/10.14311/CEJ.2025.02.0020Keywords:
mobile mapping system, mobile laser scanning, point cloud accuracy, Riegl VMX-2HAAbstract
The rapid collection of accurate spatial data and its use in various domains is driving the development of Mobile Mapping Systems (MMS). This study evaluates the accuracy of the Riegl VMX-2HA system in three different environments: an urban residential area, an open road section with an unobstructed view of the sky, and a forested roadway where GNSS signals are significantly affected. This research investigates the effect of these environments and different alignment methods on point cloud accuracy. A combination of GNSS, IMU and DMI was used to determine the trajectory, with measurements tied to GCPs. The study compares the results of the processing of the separate sections with the calculation of the entire section and evaluates the differences of the repeated measurements. The results show that aligning measurements without separating sections by environment improves accuracy. The results contribute to the optimisation of MMS-based data collection strategies and provide insight to improve the reliability of spatial data collection.
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CHIANG, Kai Wei; TSAI, Guang-Je and ZENG, Jhih Cing. Mobile Mapping Technologies. Online. Urban Informatics. The Urban Book Series. 2021, s. 439-465. ISBN 978-981-15-8982-9. Available at: https://doi.org/10.1007/978-981-15-8983-6_25. [accessed 2025-02-13].
LAPUCHA, D. Precise GPS/INS “Positioning for Highway Inventory System”, Report No. 20038. Master’s Thesis. Online. Department of Geomatics Engineering, The University of Calgary, Calgary, AB,. 1990. [accessed 2025-02-13].
EL-SHEIMY, N. The Development of VISAT: A Mobile Survey System for GIS Applications. Ph.D. Thesis. Online. University of Calgary, Calgary, AB, Canada. 1996. Available at: https://prism.ucalgary.ca. [accessed 2025-02-13].
PUENTE, I.; GONZÁLEZ-JORGE, H.; MARTÍNEZ-SÁNCHEZ, J. and ARIAS, P. Review of mobile mapping and surveying technologies. Online. Measurement. 2013, roč. 46, č. 7, s. 2127-2145. ISSN 02632241. Available at: https://doi.org/10.1016/j.measurement.2013.03.006. [accessed 2025-02-13].
KERSTINGA, A. P. and FRIESS, P. POST-MISSION QUALITY ASSURANCE PROCEDURE FOR SURVEY-GRADE MOBILE MAPPING SYSTEMS. Online. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2016, roč. XLI-B1, s. 647-652. ISSN 2194-9034. Available at: https://doi.org/10.5194/isprs-archives-XLI-B1-647-2016. [accessed 2025-02-13].
KACZMAREK, Adrian; ROHM, Witold; KLINGBEIL, Lasse and TCHÓRZEWSKI, Janusz. Experimental 2D extended Kalman filter sensor fusion for low-cost GNSS/IMU/Odometers precise positioning system. Online. Measurement. 2022, roč. 193. ISSN 02632241. Available at: https://doi.org/10.1016/j.measurement.2022.110963. [accessed 2025-02-13].
BLASER, S.; MEYER, J.; NEBIKER, S.; FRICKER, L. and WEBER, D. CENTIMETRE-ACCURACY IN FORESTS AND URBAN CANYONS – COMBINING A HIGH-PERFORMANCE IMAGE-BASED MOBILE MAPPING BACKPACK WITH NEW GEOREFERENCING METHODS. Online. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2020, roč. V-1-2020, s. 333-341. ISSN 2194-9050. Available at: https://doi.org/10.5194/isprs-annals-V-1-2020-333-2020. [accessed 2025-02-13].
CAVEGN, S.; BLASER, S.; NEBIKER, S. and HAALA, N. ROBUST AND ACCURATE IMAGE-BASED GEOREFERENCING EXPLOITING RELATIVE ORIENTATION CONSTRAINTS. Online. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018, roč. IV-2, s. 57-64. ISSN 2194-9050. Available at: https://doi.org/10.5194/isprs-annals-IV-2-57-2018. [accessed 2025-02-13].
