Work

Optimizing UAV Flight Parameters for Linear Infrastructure Pathology Detection: Assessing Smart Oblique Capture

Year: 2026

Type: article

Abstract: The rapid deterioration of road infrastructure requires accurate and efficient methods for detecting pavement distresses. Unmanned Aerial Vehicles (UAVs) have emerged as a reliable alternative to conventional inspection techniques, enabling high-resolution data acquisition and improved operational safety. This study investigates the application of the Smart Oblique Capture (SOC) technique for pavement inspection through a systematic calibration of UAV flight parameters, including Ground Sample Distance (GSD), frontal and lateral overlap, camera tilt angle, and flight pattern. A structured experimental campaign was conducted, comprising 135 parameter combinations evaluated across three independent scenarios, resulting in a total of 405 UAV flights. The analysis focused on assessing the impact of these parameters on the visual quality of two-dimensional pavement reconstructions and processing efficiency. The results show that a configuration consisting of a 0.5 cm/pixel GSD, 70% frontal overlap, 80% lateral overlap, and a 70° camera tilt angle achieves the best balance between reconstruction quality and computational cost. Furthermore, the findings indicate that Smart Oblique Capture does not provide a statistically significant improvement in reconstruction quality for linear infrastructure compared to conventional oblique configurations, despite requiring a higher number of images and longer processing times. Overall, the results demonstrate that flight parameter calibration plays a more critical role than the adoption of advanced acquisition strategies such as Smart Oblique Capture. This study provides practical and reproducible guidelines for UAV-based pavement inspection, supporting efficient data acquisition while minimizing redundant information and unnecessary computational costs in infrastructure monitoring workflows.

Source: Drones

DOI: 10.3390/drones10050324

Authors: Jingwei Liu, José Lemus-Romani, Eduardo J. Rueda, Esteban González-Rauter, Marcelo Becerra-Rozas

Institutions: Pontificia Universidad Católica de Chile, Viña del Mar University, Pontificia Universidad Católica de Valparaíso

Language: English

Topic: 3D Surveying and Cultural Heritage

Subfield: Geology

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,137