Circlegrammetry for drone imaging: Evaluating a novel technique for mission planning and 3D mapping

Circlegrammetry is a new drone photogrammetry technique that utilizes circular flight paths. This approach promises higher efficiency for 3D modelling compared to traditional grid-based methods. This study evaluates its performance in a Christmas tree (Balsam fir) field, a complex agricultural environment characterized by intricate vegetation geometry. Experiments were conducted in a 2-ha orchard located in Truro, Nova Scotia, using a DJI Matrice 300 RTK equipped with a high-resolution optical camera. Three Circlegrammetry missions with varying overlaps (25 and 50 %) and flight heights (40 and 60 m) were compared against standard oblique and smart oblique drone missions flown at an flight heights of 60 m. Mission assessments focused on flight efficiency, processing performance and reconstruction accuracy. The point density of the tree canopy, generated from dense point clouds, was also evaluated against different survey methods. Results demonstrated that Circlegrammetry significantly reduced flight times and the number of images required, particularly at lower overlap configurations. For example, Circlegrammetry with a 25 % overlap achieved mission completion in about half the time required for smart oblique methods and in approximately one-third the duration of standard oblique missions. Processing efficiency was similarly favoured by Circlegrammetry (25 % overlap), with notable reductions in processing times. In terms of reconstruction quality, Circlegrammetry produced spatially accurate models with ground-control RMSE values ranging from 1.38 to 1.53 cm. These results were comparable to those of traditional oblique methods, despite not utilizing nadir imagery. However, Circlegrammetry showed limitations in capturing lower canopy details on the tree, with an average point density higher than that of other methods. For example, Circle 25 % performed the worst, with an average point spacing of 15.79 points per millimetre for the lower canopy. In contrast, the standard oblique approach performed the best, with an average point spacing of 11.89 points per millimetre. This suggested some constraints inherent to the inward-facing of the camera and higher oblique-angle flight paths on Cirlegrammetry missions. Overall, Circlegrammetry emerges as a promising method for precision agriculture applications by striking a balance between flight efficiency and reconstruction detail. Circlegrammetry with a 50 % overlap was demonstrated to be a comparable alternative to the smart oblique acquisition method. Future research should focus on optimizing overlap percentages and flight configurations to improve lower canopy coverage further and generalize these findings across diverse agricultural contexts.