LI, Shuaixin; LI, Guangyun; WANG, Li and QIN, Yuchu. SLAM integrated mobile mapping system in complex urban environments. Online. ISPRS Journal of Photogrammetry and Remote Sensing. 2020, roč. 166, s. 316-332. ISSN 09242716. Available at: https://doi.org/10.1016/j.isprsjprs.2020.05.012. [accessed 2025-02-13].
XU, Xiaobin; ZHANG, Lei; YANG, Jian; CAO, Chenfei; WANG, Wen et al. A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR. Online. Remote Sensing. 2022, roč. 14, č. 12. ISSN 2072-4292. Available at: https://doi.org/10.3390/rs14122835. [accessed 2025-02-13].
GHARINEIAT, Zahra; TARSHA KURDI, Fayez; HENNY, Krish; GRAY, Hamish; JAMIESON, Aaron et al. Assessment of NavVis VLX and BLK2GO SLAM Scanner Accuracy for Outdoor and Indoor Surveying Tasks. Online. Remote Sensing. 2024, roč. 16, č. 17. ISSN 2072-4292. Available at: https://doi.org/10.3390/rs16173256. [accessed 2025-02-13].
VYNIKAL, Jakub and ZAHRADNÍK, David. Floor plan creation using a low‐cost 360° camera. Online. The Photogrammetric Record. 2023, roč. 38, č. 184, s. 520-536. ISSN 0031-868X. Available at: https://doi.org/10.1111/phor.12463. [accessed 2025-02-13].
ONIGA, V. E.; BREABAN, A. I.; ALEXE, E. I. and VĂSII, C. INDOOR MAPPING OF A COMPLEX CULTURAL HERITAGE SCENE USING TLS AND HMLS LASER SCANNING. Online. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2021, roč. XLIII-B2-2021, s. 605-612. ISSN 2194-9034. Available at: https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-605-2021. [accessed 2025-02-13].
CHUDÁ, Juliána; VÝBOŠŤOK, Jozef; TOMAŠTÍK, Julián; CHUDÝ, František; TUNÁK, Daniel et al. Prompt Mapping Tree Positions with Handheld Mobile Scanners Based on SLAM Technology. Online. Land. 2024, roč. 13, č. 1. ISSN 2073-445X. Available at: https://doi.org/10.3390/land13010093. [accessed 2025-02-13].
PAVELKA, Karel; MATOUŠKOVÁ, Eva and PAVELKA, Karel. Remarks on Geomatics Measurement Methods Focused on Forestry Inventory. Online. Sensors. 2023, roč. 23, č. 17. ISSN 1424-8220. Available at: https://doi.org/10.3390/s23177376. [accessed 2025-02-13].
ŠTRONER, Martin; URBAN, Rudolf; KŘEMEN, Tomáš; BRAUN, Jaroslav; MICHAL, Ondřej et al. Scanning the underground: Comparison of the accuracies of SLAM and static laser scanners in a mine tunnel. Online. Measurement. 2025, roč. 242. ISSN 02632241. Available at: https://doi.org/10.1016/j.measurement.2024.115875. [accessed 2025-02-13].
TRYBAŁA, P.; KASZA, D.; WAJS, J. and REMONDINO, F. COMPARISON OF LOW-COST HANDHELD LIDAR-BASED SLAM SYSTEMS FOR MAPPING UNDERGROUND TUNNELS. Online. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2023, roč. XLVIII-1/W1-2023, s. 517-524. ISSN 2194-9034. Available at: https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-517-2023. [accessed 2025-02-13].
DI STEFANO, Francesco; CHIAPPINI, Stefano; GORREJA, Alban; BALESTRA, Mattia and PIERDICCA, Roberto. Mobile 3D scan LiDAR: a literature review. Online. Geomatics, Natural Hazards and Risk. 2021, roč. 12, č. 1, s. 2387-2429. ISSN 1947-5705. Available at: https://doi.org/10.1080/19475705.2021.1964617. [accessed 2025-02-14].
