## 4 Discussion  
The results suggest that the Trimble R12 GNSS receiver, when mounted on a harvester, is capable of achieving a high level of positioning accuracy and availability, with 86% of the observations meeting the maximum horizontal accuracy of 8 mm. The spatial distribution of the classified positions is shown in Figure 4, while Table 2 provides an overview of the geometric quality of the GNSS signals used in determining the positions. The analysis of the geometric quality of the GNSS signals showed that the presence of a canopy impacts the performance of the Trimble R12, as indicated by larger values of GDOP, PDOP, VDOP, and HDOP. Despite these challenges, the RTK corrected Trimble R12 GNSS receiver mounted on the roof of the harvester still demonstrates a high level of positioning accuracy. The results of this study indicate that the existence of canopy cover has a significant effect on the positional accuracy of the Trimble R12 device. The mean canopy cover for 'Inaccurate' points was found to be higher (62.75%) than that for 'Accurate' points (39.51%). However, it is also noted that there were points with a correct positioning even with a high level of canopy cover of 86%. The study used a CHM to evaluate the impact of canopy cover on the positional accuracy. In this study, dense point clouds for the CHMs creation were acquired with UAV imagery, which may be laborious in operational use. Many countries have national laser scanning data available at point densities from 0.5 to several points per square meter, and further studies are needed to estimate how well these data can serve as a source for canopy cover and viewshed analysis. A simple linear regression was performed to predict the PDOP and the maximum possible deviation from the total station in northing or easting directions, both based on the canopy cover estimated from the CHM. Both regression equations were found to be significant with high R\({}^{2}\) values (0.735 for PDOP and 0.497 for maximum deviation). This indicates that the maximum deviation from the true position increased by 0.733 cm for each percentage increase in the canopy cover. These results suggest that canopy cover has a significant impact on the positional accuracy of the Trimble R12 device. It is thus necessary to consider this factor when using the device, and similar alike, in forestry operations under canopy cover. The study analyzed the impact of canopy cover on the positional accuracy of the Trimble R12 using a viewshed analysis of a DSM. The results showed that 'Inaccurate' points had a higher mean level of canopy cover than the 'Accurate' points. The canopy cover estimated from the viewshed analysis of the DSM was found to be a significant predictor of the PDOP and the maximum possible deviation from the true position in northing or easting directions. In addition, the number of satellites that were visible to the Trimble R12 was found to be significantly predicted by the percentage of canopy cover estimated through the viewshed analysis of the DSM. However, we did not analyze the visibility of each satellite available in the sky, and the consequential satellite geometry, at the time of the position observation. Such an analysis may provide further insight into the positioning degradation. The regression analysis revealed that the viewshed analysis of the DSM has a stronger relationship with accuracy (R\({}^{2}\) = 0.563) compared to the relationship between accuracy and the analysis of the canopy cover model (0.497). However, it should be noted that in the analysis of the canopy cover model, the potential impact of terrain slope and shadow on satellite visibility was not taken into consideration. While this factor may not have a significant effect on the specific environment under investigation, it could be of great importance in the broader context of the global industry. To address this limitation, we propose the use of the whole digital surface model (DSM) for evaluating the impact of canopy cover on accuracy.