In recent years, unmanned aerial vehicles (UAVs) have increased rapidly and successfully established themselves as a tool for the rapid collection of high-resolution images as baseline data in land cover studies and topographic mapping. In photogrammetry using the SfM-MVS method of processing captured images, indirect georeferencing of the digital data through ground control points (GCPs) is usually applied. But selecting, marking, and coordinating GCPs in hardto-reach terrains is time-consuming and sometimes dangerous or impossible. The main objective of this study is to evaluate the accuracy of high-resolution topographic data (HRTD) products of photogrammetric processing of PPK-directly georeferenced images by SfM-MVS workflow. Direct and indirect methods of georeferencing digital products are compared. The planimetric and vertical root mean square error (RMSE) in the position of the validation points were calculated by the differences between measured coordinates in dense point clouds, orthophoto mosaics, and terrain surfaces (DSM), and precisely measured coordinates of the validation points by GNSSRTK receivers. The analysis is based on a statistical evaluation of experimental data obtained from a TAROT X6-based hexacopter equipped with two different image sensor configurations: 1) Sony RX0 action camera and 2) Sony A6000 mirrorless camera, and 3) DJI Phantom 4 Pro quadcopter with integrated additional L1-GNSS module for direct georeferencing by PPKmethod. HRTD generation was performed with three block control configurations for each UAV: 1) Indirect georeferencing via GCP only, 2) PPK direct georeferencing without GCP, and 3) PPK georeferencing using one GCP. Our research showed that when using L1-GNSS onboard receivers for PPK-georeferencing without any GCPs, the point cloud's planimetric accuracy (RMSExy) was from 0.125 to 0.231 cm, depending on the UAV/camera configuration. However, two flight missions produced significant vertical offsets, most likely due to ionospheric disturbances affecting the resolution of phase cycle ambiguities in the single-frequency receivers used. When adding one control point in the PPK georeferencing method, the planimetric and vertical accuracy of the data is comparable to the indirect GCP referencing method. Furthermore, our results show that camera properties (i.e., focal length, resolution, sensor quality) affect the quality and accuracy of digital products. The HRTDs were also evaluated according to the ASPRS (American Photogrammetry and Remote Sensing Society) Standards for Accuracy of Digital Geospatial Data. Analyzing the accuracy of the HRTDs obtained with the experimental UAV/camera configurations for the test area, the present study shows that the PPK-SfM-MVS workflow can provide quality data with a centimeters accuracy of the photogrammetric products.

The mapping and three-dimensional modeling of mountain areas and the study of land cover change dynamics are current tasks in preserving and maintaining protected natural parks and forests. In this context, recent developments in digital photogrammetry using the SfM-MVS method to process captured imagery and the development of unmanned aerial systems (UAS) allow for reducing the costs, time, and the use of human resources and obtaining and repeatable 3D topographic data for moun-tainous regions. We will call this acquired 3D high-resolution topographic data (HRTD) 4D data in the context of an additional temporal component. The main objective of this study is to evaluate the applicability of PPK (Post-Processing Kinematic) direct georeferencing of images captured by UAVs and processed through the SfM-MVS method to obtain HRTDs for 4D land cover analysis. We analyze a 3D HRTD with an acquisition interval of two years for a mountain test area in Plana Mountain near Sofia. The test area has a diverse vegetation cover, including coniferous forest, grassland, hay meadows, shrubs, and single deciduous trees. We conducted multiple surveys of the test area with a budget PPK-UAV configuration (DJI Phantom 4 Pro with a single-frequency PPK-GNSS kit installed) from March 2020 to October 2022. Two autumn surveys from September 2020 and October 2022 were se-lected, which possess the most-good performance on numerical data accuracy. We performed 3D data analysis on 1) Assessment of the accuracy of PPK-SfM-MVS photogrammetry generated topographic data (3D clouds and DSM); 2) Investigation of the errors in the individual specific surfaces (for the individual isolated sections) using the M3C2 tool for comparing and evaluating dense point clouds; 3) Determining land cover changes in the demarcated areas using a surface of differences (DoD). Accuracy analysis showed that the PPK solution provides comparable accuracy (about RMSE3D = 0.067 m for the 2020 data, georeferencing (PPK+1GCP) and RMSE3D about 0.13 m for the 2022 data, georeferencing (PPK only)) like the GCP method. The multi-temporal topographic reconstructions based on UAV- PPK-SfM allowed us to quantify and qualitatively determine the land cover changes that occurred. The UAV-PPK-SfM workflow in the context of 4D land surface monitoring and the results suggested that even low-cost UAV-PPK systems can provide data suitable for measuring geomorphic change at the scale of the acquired data. The multi-temporal topographic reconstructions based on UAV- PPK-SfM allowed us to quantify and qualitatively determine the land cover changes that occurred. The UAV-PPK-SfM workflow in the context of 4D land surface monitoring and the results suggested that even low-cost UAV-PPK systems can provide data suitable for measuring geomorphic change at the scale of the acquired data.