Accuracy of forest road digital terrain models captured using airborne and mobile light detection and ranging technology and photogrammetry

• Autorzy: Kardoš Miroslav , Borowski Łukasz , Sackov Ivan , Tomaštík Julián , Čurila Daniel , Maciuk Kamil , Ferencík Michal , Basista Izabela

Identyfikatory

DOI

10.24425/agg.2025.154149

• Języki publikacji: EN

Abstrakty

EN

The evaluation of the accuracy of generated DEMs using three remote sensing techniques on three types of forest road surfaces was performed. As a sample data, we used the forest road constructed from asphalt, concrete road slabs, and paving stones located in Víglaš, Central Slovakia.We evaluated the vertical accuracy of the DEMs produced by mobile laser scanning (MLS, Leica Pegasus, 840 pts/m2, airborne laser scanning (ALS, Leica ALS 70, 9 pts/m2, and aerial photogrammetry (AP, Leica RCD 30, 5 pts/m2. DEMs were generated in ArcGIS with a final resolution of 0.5m using the IDW method. The accuracy of DEMs was evaluated with the reference dataset on 700 check points. Regarding road surface capture quality, terrain generation, and point density, the MLS method dominates. It provides the RMSE values in range of ± 0.01 m to ± 0.03 m. The ALS method provided balanced RMSE results irrespective of surface type (RMSE ± 0.04 m to ± 0.05 m). The AP has the highest variability on all surface types (RMSE ± 0.12 m to ± 0.22 m). For AP, 0the decimeter-level accuracy is not sufficient for construction and maintenance purposes. This method provided the largest blunders at the road parts closest to the trees. ALS, with its ability to partially penetrate the forest canopy, can provide complex information about forest roads for inventory purposes. MLS provided the best spatial accuracy, enabling both construction and maintenance works. In any case, the advantage is that these data types can be combined.

Słowa kluczowe

EN

mobile laser scanning; digital elevation model; photogrammetry; forest road; airborne laser scanning

PL

skanowanie laserowe; numeryczny model terenu; fotogrametria

• Wydawca: Komitet Geodezji PAN
• Czasopismo: Advances in Geodesy and Geoinformation
• Rocznik: 2025
• Tom: Vol. 74, no. 1
• Strony: art. no. e65, 2025
• Opis fizyczny: Bibliogr. 37 poz., fot., rys., tab., wykr.