YANG, Bisheng; DONG, Zhen; LIU, Yuan; LIANG, Fuxun and WANG, Yongjun. Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data. Online. ISPRS Journal of Photogrammetry and Remote Sensing. 2017, roč. 126, s. 180-194. ISSN 09242716. Available at: https://doi.org/10.1016/j.isprsjprs.2017.02.014. [accessed 2025-02-14].
WANG, Hanyun; LUO, Huan; WEN, Chenglu; CHENG, Jun; LI, Peng et al. Road Boundaries Detection Based on Local Normal Saliency From Mobile Laser Scanning Data. Online. IEEE Geoscience and Remote Sensing Letters. 2015, roč. 12, č. 10, s. 2085-2089. ISSN 1545-598X. Available at: https://doi.org/10.1109/LGRS.2015.2449074. [accessed 2025-02-14].
BALADO, J.; DÍAZ-VILARIÑO, L.; ARIAS, P. and GONZÁLEZ-JORGE, H. Automatic classification of urban ground elements from mobile laser scanning data. Online. Automation in Construction. 2018, roč. 86, s. 226-239. ISSN 09265805. Available at: https://doi.org/10.1016/j.autcon.2017.09.004. [accessed 2025-02-14].
GUNEY, Emin; BAYILMIS, Cuneyt and CAKAN, Batuhan. An Implementation of Real-Time Traffic Signs and Road Objects Detection Based on Mobile GPU Platforms. Online. IEEE Access. 2022, roč. 10, s. 86191-86203. ISSN 2169-3536. Available at: https://doi.org/10.1109/ACCESS.2022.3198954. [accessed 2025-02-15].
MA, Yang; ZHENG, Yubing; EASA, Said; WONG, Yiik Diew and EL-BASYOUNY, Karim. Virtual analysis of urban road visibility using mobile laser scanning data and deep learning. Online. Automation in Construction. 2022, roč. 133. ISSN 09265805. Available at: https://doi.org/10.1016/j.autcon.2021.104014. [accessed 2025-02-14].
MA, Lingfei; LI, Ying; LI, Jonathan; JUNIOR, Jose Marcato; GONCALVES, Wesley Nunes et al. BoundaryNet: Extraction and Completion of Road Boundaries With Deep Learning Using Mobile Laser Scanning Point Clouds and Satellite Imagery. Online. IEEE Transactions on Intelligent Transportation Systems. 2022, roč. 23, č. 6, s. 5638-5654. ISSN 1524-9050. Available at: https://doi.org/10.1109/TITS.2021.3055366. [accessed 2025-02-14].
YAO, Lianbi; QIN, Changcai; CHEN, Qichao and WU, Hangbin. Automatic Road Marking Extraction and Vectorization from Vehicle-Borne Laser Scanning Data. Online. Remote Sensing. 2021, roč. 13, č. 13. ISSN 2072-4292. Available at: https://doi.org/10.3390/rs13132612. [accessed 2025-02-14].
LI, Qiujie; YUAN, Pengcheng; LIN, Yusen; TONG, Yuekai and LIU, Xu. Pointwise classification of mobile laser scanning point clouds of urban scenes using raw data. Online. Journal of Applied Remote Sensing. 2021, roč. 15, č. 02. ISSN 1931-3195. Available at: https://doi.org/10.1117/1.JRS.15.024523. [accessed 2025-02-14].
REITERER, Alexander; WÄSCHLE, Katharina; STÖRK, Dominik; LEYDECKER, Achim and GITZEN, Niko. Fully Automated Segmentation of 2D and 3D Mobile Mapping Data for Reliable Modeling of Surface Structures Using Deep Learning. Online. Remote Sensing. 2020, roč. 12, č. 16. ISSN 2072-4292. Available at: https://doi.org/10.3390/rs12162530. [accessed 2025-02-15].
