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Unmanned Aerial Vehicles (UAVs) have gained widespread popularity as an efficient means for remote sensing, asset management, and reality modeling. In the realm of geotechnical applications, the accuracy of measurements obtained through UAVs is critical for assessing practical parameters such as soil layer thickness in earthworks and soil compaction projects. Several factors, including drone and camera quality, flight altitude, flight path, georeferencing methodology, number of photographs, and environmental conditions, can impact measurement accuracy. Potential dynamic movements of the drone during photo capture introduce variability (relative to photographs taken from a fixed camera position) at each point along the flight path, leading to potential discrepancies in results, as recorded images are influenced by environmental factors such as lighting, wind, and dust. This study aims to quantify the differences between two general approaches to image acquisition: (1) periodic stop-motion photography taken during a drone flight with single photographs taken at specified intervals and (2) image analysis of photographs extracted from continuous-feed video recorded by the drone during continuous flight. To assess the two image capture techniques, aerial surveys of check points in known configurations were performed, with ground control points also being placed at predetermined locations within the survey area. Traditional survey methods were employed to georeference the coordinates of the ground control points. Approximately 400 photos were captured under “nearly fixed” (relatively stable) positional states, with an equivalent number of images extracted from the continuous video feed at similar corresponding locations. The coordinates of the checkpoints were obtained using reality modeling software. The findings from this study offer valuable insights into the comparative accuracy of these two image acquisition approaches and also shed light on the influence of various video capturing techniques on measurement accuracy.