*4.4. The Application*

The new generation of harvesters is equipped with sensors, computers, and GNSS receivers that store big data obtained from the processed trees and machine parameters as a standard format of StanForD (Standard for Forest Data and communication) [3]. Despite the high capacity of these data for modelling forest productivity, the errors in positions significantly degrade the efficiency of these data [6–8]. This type of low-cost GNSS receiver can improve the accuracy, integrity, and continuity of positions for the harvesters, with a significant impact on increasing the efficiency of forest productivity maps to Improve the sustainability of future rotations and precision forestry. Moreover, understanding the influential features that affect the positioning accuracy of the low-cost GNSS devices contributes to developing algorithms for the correction of positioning errors

or for the selection of appropriate low-cost receivers or antennas to minimize the influence of environmental features on positioning accuracy during forest operations.

**Figure 9.** Sky view for a specific location for the antenna of u-blox ZED-F9P: (**a**) the quality of sky view and (**b**) the position of satellites that were used in navigation.

#### **5. Conclusions**

In this study, we presented a geographic object-based TreeNet approach to determine influential environmental features that affect the positioning accuracy of a newly developed, low-cost, high-precision GNSS receiver, u-blox ZED-F9P, in forests. The experiment concentrated on some logging trails in commercial forests in Southern Finland. The low-cost receiver showed reliable positioning accuracy when integrated with high-density LiDAR data in the forest. The TreeNet model showed a high performance for expressing features that determine the positioning accuracy of the low-cost receiver in the forest. A combination of features increased the positioning errors of the low-cost receiver, in which the most important feature was tree height and then the topographic features, such as elevation and slope direction over the study stands. In the current research, we merely used the standard patched antenna packed with the low-cost receiver. However, we suggest testing the efficiency of other types of antennas, e.g., geodetic-grade ones, or a combination of antennas with the low-cost receiver to improve the positioning accuracy in the forest environment.

**Author Contributions:** Conceptualization, O.A., J.U., A.L. and J.P.; methodology, O.A., J.U., A.L. and J.P.; data provision, J.U.; data preparation, O.A. and J.P.; software and programming, O.A. and J.P.; field investigation and sampling, O.A., J.U., A.L. and J.P.; visualization, O.A.; writing—original draft preparation, O.A.; writing—review and editing, J.U., A.L. and J.P.; supervision, J.U. and A.L.; project administration, J.U. All authors have read and agreed to the published version of the manuscript.

**Funding:** Open access funding provided by University of Helsinki. This work has been funded by the public-private partnership grant established for the professorship of forest operation and logistics at the University of Helsinki, grant number 7820148 and by the proof-of-concept-grant by the Faculty of Agriculture and Forestry, University of Helsinki, grant number 78004041.

**Acknowledgments:** We would like thank Pekka Huuhka for constructing the research sulky and Mikko Leinonen for assisting in the field operations. We would also like to express our gratitude to Finsilva Oyj for providing the access to their forest holdings and related forest inventory databases.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
