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Pothole Detection Based on UAV Photogrammetry

by Muhammad Aliff Haiqal Darmawan1, Shahrul Nizan Abd Mukti2, Khairul Nizam Tahar1,*

1 School of Geomatics Science and Natural Resources, College of Built Environment, Universiti Teknologi MARA, Shah Alam, 40450, Malaysia
2 Kuala Lumpur City Hall, Menara DBKL1, Kuala Lumpur, 50350, Malaysia

* Corresponding Author: Khairul Nizam Tahar. Email: email

Revue Internationale de Géomatique 2025, 34, 21-35. https://doi.org/10.32604/rig.2024.057266

Abstract

Potholes are the most prevalent type of structural defect found on roads, caused by aging infrastructure, heavy rains, heavy traffic, thin or weak substructures, and other factors. Regular assessment of road conditions is essential for maintaining and improving road networks. Current techniques for identifying potholes on urban roadways primarily rely on public reporting, such as hotlines or social networking websites, which are both time-consuming and inefficient. This study aims to detect potholes using Unmanned Aerial Vehicles (UAVs) images, enabling accurate analysis of their size, shape, and location, thereby enhancing detection efficiency compared to conventional methods. It compared area and volume measurements of potholes derived from UAV models with those obtained through traditional methods, revealing discrepancies and highlighting UAVs’ potential for providing more accurate data with appropriate settings. The study found measurement errors ranging from 90 to 8200 cm2 in area and 2000 to 31,000 cm3 in volume, emphasizing the need for careful data handling in assessments. This study demonstrates UAV technology’s effectiveness in pothole detection, providing insights that support the adoption of aerial photogrammetry for road maintenance. This approach has the potential to improve efficiency in infrastructure management. By appropriately adjusting altitude settings and parameters based on pothole size and depth, UAVs can detect potholes effectively. To achieve more accurate results, the study recommends analyzing a larger number of potholes rather than limiting the focus to a single pothole.

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Cite This Article

APA Style
Darmawan, M.A.H., Mukti, S.N.A., Tahar, K.N. (2025). Pothole detection based on UAV photogrammetry. Revue Internationale de Géomatique, 34(1), 21–35. https://doi.org/10.32604/rig.2024.057266
Vancouver Style
Darmawan MAH, Mukti SNA, Tahar KN. Pothole detection based on UAV photogrammetry. Revue Internationale de Géomatique. 2025;34(1):21–35. https://doi.org/10.32604/rig.2024.057266
IEEE Style
M. A. H. Darmawan, S. N. A. Mukti, and K. N. Tahar, “Pothole Detection Based on UAV Photogrammetry,” Revue Internationale de Géomatique, vol. 34, no. 1, pp. 21–35, 2025. https://doi.org/10.32604/rig.2024.057266



cc Copyright © 2025 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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