Detection of distress in rural road pavements: an analysis of UAV altitude variations

Abstract. Ensuring the safety of road networks is a fundamental priority in both urban and rural contexts. The degradation of asphalt surfaces, an inevitable process, is driven by several factors, including the fourth power of axle loads imposed by vehicles, the use of materials that do not always meet high-quality standards, the growing volume of traffic, persistent congestion, and the effects of climate change. Initial damage often appears in the form of longitudinal, transverse, alligator, or block cracks. If not addressed promptly, these defects can progress into potholes, significantly increasing road hazards and repair costs. For municipal authorities, the economic burden of repairing potholes far exceeds that of addressing cracks at an earlier stage, highlighting the critical importance of timely maintenance interventions. Continuous monitoring of pavement conditions is essential to mitigate these risks. However, the frequency of assessments required for effective monitoring presents a challenge when traditional techniques are employed, as they are often associated with high costs and resource demands. Drone-based photogrammetry offers a cost-effective alternative, enabling efficient and accurate evaluations of pavement conditions. Despite its advantages, a significant gap exists in the parametric data linking measurement accuracy to flight altitude, limiting its optimisation for practical applications. This study investigates the relationship between flight altitude and measurement precision, analysing root mean square (RMS) values at altitudes of 5m, 10m, 15m, 20m, and 25m. The findings aim to provide a clearer understanding of the trade-offs between altitude and accuracy, contributing to the refinement of drone-based methodologies for pavement monitoring.