VIERHUB-LORENZ, Valentin; KELLNER, Maximilian; ZIPFEL, Oliver and REITERER, Alexander. A Study on the Effect of Multispectral LiDAR Data on Automated Semantic Segmentation of 3D-Point Clouds. Online. Remote Sensing. 2022, roč. 14, č. 24. ISSN 2072-4292. Available at: https://doi.org/10.3390/rs14246349. [accessed 2025-02-15].
KALVODA, Petr; NOSEK, Jakub; KURUC, Michal; VOLARIK, Tomas and KALVODOVA, Petra. Accuracy Evaluation and Comparison of Mobile Laser Scanning and Mobile Photogrammetry Data. Online. IOP Conference Series: Earth and Environmental Science. 2020, roč. 609, č. 1. ISSN 1755-1307. Available at: https://doi.org/10.1088/1755-1315/609/1/012091. [accessed 2025-02-15].
PUENTE, I.; GONZÁLEZ-JORGE, H.; RIVEIRO, B. and ARIAS, P. Accuracy verification of the Lynx Mobile Mapper system. Online. 2013, roč. 45, s. 578-586. ISSN 00303992. Available at: https://doi.org/10.1016/j.optlastec.2012.05.029. [accessed 2025-02-15].
GREŠLA, O. and JAŠEK, P. MEASURING ROAD STRUCTURES USING A MOBILE MAPPING SYSTEM. Online. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2023, roč. XLVIII-5/W2-2023, s. 43-48. ISSN 2194-9034. Available at: https://doi.org/10.5194/isprs-archives-XLVIII-5-W2-2023-43-2023. [accessed 2025-02-15].
TRECCANI, Daniele; ADAMI, Andrea; BRUNELLI, Valerio and FREGONESE, Luigi. Mobile mapping system for historic built heritage and GIS integration: a challenging case study. Online. Applied Geomatics. 2024, roč. 16, č. 1, s. 293-312. ISSN 1866-9298. Available at: https://doi.org/10.1007/s12518-024-00555-w. [accessed 2025-02-15].
BĚLOCH, Lukáš and PAVELKA, Karel. Optimizing Mobile Laser Scanning Accuracy for Urban Applications: A Comparison by Strategy of Different Measured Ground Points. Online. Applied Sciences. 2024, roč. 14, č. 8. ISSN 2076-3417. Available at: https://doi.org/10.3390/app14083387. [accessed 2025-02-15].
KALVODA, Petr; NOSEK, Jakub and KALVODOVA, Petra. Influence of Control Points Configuration on the Mobile Laser Scanning Accuracy. Online. IOP Conference Series: Earth and Environmental Science. 2021, roč. 906, č. 1. ISSN 1755-1307. Available at: https://doi.org/10.1088/1755-1315/906/1/012091. [accessed 2025-02-15].
EXPERIMENTAL DETERMINATION OF THE INFLUENCE OF CHOOSING TIE POINTS FOR MOBILE MAPPING IN POOR CONDITIONS. Online. In: Geodézie ve stavebnictví a průmyslu. Praha: Český svaz geodetů a kartografů, 2024, p. 70-80. ISBN 978-80-02-03049-2. Available at: http://csgk.fce.vutbr.cz/Oakce/A139/prezentace/11_GSP24_Gresla.pdf. [accessed 2025-02-15].
MATTHEUWSEN, L.; BASSIER, M. and VERGAUWEN, M. THEORETICAL ACCURACY PREDICTION AND VALIDATION OF LOW-END AND HIGH-END MOBILE MAPPING SYSTEM IN URBAN, RESIDENTIAL AND RURAL AREAS. Online. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019, roč. XLII-2/W18, s. 121-128. ISSN 2194-9034. Available at: https://doi.org/10.5194/isprs-archives-XLII-2-W18-121-2019. [accessed 2025-02-15].
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