## 1 Introduction  
As a new aerial survey platform, unmanned aerial vehicles (UAVs) have attracted increasing attention worldwide. Compared with methods based on satellite or airborne sensors, UAVs provide user-defined spatial and temporal resolution data at a relatively low cost, as well as flexible options for sensor use and data collection [1]. Images captured by UAVs and processed by structure-from-motion (SfM) photogrammetry are a combination of mature photogrammetry principles and modern computer vision technology [2] (hereafter UAV SfM). UAV SfM is widely used in Earth and Environmental Sciences to generate high-resolution topography (HRT) data [3, 4], including precision agriculture [5, 6], landslide monitoring [7, 8], coastal change [9, 10], and glacier dynamics [11, 12]. Georeferencing is the process of referencing the results of bundle adjustment (BA) and photogrammetric processes to a specific coordinate system [13]. During bundle adjustment (BA), ground control point (GCP) coordinates on the ground are provided and measured in the images (indirect georeferencing) or known external elements of the images are directly used (direct georeferencing) [14]. Direct georeferencing requires cm-level positioning accuracy of the UAV, obtained by difference data. GCP field deployment, surveying, and recognition in images may require a significant amount of time and cost, while direct georeferencing based on IMU and GNSS can quickly collect data and significantly improve work efficiency. However, these benefits are only valuable if the accuracy of the directly georeferenced topographic product meets the requirements of the application. First, the GNSS mobile receiver on the UAV achieves centimeter-level positioning accuracy by receiving difference data provided by a virtual reference station (VRS), and then adds the position data solved by the fusion of real-time kinematic (RTK) and post-processed kinematic (PPK) into the BA process. Direct georeferencing requires obtaining the coordinates of a GNSS receiver at the exact moment the image is acquired, although RTK can provide high-accuracy single-point positioning. However, there might be distortions in signals from satellite constellations and interruptions in RTK connections for a fast-flying UAV. Fusion PPK technology can solve epoch data in the lockout period through a reverse Kalman filter to improve the fixed rate and positioning accuracy [15; 16]. Considering the rapid development of UAV technology, it is necessary to evaluate the accuracy of UAV direct georeferencing methods with GNSS RTK/PPK technology. Many studies have evaluated the technology based on measured checkpoints on the ground. [PERSON] et al. evaluated the data of a farm and showed that the horizontal and vertical _RMSE_ of direct georeferencing were no more than 0.256 and 0.238 m, respectively [17]. [PERSON] et al. obtained data with a GSD of 10-20 cm in an area over tens of square kilometers and verified that the accuracy and precision (repeatability) of direct georeferencing were better than \(\pm\)30 and \(\pm\)8 cm, respectively, at 95% _RMSE_[18]. In the other two studies, the vertical _RMSE_ did not exceed 10 and 20 cm, respectively [19; 20]. The accuracy of the vertical direction is not always able to meet the requirements, and the accuracy can only reach the meter level in some studies [21; 22]. [PERSON] obtained a vertical _RMSE_ of 40 cm using an image of 0.7 cm GSD [23]. [PERSON] compared direct and indirect georeferencing methods, and recommended using GCPs where high accuracy is required [24]. The final product quality mainly depends on camera specifications, GCP configuration (accuracy, density and distribution), flight parameters (image overlap, GSD, etc. ), land cover and terrain complexity, processing software, and flight platform (fixed wing or rotor wing). Measuring GCP is a time-consuming task, so a balance between appropriate accuracy and efficiency is needed.