Abstract. Technological improvement of Unmanned Aerial Vehicles (UAVs) and computer vision algorithms, such as Structured-from-Motion (SfM) and Multi-view Stereo (MVS) have provided the possibility for high-resolution mapping and high-density point cloud generation using low-cost equipment and sensors. Orthomosaics and Digital Terrain Model (DTM) are the main digital products considering mapping purposes. Their quality is directly related to the sensors boarded on the UAV and data processing. Ground Control Points (GCPs) are used in the process of indirect georeferencing and also to model the lens distortions. The number of GCPs used in this process affects the positional accuracy of the final products. This study aims to determine the optimum number of GCPs to achieve high accuracy orthomosaics and DTM. To obtain this optimum number, an area of 3.85 ha was mapped with a low-cost UAV DJI Phantom 4 Advanced at 31 m flying height, lateral and longitudinal overlap of 90% and 80%, respectively, and using 22 checkpoints for quality assessment. For the experiments, different configuration were used both for the number of GCPs and for the use of self-calibration process or pre-calibrated camera IOP (Interior Orientation Parameters). The results show that for the flight configuration used in this work and for the mentioned UAV, a total of 5 GCPs, with pre-calibrated camera IOP, yields an accuracy of 0.023 m for X, 0.031 m for Y and 0.033 m for Z.

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Technological improvement in sensors and the use of computer vision algorithms made possible the generation of high accuracy mapping products (cm level) using data acquired by low-cost Unmanned Aerial Vehicles (UAV). However, the procedure to optimally set the aerial block configuration is not well understood for some users mainly due to the popularization of the UAV and its use by non-specialists. This study aims to contribute to this aspect, investigating and highlighting the influence of flight parameters, camera calibration and number of Ground Control Points (GCP) on generating digital terrain models and orthomosaic. To address this issue, several field experiments and data processing were carried out. The quality was assessed by calculating the Root Mean Square Error (RMSE) together with a bias evaluation (t-Student test at 90% confidence level). The results suggest that an optimum block configuration for accurate and unbiased products is achieved by surveying at rates of 80%/60% (forward and sidelap, respectively), with an average Ground Sample Distance (GSD) of around 1 cm at a flight height of 31 m, using a precalibrated camera and 5 GCP at least.