Analysis of the impact of interior orientation parameters in different UAV-based image-block compositions on positional accuracy

Understanding the factors that influence the quality of unmanned aerial vehicle (UAV)-based products is a scientifically ongoing and relevant topic. Our research focused on the impact of the interior orientation parameters (IOPs) on the positional accuracy of points in a calibration field, identified and measured in an orthophoto and a point cloud. We established a calibration field consisting of 20 materialized points and 10 detailed points measured with high accuracy. Surveying missions with a fixed-wing UAV were carried out in three series. Several image blocks that differed in flight direction (along, across), flight altitude (70 m, 120 m), and IOPs (known or unknown values in the image-block adjustment) were composed. The analysis of the various scenarios indicated that fixed IOPs, computed from a good geometric composition, can especially improve vertical accuracy in comparison with self-calibration; an image block composed from two perpendicular flight directions can yield better results than an image block composed from a single flight direction.