Rutting measurements are a significant part of scientific research on the impact of forest vehicles on the forest soils and damage to the forest transport infrastructure. Although photogrammetric methods of measurement or measurements based on LiDAR (light detection and ranging) data are increasingly being used for rutting measurements, the previous research conducted using these methods indicated the challenge of recording water-filled ruts. For this reason, it is necessary to define a reliable method of rutting field measurement in lowland forest stands characterized by a high level of groundwater that fills the ruts shortly after the passage of forest vehicles. This research analyzed the measurement accuracy using a total station and a GNSS RTK device with a CROPOS correction base in relation to the measuring rod that represented the reference method. Based on recorded and processed data, ruts are displayed in two ways: as net and as gross value of rut depth. The analysis of net rutting revealed a statistically significant difference between the calculated rut depths based on measurements with a GNSS RTK device and other methods. On average, the net rutting measured by the GNSS RTK device was 2.86 cm smaller than that of the reference method. When calculating the gross rutting, which consisted of the net rut depth and the bulge height, no statistically significant difference was found between the measurement methods used. Based on this result, the bulge height was also analyzed, and showed a statistically significant difference between the data recorded by the GNSS RTK device and other methods. It can be concluded that measuring the depth of ruts with a total station gives accurate data and represents the optimal modern field measurement method for the same or similar terrain conditions. In contrast, the GNSS RTK device, which constantly gives higher elevation points, can be used to measure gross rutting.

Field data, as the basis for planning and designing forest roads, must have high spatial accuracy. Classical (using a theodolite and a level) and modern (based on total stations and GNSSs) surveying methods are used in current field data survey for forest road design. This study analyzed the spatial accuracy of classical and modern surveying methods, the accuracy of spatial data recorded using a UAV equipped with an RGB camera at different flight altitudes, and the accuracy of lidar data of the Republic of Croatia. This study was conducted on a forest area where salvage logging was carried out, which enabled the use of a GNSS receiver in RTK mode as a reference method. The highest RMSE values of the spatial coordinates were recorded for measurements obtained with the classical surveying method (0.89 m) and a total station (0.33 m). The flight altitude of the UAV did not significantly affect the spatial error of the collected data, which ranged between 0.07 and 0.09 m. The cross-terrain slope, as one of the factors that significantly affect the amount of earthworks, did not differ statistically significantly between the methods. The ALS error was strongly influenced by the cross-terrain slope. The authors conclude that the new survey methods (SfM and lidar data) provide high-accuracy data but also draw attention to challenges in their use, such as vegetation and biomass on the ground.

This paper examines the energy potential of silver fir (Abies alba Mill) and Norway spruce (Picea abies (L.) Karst) trees across three tree crown defoliation degrees (TCDDs): healthy, severely defoliated (61–99%) and dead. The study was conducted in the area of the Forest Administration Delnice, Management Unit »Milanov vrh«, in the Republic of Croatia. Field measurements were conducted on 83 silver fir trees and 114 Norway spruce trees to determine the mass of live and dead branches per tree and to collect samples of wood, bark, main live and dead branches, and side live and dead branches (in total, 813) for further laboratory analyses. Further, differences in wood basic density, moisture content, ash content, net calorific value, and carbon, hydrogen, nitrogen, and sulfur content across TCDD classes were also determined. For both tree species, wood basic density across TCDDs decreased as follows: severely defoliated trees > healthy trees > dead trees. Regression analyses showed that the largest masses of branches occurred on healthy silver fir trees (R² = 0.48), followed by severely defoliated (R² = 0.41) and dead trees (R² = 0.46). The same trend in determined total branch mass per tree was observed for Norway spruce trees, where the coefficient of determination was highest for dead trees (R² = 0.72), followed by severely defoliated (R² = 0.69) and healthy (R² = 0.61) trees. A negative correlation between moisture content and TCDD class was observed for wood, bark, and live branches. The highest net calorific value was found for side live branches for both researched species, and only the net calorific value of side live branches of Norway spruce was statistically significantly different across TCDD classes. Overall, this study showed a negative impact of TCDD on the amount of available tree residues (branches) that could be utilized as a solid biofuel. Furthermore, the results of the laboratory analyses were ambiguous, increasing the complexity and heterogeneity of the wood material and underscoring the need for further investigation.