New Possibilities of Field Data Survey in Forest Road Design
Abstract
1. Introduction
- The classical method (using theodolites, levels, and inclinometers);
- The modern method (based on total stations and GNSSs).
2. Materials and Methods
2.1. Research Area
2.2. Data Collection
2.2.1. Classical Method of Measurement
2.2.2. Modern Method of Measurement
2.2.3. Experimental Method of Measurement
- At a height of 60 m with the terrain follow function disabled (60NF);
- At a height of 70 m with the terrain follow function disabled (70NF);
- At a height of 70 m with terrain follow function enabled (70F);
- At a height of 90 m with terrain follow function enabled (90F).
2.3. Data Processing
- 60NF digital terrain model (DTM60NF);
- 70NF digital terrain model (DTM70NF);
- 70F digital terrain model (DTM70F);
- 90F digital terrain model (DTM90F).
3. Results
4. Discussion
5. Conclusions
- At field points with higher stations, values recorded using the classical survey method (with a theodolite and a level) and a total station show an accumulation of errors due to an increased number of changes in the instrument position. By reducing the number of instrument stations, errors can be reduced. Unfortunately, in forest conditions and when surveying complex terrains, this condition cannot always be met.
- The UAV SfM provides data with high spatial accuracies. Spatial accuracy is influenced by vegetation, i.e., biomass on the ground. Terrain follow flight image-based DTMs achieve greater spatial accuracy than those without the flight option.
- Although manual classification of point clouds can produce more accurate data, especially using the z coordinate, in some cases, it can also cause less accurate DTMs than the one created based on automatic classifications. Such phenomena have been found in places where most of the point cloud has been erased.
- The ALS survey achieved a higher z-coordinate RMSE compared with that of the UAV SfM survey, even though it has a higher penetration of the tree canopy assembly and vegetation. The ALS z error was strongly influenced by the cross-terrain slope. The authors conclude that the tested lidar data can be used for forest road planning, while their use in design should be examined in further research.
- Although no differences were found between cross-terrain slopes recorded using different survey methods, further analyses and research on the applicability of field data collected via these methods need to be conducted and their impact on other forest road design processes needs to be tested.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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60NF | 70NF | 70F | 90F | |
---|---|---|---|---|
Flight altitude | 60 m | 70 m | 70 m | 90 m |
Terrain follow | No | No | Yes | Yes |
Number of aerial photographs | 827 | 666 | 692 | 414 |
Front/side overlap | 80/80% | 80/80% | 80/80% | 80/80% |
Area | 24.20 ha | 26.54 ha | 27.89 ha | 29.64 ha |
GSD * | 2.32 [cm/pixel] | 2.66 [cm/pixel] | 2.28 [cm/pixel] | 2.86 [cm/pixel] |
DTM resolution | 5 × GSD (2.32 [cm/pixel]) | 5 × GSD (2.66 [cm/pixel]) | 5 × GSD (2.28 [cm/pixel]) | 5 × GSD (2.86 [cm/pixel]) |
Processing time (total) | 6 h 22 min | 4 h 42 min | 5 h 54 min | 4 h 22 min |
Survey Method | Centerline Length (m) | Elevation Difference (m) Between First and Last IPs | Average Longitudinal Terrain Slope (%) |
---|---|---|---|
GNSS | 879.42 | 66.50 | 7.56 |
Classical | 880.51 | 66.70 | 7.57 |
Total station | 879.39 | 66.74 | 7.59 |
DTM60NF | 879.44 | 66.42 | 7.55 |
DTM70F | 879.48 | 66.46 | 7.56 |
DTM70MC | 879.48 | 66.45 | 7.56 |
DTM70NF | 879.55 | 66.37 | 7.55 |
DTM90F | 879.53 | 66.49 | 7.56 |
Coordinate | Classical Method (m) | Total Station (m) | DTM60NF (m) | DTM70F (m) | DTM70MC (m) | DTM70NF (m) | DTM90F (m) | DTMALS (m) * |
---|---|---|---|---|---|---|---|---|
x | 1.72 | 0.45 | 0.10 | 0.10 | 0.10 | 0.11 | 0.12 | / |
y | 1.58 | 0.28 | 0.09 | 0.09 | 0.09 | 0.09 | 0.09 | / |
z | 0.47 | 0.15 | 0.22 | 0.20 | 0.19 | 0.21 | 0.20 | 0.24 |
GNSS | Classical | Total Station | DTM60NF | DTM70F | DTM70MC | DTM70NF | DTM90F | DTMALS | |
---|---|---|---|---|---|---|---|---|---|
Average (%) | 31.58 | 31.31 | 31.64 | 32.13 | 32.15 | 32.15 | 32.11 | 32.13 | 31.94 |
Max (%) | 58.96 | 57.69 | 59.23 | 58.80 | 58.76 | 58.75 | 59.25 | 59.20 | 63.01 |
Min (%) | 1.14 | 2.19 | 0.89 | 1.11 | 1.25 | 1.30 | 1.39 | 1.58 | 3.23 |
Median (%) | 28.12 | 27.56 | 28.08 | 28.83 | 28.84 | 29.00 | 28.90 | 28.85 | 28.66 |
RMSE (%) | / | 3.12 | 0.27 | 1.87 | 1.80 | 1.77 | 1.81 | 1.81 | 2.11 |
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Lovrinčević, M.; Papa, I.; Janeš, D.; Hodak, L.; Pentek, T.; Đuka, A. New Possibilities of Field Data Survey in Forest Road Design. Sensors 2025, 25, 4192. https://doi.org/10.3390/s25134192
Lovrinčević M, Papa I, Janeš D, Hodak L, Pentek T, Đuka A. New Possibilities of Field Data Survey in Forest Road Design. Sensors. 2025; 25(13):4192. https://doi.org/10.3390/s25134192
Chicago/Turabian StyleLovrinčević, Mihael, Ivica Papa, David Janeš, Luka Hodak, Tibor Pentek, and Andreja Đuka. 2025. "New Possibilities of Field Data Survey in Forest Road Design" Sensors 25, no. 13: 4192. https://doi.org/10.3390/s25134192
APA StyleLovrinčević, M., Papa, I., Janeš, D., Hodak, L., Pentek, T., & Đuka, A. (2025). New Possibilities of Field Data Survey in Forest Road Design. Sensors, 25(13), 4192. https://doi.org/10.3390/s25134192