Abstract
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.
Highlights
And 2, with the following information: Ground Control Points (GCPs) is the number of ground control points used, CP is the number of check-points used, Root Mean Square Error (RMSE) measured in meters for each component (X, Y and Z), μ is the median in meters, σ is the standard deviation in meters, and B (Y for biased and N for unbiased results)
This paper presented a positional evaluation of generated Digital Terrain Model (DTM) and orthomosaic based on Unmanned Aerial Vehicles (UAVs) images acquired with a lowcost UAV DJI Phantom 4 Advanced
The authors determined the optimum number of GCPs by processing with self-calibration and fixed Interior Orientation Parameters (IOP) with 0, 3, 4, 5, 8 and 10 GCP
Summary
The collection of geospatial data for 3D mapping is conducted using conventional survey methods by using GNSS (Global Navigation Satellite System) receivers and/ or total station, and recently, by the usage of RTK (Real Time Kinematics) GNSS technique. These methods are very costly, time consuming, and in some scenarios it is difficult to access the site area. The UAV is able to autonomously follow a pre-programmed flight plan, to take-off from a specific point, to fly over a desired area to take pictures, and to land in a defined region.
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