*4.3. Influential Forest Features*

Based on our analyses, LiDAR-derived tree height is the top feature that influence on the positioning accuracy of the low-cost GNSS receiver in movable RTK mode. Tree density is among top five influential features (Figure 6). The complexity of the forest structure causes multipath effects [69], which is one of the main sources of increasing positioning errors in forest. Tree's characteristics, such as height, volume, tree density and canopy may block or weaken the signals [70]. A closed canopy can cause cycle slips [63], which clogs the signals to reach the receivers. Our analyses demonstrated that the low-cost GNSS receiver continuously recorded the signals throughout the logging trails, and it was resistant against cycle slips effects. Conversely, the great majority of work has focused on the canopy cover [11,13,14,16,71–73] as the main factors that affect the positioning accuracy of the GNSS receivers. Nevertheless, no priority between the forest cover factors on the positioning accuracy of GNSS was reported in the research of Ordóñez Galán et al. [15], while our study shows that there is a distinct difference between the impacts of tree characteristic factors on the positioning accuracy of the GNSS receiver. Moreover, some earlier studies reported the higher impact of the broadleaved tree species on increasing the errors of positioning by the GNSS receiver [13,14]. Our research showed that the importance of the tree species is less than other tree characteristics. The influence of pine and mixture species is positive against the spruce and birch.

Using high-density LiDAR data enabled us to take into account precisely some features of tree characteristics that were less a focus of earlier studies, such as tree height or tree density, not in plot scale but over the entire surveyed logging trails. For example, due to limitations involved in using traditional methods to measure tree height, the preponderance of the studies focused instead on forest cover or forest type [13–16,64] as potential effective factors of tree characteristics to determine the positioning accuracy of GNSS receivers. We considered trees' characteristics inside an object, which is much more similar to the natural condition of a forest stand. Furthermore, we carried out the experiments in a season which the leaf of some tree species such as birch is almost off. Hence, canopy cover or tree species did show lower importance than tree height or tree density in the current research. Likewise, topographic conditions affect the signals and cause the multipath effects. Our study revealed that topography directions and elevation are among top five important features that determine the positioning accuracy of the low-cost GNSS receiver (Figure 6). Aspect and slope derived from the DTM showed higher importance than was shown by the corresponding features derived from the DSM. The high ability of DTM to visualise the morphology of the bare earth under the forest canopy [74], such as variations in slope directions and values, might be one reason for this difference. On the other hand, the high variation in the curvature of the forest canopy may lead to a higher influence of DSM-derived plan curvature and mean curvature when compared to the corresponding derivatives from the DTM. Although there is no holistic research about the impact of topographic conditions in forest environment, some studies verified significant impacts of terrain in non-forest environments on the positioning accuracy of the GNSS receivers [1,18]. Based on the PD plots, the positioning errors of the low-cost GNSS receiver increase in forest areas with tree height above 14 m, tree density above 30%, western topographic directions or high elevation (Figure 6). These thresholds are based on our results in southern Finland, and similar studies should be repeated to achieve fixed values over the Nordic region. The performance of the antenna, as a sky view, is presented for a specific measured position during our experiment in Figure 9. The number of satellites that are used in navigation with a valid fixed position in the eastern direction is higher than in the western direction. We can infer that the geometric location of the satellites and their signal qualities may cause that aspect to be one of the top features determining the accuracy of the positioning by the low-cost GNSS receiver. Lower fixing rates and position errors of GNSS on west aspects were reported by D'eon and Delparte [75]. However, they reported that the differences in these values between different directions were not significant. The effect of aspect and convex slopes on the odds of missing signals was reported in the forest as well. Zimmerman and Keefe [76] verified that the alert delay of GNSS in the west directions is higher than in the east directions, which increases the error of positioning under forest canopies.

In addition, our analyses indicated that the interaction of the conditioning features intensifies the positioning errors by the receiver (Figure 8). It seems that using extra antenna or geodetic antenna [29–31,35] may mitigate the impact of the forest structure or topographic conditions on the positioning errors of this type of low-cost GNSS receivers in forest environments.