Twórcy

autor

Kardoš Miroslav

• Technical University Zvolen, Zvolen, Slovakia

• https://orcid.org/0000-0002-9458-5040

autor

Borowski Łukasz

• University of the National Education Commission, Krakow, Poland

• https://orcid.org/0000-0001-7356-5377

autor

Sackov Ivan

• National Forest Centre, Zvolen, Slovakia

• https://orcid.org/0000-0001-8379-5635

autor

Tomaštík Julián

• Technical University Zvolen, Zvolen, Slovakia

• https://orcid.org/0000-0001-6691-8357

autor

Čurila Daniel

• Technical University Zvolen, Zvolen, Slovakia

• https://orcid.org/0009-0005-9275-7418

autor

Maciuk Kamil

• AGH University of Krakow, Krakow, Poland

• https://orcid.org/0000-0001-5514-8510

autor

Ferencík Michal

• Technical University Zvolen, Zvolen, Slovakia

• https://orcid.org/0000-0002-2676-1292

autor

Basista Izabela

• AGH University of Krakow, Krakow, Poland

• https://orcid.org/0000-0002-0820-5380

Bibliografia

• 1. Apollo, M., and Andreychouk, V. (2020). Trampling Intensity and Vegetation Response and Recovery according to Altitude: An Experimental Study from the Himalayan Miyar Valley. Resources, 9, 98. DOI: 10.3390/resources9080098.
• 2. Apollo, M., Jakubiak, M., Nistor, S. et al. (2023). Geodata in science – a review of selected scientific fields. Acta Scientiarum Polonorum Formatio Circumiectus, 22, 17–40. DOI:10.15576/ASP.FC/2023.22.2.02.
• 3. Azizi, Z., Najafi, A., and Sadeghian, S. (2014). Forest Road Detection Using LiDAR Data. J. Forestry Res., 25. DOI: 10.1007/s11676-014-0544-0.
• 4. Balenovic, I., Gasparovic, M., Anita, S.M. et al. (2018). Accuracy Assessment of Digital Terrain Models of Lowland Pedunculate Oak Forests Derived from Airborne Laser Scanning and Photogrammetry. Croatian J. Forest Engineer., 39.
• 5. Botes, D. (2013). Accuracy assessment: Mobile laser scanning versus competing methods. The South African Surveying and Geomatics Indaba (SASGI) Proceedings, Ekurhuleni, South Africa 16.
• 6. Botes, D., and Geomatics, G. (2013). Accuracy assessment: Mobile laser scanning versus competing methods.
• 7. Buján, S., Guerra, J., González-Ferreiro, E. et al. (2021). Forest Road Detection Using LiDAR Data and Hybrid Classification. Remote Sens., 13, 393. DOI: 10.3390/rs13030393.
• 8. Cateanu, M., and Arcadie, C. (2021). The Effect of LiDAR Sampling Density on DTM Accuracy for Areas with Heavy Forest Cover. Forests, 12. DOI: 10.3390/f12030265.
• 9. David, N., Mallet, C., Pons, T. et al. (2009). Pathway detection and geometrical description from ALS data in forested moutaneous area. In: Bretar F, Pierrot-Deseilligny M, Vosselman G (Eds) Laser scanning, IAPRS, Paris, France, September 1-2, 38, 242–247.
• 10. Dudáková, Z., Ferencík, M., Allman, M. et al. (2022). Who Uses Forest Roads? Has the COVID-19 Pandemics Affected Their Recreational Usage? Case Study from Central Slovakia. Forests, 13, 458. DOI: 10.3390/f13030458.
• 11. Ferencík, M., Kardoš, M., Allman, M. et al. (2019). Detection of forest road damage using mobile laser profilometry. Comput. Electron. Agric., 166, 105010. DOI: 10.1016/j.compag.2019.105010.
• 12. Ferraz, A., Mallet, C., and Chehata, N. (2016). Large-scale road detection in forested mountainous areas using airborne topographic lidar data. ISPRS J. Photogram. Remote Sens., 112, 23–36. DOI:10.1016/j.isprsjprs.2015.12.002.
• 13. Fidelus-Orzechowska, J., Strzyzowski, D., and Zelazny, M. (2018). The geomorphic activity of forest roads and its dependencies in the Tatra Mountains. Geografiska Annaler: Series A, Physical Geography, 100, 59–74. DOI: 10.1080/04353676.2017.1376585.
• 14. Gil, A.L., Núñez-Casillas, L., Isenburg, M. et al. (2013). A comparison between LiDAR and photogrammetry digital terrain models in a forest area on Tenerife Island. Canadian J. Remote Sens., 39, 396–409. DOI: 10.5589/m13-047.
• 15. Hobi, M.L., and Ginzler, C. (2012). Accuracy assessment of digital surface models based on WorldView-2 and ADS80 stereo remote sensing data. Sensors, 12, 6347–6368. DOI: 10.3390/s120506347.
• 16. Hofmann, S., and Brenner, C. (2016).Accuracy assessment of mobile mapping point clouds using the existing environment as terrestrial reference. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B1, 601–608. DOI: 10.5194/isprsarchives-XLI-B1-601-2016.
