Pothole Detection Based on UAV Photogrammetry

• Published in: REVUE INTERNATIONALE DE GEOMATIQUE
• Main Authors: Darmawan, Muhammad Aliff Haiqal; Mukti, Shahrul Nizan Abd; Tahar, Khairul Nizam
• Format: Article
• Language: English
• Published: TECH SCIENCE PRESS 2025
• Subjects: Remote Sensing
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001401231800001

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 timeconsuming 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.