An Exploratory Study on Imaging Resolution, Operational Parameters, and Measurement Uncertainty in UAV-Based Crack Inspection

Unmanned aerial vehicles (UAVs) are increasingly used for crack inspection of civil infrastructure. However, crack interpretation from UAV imagery is constrained by trade-offs among imaging resolution, operational efficiency, and measurement uncertainty. Higher resolution generally requires reduced flight distance, increased image quantity, and greater data-processing effort, which can limit inspection efficiency. This study presents an exploratory analysis of UAV-based crack inspection from a measurement-oriented perspective. Empirical UAV flight experiments were conducted to examine the relationships among flight distance, ground sampling distance (GSD), image quantity, and photogrammetric processing effort under controlled acquisition conditions. In addition, a dataset-based segmentation analysis was performed to investigate pixel-level uncertainty associated with crack thickness representation near the resolution limit. This analysis does not aim to estimate physical crack width, but rather to identify intrinsic limitations of image-based crack interpretation. The results indicate that while flight distance and GSD follow expected geometric relationships, image quantity and processing effort are influenced by multiple interacting factors rather than resolution alone. Pixel-level analysis further reveals substantial segmentation uncertainty for thin cracks represented by only a few pixels. These findings highlight the importance of accounting for measurement uncertainty and operational trade-offs when planning efficient UAV-based crack inspections.