• 17. Höhle, J., and Potuckova, M. (2011). Assessment of the quality of Digital Terrain Models. Official Publication: EuroSDR.
• 18. Hruza, P., Mikita, T., Tyagur, N. et al. (2018). Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing. Remote Sens., 10, 492. DOI: 10.3390/rs10040492.
• 19. Hunt, L.M., and Hosegood, S. (2008). The effectiveness of signs at restricting vehicle traffic: a case of seasonal closures on forest access roads. Canadian J.Forest Res., 38, 2306–2312.
• 20. Hyyppä, H., Yu, X., Hyyppä, J. et al. (2004). Factors Affecting the Quality of DTM Generation in Forested Areas. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 36.
• 21. Juško, V., Sedmák, R., and Kúdela, P. (2022). Siltation of Small Water Reservoir under Climate Change: A Case Study from Forested Mountain Landscape of Western Carpathians, Slovakia. Water, 14, 2606.
• 22. Kardoš, M., Sackov, I., Tomaštík, J. et al. (2024). Elevation Accuracy of Forest Road Maps Derived from Aerial Imaging, Airborne Laser Scanning and Mobile Laser Scanning Data. Forests, 15, 840. DOI:10.3390/f15050840.
• 23. Kukko, A., Kaartinen, H., Hyyppä, J. et al. (2012). Multiplatform Mobile Laser Scanning: Usability and Performance. Sensors, 12, 11712-11733. DOI: 10.3390/s120911712.
• 24. Kweon, H., Seo, J.I., and Lee, J.-W. (2020). Assessing the Applicability of Mobile Laser Scanning for Mapping Forest Roads in the Republic of Korea. Remote Sens., 12, 1502. DOI: 10.3390/rs12091502.
• 25. Lehtomäki, M., Jaakkola, A., Hyyppä, J. et al. (2010). Detection of Vertical Pole-Like Objects in a Road Environment Using Vehicle-Based Laser Scanning Data. Remote Sens., 2, 641–664. DOI:10.3390/rs2030641.
• 26. Maciuk, K., Apollo, M., Mostowska, J. et al. (2021). Altitude on Cartographic Materials and Its Correction According to New Measurement Techniques. Remote Sens., 13, 444. DOI: 10.3390/rs13030444.
• 27. Morley, I., Coops, N., Roussel, J.-R. et al. (2023). Updating forest road networks using single photon LiDAR in northern Forest environments. Forestry: An Int. J. Forest Res. DOI: 10.1093/forestry/cpad021.
• 28. Poreba, M., and Goulette, F. (2013). Line Segment-based Approach for Accuracy Assessment of MLS point clouds in Urban Areas.
• 29. Rahmayudi, A., and Rizaldy, A. (2016). Comparison of semiautomatic DTM from image matching with DTM from LIDAR. ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B3, 373–380. DOI: 10.5194/isprsarchives-XLI-B3-373-2016.
• 30. Sackov, I., and Kardoš, M. (2014). Forest delineation based on LiDAR data and vertical accuracy of the terrain model in forest and non-forest area. Ann. Forest Res., 1. DOI: 10.15287/afr.2014.169.
• 31. Skaloud, J., and Schaer, P. (2012). Automated Assessment of Digital Terrain Models Derived From Airborne Laser Scanning. Photogrammetrie – Fernerkundung – Geoinformation, 105–114. DOI:10.1127/1432-8364/2012/0105.
• 32. Su, J., and Bork, E. (2006). Influence of Vegetation, Slope, and Lidar Sampling Angle on DEM Accuracy. Photogr. Eng. Remote Sens., 72, 1265–1274. DOI: 10.14358/PERS.72.11.1265.
• 33. Suleymanoglu, B., Gurturk, M., Yilmaz, Y. et al. (2023). Comparison of Unmanned Aerial Vehicle-LiDAR and Image-Based Mobile Mapping System for Assessing Road Geometry Parameters via Digital Terrain Models. Trans. Res. Record, 2677, 617–632. DOI: 10.1177/03611981231157730.
• 34. White, R.A., Dietterick, B.C., Mastin, T. et al. (2010). Forest Roads Mapped Using LiDAR in Steep Forested Terrain. Remote Sens., 2, 1120–1141. DOI: 10.3390/rs2041120.
• 35. Wolf, R.P., Dewitt, A.B., and Wilkinson, E.B. (2014). Elements of Photogrammetry with Applications in GIS. 4th Edition. (In Ed.) McGraw-Hill Education.
• 36. Xu, S., Cheng, P., Zhang, Y. et al. (2015). Error Analysis and Accuracy Assessment of Mobile Laser Scanning System. Open Automation and Control Systems J., 7, 485–495. DOI: 10.2174/1874444301507010485.
• 37. Yu, X., Hyyppä, H., Kaartinen, H. et al. (2005). Applicability of first pulse derived digital terrain models for boreal forest studies. ISPRS WG III/3, III/4, V/3 Workshop “Laser scanning 2005”, Enschede, the Netherlands, 97–102.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025)