Justification of the provisions of the methodology for performing ground photogrammetric survey of unfinished construction projects
- Authors: Vorobiev P.Y.1
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Affiliations:
- National Research Moscow State University of Civil Engineering
- Issue: No 3 (2025)
- Pages: 45-50
- Section: Articles
- URL: https://rjmseer.com/0044-4472/article/view/679479
- DOI: https://doi.org/10.31659/0044-4472-2025-3-45-50
- ID: 679479
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Abstract
This article presents the results of a study that substantiates the provisions of a methodology for conducting terrestrial photogrammetric surveys of unfinished construction objects using a dual-camera system. The relevance of this work stems from the necessity of obtaining reliable information about the actual condition of structural elements at unfinished construction sites, which is important for making decisions regarding necessary actions for restoration, demolition, or conservation of the object. For the study, a terrestrial photogrammetric survey was carried out using a dual-camera photogrammetric system on an unfinished construction object. The variable parameters considered in performing and processing the photogrammetric survey were shooting frequency, method of image alignment, and the application of an optimization procedure. The results obtained showed that to ensure successful image alignment, it is necessary to consider the minimum required shooting distance between frames and to apply an optimization procedure based on the accurate coordinates of the centers of reference images. The use of general pre-selection during image alignment allows for the best results in terms of the final model’s accuracy. The conclusions drawn enable the formulation of the main provisions of a methodology for conducting terrestrial photogrammetric surveys of unfinished construction objects using a dual-camera system, ensuring the acquisition of three-dimensional models for subsequent analysis of the technical condition of structural elements.
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About the authors
P. Y. Vorobiev
National Research Moscow State University of Civil Engineering
Author for correspondence.
Email: VorobevPYU@mgsu.ru
Teacher-Researcher
Russian Federation, 26, Yaroslavskoe Highway, Moscow, 129337References
- Idris Jeelani, Masoud Gheisari. Safety challenges of UAV integration in construction: Conceptual analysis and future research roadmap. Safety Science. 2021. Vol. 144. https://doi.org/10.1016/j.ssci.2021.105473
- Nils Rinke, Ilka von Gösseln, Vitali Kochkine, Jürgen Schweitzer, Volker Berkhahn, Fritz Berner, Hansjörg Kutterer, Ingo Neumann, Volker Schwieger. Simulating quality assurance and efficiency analysis between construction management and engineering geodesy. Automation in Construction. 2017. Vol. 76, pp. 24–35. https://doi.org/10.1016/j.autcon.2017.01.009
- Srijeet Halder, Kereshmeh Afsari, Erin Chiou, Rafael Patrick, Kaveh Akbari Hamed. Construction inspection & monitoring with quadruped robots in future human-robot teaming: A preliminary study. Journal of Building Engineering. 2023. Vol. 65. https://doi.org/10.1016/j.jobe.2022.105814
- Rong Huang, Yusheng Xu, Ludwig Hoegner, Uwe Stilla. Semantics-aided 3D change detection on construction sites using UAV-based photogrammetric point clouds. Automation in Construction. 2022. Vol. 134. https://doi.org/10.1016/j.autcon.2021.104057
- Kiriiak N. Development and implementation of technical decision for digital support of construction using photogrammetry methods. Nuclear Engineering and Design. 2021. Vol. 381. https://doi.org/10.1016/j.nucengdes.2021.111366
- Yitian Han, Dongming Feng, Weiwei Wu, Xingyu Yu, Gang Wu, Jixiang Liu. Geometric shape measurement and its application in bridge construction based on UAV and terrestrial laser scanner. Automation in Construction. 2023. Vol. 151. https://doi.org/10.1016/j.autcon.2023.104880
- Nan Ye, Hongyu Zhu, Mingqiang Wei, Liyan Zhang. Accurate and dense point cloud generation for industrial Measurement via target-free photogrammetry. Optics and Lasers in Engineering. 2021. Vol. 140. https://doi.org/10.1016/j.optlaseng.2020.106521
- Amir Ibrahim, Wilfredo Torres-Calderon, Mani Golparvar-Fard. Reinforcement learning for high-quality reality mapping of indoor construction using unmanned ground vehicles. Automation in Construction. 2023. Vol. 156, 105110. https://doi.org/10.1016/j.autcon.2023.105110
- Muhammad Mukhlisin, Hany Windri Astuti, Rini Kusumawardani, Eni Dwi Wardihani, Bambang Supriyo. Rapid and low cost ground displacement mapping using UAV photogrammetry. Physics and Chemistry of the Earth, Parts A/B/C. 2023. Vol. 130. https://doi.org/10.1016/j.pce.2023.103367
- Sander Varbla, Artu Ellmann, Raido Puust. Centimetre-range deformations of built environment revealed by drone-based photogrammetry. Automation in Construction. 2021. Vol. 128. https://doi.org/10.1016/j.autcon.2021.103787
- Rostislav Dandoš, Karel Mozdřeň, Hana Staňková. A new control mark for photogrammetry and its localization from single image using computer vision. Computer Standards & Interfaces. 2018. Vol. 56. https://doi.org/10.1016/j.csi.2017.09.003
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