Forest roads, as a prerequisite for high-quality forest management, should be optimally distributed in order to avoid negative environmental impacts and to best fulfill their task. In the design phase of forest roads, it is necessary to know which factors influence most the volume of earthworks to enable the designer to best adapt to the terrain requirements. In this paper the impact of an average cross terrain slope and carriageway value of a forest road on cut and fill volume is analyzed. The research was carried out in the area of the management unit Trovrh–Kik, characterized by irregular terrain with slopes ranging between 27 and 58%, and on some micro locations even up to 84%. On eight forest roads, based on standard cross-section profiles, the influence of the average cross terrain slope and carriageway value (difference between ground level and grade level) of the forest road on the cut and fill volume per 1 m of the forest road route was analyzed. The obtained coefficients of determination indicate a strong correlation between the cut volume and carriageway value (R² = 0.6841), and a moderate correlation between the fill volume and carriageway value (R² = 0.5619). Unlike the influence of carriageway value on the cut and fill volume, the correlation between the cross terrain slope and fill volume is weak (R² = 0.2076) or moderate in the case of the cut volume (R² = 0.3167). On the basis of the analyzed standard cross-section profiles, it was determined that the carriageway value was 0.051 m, where the difference between the cut and fill volume was minimum and the average actual carriageway value was determined to be −0.09 m. It can be concluded that, on terrains with large and varying slopes, there is no unique model or terrain factor that could describe the earthworks required in the construction of a forest road. However, it is beyond doubt that the increase in the carriageway value and cross terrain slope caused the increase in the aforementioned volumes.

Planning in forestry should be based on accurate and reliable data. UAVs equipped with RGB cameras can enable fast and relatively cheap surveys, but their accuracy depends on many factors. Therefore, it is necessary to determine when UAVs can be used and when this type of survey gives data that does not reflect the true ground situation. This research analyzed the usability of a UAV, equipped with a RGB camera, for recording normal cross-sections and side ditch depths of the forest road in a lowland forest. The research was conducted in two time periods: during winter and spring, i.e., outside and during the vegetation season. DTMs of the area researched were created based on aerial photographs taken with the UAV, Z values of terrain points were read, and the depths of side ditches were calculated based on read Z values. The water depth in the side ditches and the vegetation height on the entire road body width were recorded to determine the influence of these two variables on the UAV survey error. Terrain points were recorded with the total station, which was the reference measurement method. An analysis of the obtained (read) DTM Z values revealed RMSE values of 10.09 cm for winter (outside vegetation) and 36.41 cm for spring (vegetation) UAV survey. The side ditch, calculated based on the DTM of the winter and spring periods of UAV recording, were statistically significantly different from the side ditch depths measured using the total station. Correcting the obtained data with water depth and vegetation height lowered the differences in Z values, as well as the ditch depths visible from ${RMSE}_Z$ (7.70 cm) for the winter UAV survey, with no statistically significant difference in side ditch depths. In the case of the correction of spring recording data, ${RMSE}_Z$ was smaller (23.41 cm) than before correction (36.41 cm), and the depth of the side ditches was still statistically significantly different. The authors conclude that water and ground vegetation can significantly affect UAV survey accuracy. In the winter period, side ditch depth measurement is possible in areas where water is not present. If water is present, manual measurement of water height and correction of obtained UAV data can improve data accuracy. On the other hand, spring or vegetation period UAV surveys are highly affected by ground vegetation height and the authors do not recommend surveys in that period.

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.

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.

This study compared oak butt-log volume estimations gained through terrestrial measurements in the forest stand with a remote approach using an unmanned aerial system (UAS) and photogrammetric post-processing. Terrestrial measurements were conducted in the lowland part of Croatia after a completed motor–manual final felling of a 140-year-old even-aged oak stand. Butt-logs’ volumes were estimated with four methods: the sectioning method and Huber’s, Smailan’s and Riecke–Newton’s methods. Measuring diameters and lengths and estimating volumes remotely were based on orthophotos using four different software: ArcGIS, QGIS, AutoCAD and Pix4D. Riecke–Newton’s method for volume estimation had the smallest relative bias of +1.74%, while for Huber’s method it was −8.07% and with Smailan’s method it was +21.23%. Log volume estimations gained remotely via ArcGIS and QGIS were, in the case of Huber’s method, at +3.63% relative bias, and in the case of Riecke–Newton’s method at +1.39% relative bias. Volume estimation using the sectioning method resulted in a total of 51.334 m³ for the whole sample, while the sectioning method performed with the help of AutoCAD resulted in 55.151 m³, i.e., +7.43% relative bias. Volume estimation of thirty oak butt-logs given by Pix4D software (version 4.8.4) resulted in +9.34% relative bias (56.134 m³). Comparing terrestrial measurements and the volume estimations based on them to those gained remotely showed a very high correlation in all cases. This study showed that using a UAS for log volume estimation surveys has the potential for broader use, especially after final felling in even-aged forests where the remaining trees in the stand would not block photogrammetric analysis.

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.