J. For. Sci., 2018, 64(11):469-477 | DOI: 10.17221/87/2018-JFS

Study of the LiDAR accuracy in mapping forest road alignments and estimating the earthwork volumeOriginal Paper

Benyamin MATINNIA*, Aidin PARSAKHOO, Jahangir MOHAMADI, Shaban SHATAEE JOUIBARY
Department of Forestry, Faculty of Forest Science, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

Today, differential geographical position system and total station devices are improving the accuracy of positioning information, but in critical locations such as steep slopes and closed canopy cover, the device accuracy is limited. Moreover, field surveying in this technique is time-consuming and expensive. For this reason, remote sensing technique such as light detection and ranging (LiDAR) laser scanner should be used in field measurements. The objective of this study was to evaluate and compare precision and time expenditure of total station and airborne LiDAR in producing horizontal and vertical alignments and estimating earthwork volume of two proposed forest roads in a deciduous forest of Iran. To investigate this task, the geographical position of proposed forest roads were detected by differential geographical position system and then marked on land. Mentioned roads were taken again with Leica Total Station (LTS) on control points with same 5 m intervals from start point. Recent data served as a reference value for comparison with LiDAR measurements. The data were processed in Civil 3D, Fusion and Leica geo office software. Results showed that in comparison to field-surveyed routes by LTS, the LiDAR-derived routes exhibited a horizontal accuracy of 0.23 and 0.47 m and vertical accuracy of 0.31 and 0.66 m for road 1 and road 2, respectively. The LiDAR-derived sections every 1 m exhibited cut and fill accuracy of 2.39 and 3.18 m3 for road 1 and 2.98 and 5.60 m3 road 2, respectively. In this study, it was proved that the road project can be prepared faster by LiDAR than that of LTS. Therefore, high accuracy of road projection by LiDAR is useful for terrain analysis without the need for field reconnaissance.

Keywords: airborne LiDAR; Leica Total Station; mapping proposed road; accuracy estimation; deciduous forest canopy cover

Published: November 30, 2018  Show citation

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MATINNIA B, PARSAKHOO A, MOHAMADI J, SHATAEE JOUIBARY S. Study of the LiDAR accuracy in mapping forest road alignments and estimating the earthwork volume. J. For. Sci. 2018;64(11):469-477. doi: 10.17221/87/2018-JFS.
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    References

    1. Akay A.E. (2006): Minimizing total cost of forest roads with computer-aided design model. Sadhana - Academy Proceedings in Engineering Sciences, 31: 621-633. Go to original source...
    2. Alharthy A., Bethel J. (2004): Automated road extraction from LiDAR data. In: Bethel J. (ed.): Proceedings of the American Society of Photogrammetry and Remote Sensing Annual Conference, Anchorage, June 23-24, 2004: 51-58.
    3. Amo M., Martinez F., Torre M. (2006): Road extraction from aerial images using a region competition algorithm. IEEE Transactions on Image Processing, 15: 1192-1201. Go to original source... Go to PubMed...
    4. Azizi Z., Najafi A., Sadeghian S. (2014): Forest road detection using LiDAR data. Journal of Forestry Research, 25: 975-980. Go to original source...
    5. Chekole S.D. (2014): Surveying with GPS, total station and terrestrial laser scanner: A comparative study. [MSc Thesis.] Stockholm, School of Architecture and the Built Environment, KTH Royal Institute of Technology: 55.
    6. Clode S., Rottensteiner F., Kootsookos P., Zelniker E. (2007): Detection and vectorization of roads from LiDAR data. Photogrammetric Engineering and Remote Sensing, 73: 517-535. Go to original source...
    7. Coffin A.W. (2007): From roadkill to road ecology: A review of the ecological effects of roads. Journal of Transport Geography, 15: 396-406. Go to original source...
    8. Contreras M.A., Aracena P., Chung W. (2012): Improving accuracy in earthwork volume estimation for proposed forest roads using a high-resolution digital elevation model. Croation Journal of Forest Engineering, 33: 125-134.
    9. Coulter E., Chung W., Akay A., Sessions J. (2001): Forest road earthwork calculations for linear road segments using a height resolution digital terrain model generated from LiDAR data. In: Proceedings of the First International Precision Forestry Symposium, Seattle, June 17-20, 2001: 125-129.
    10. Craven M., Wing M.G. (2014): Applying airborne LiDAR for forested road geomatics. Scandinavian Journal of Forest Research, 29: 174-182. Go to original source...
    11. David N., Mallet C., Pons T., Chauve A., Bretar F. (2009): Pathway detection and geometrical description from ALS data in forested mountaneous area. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVIII (Part 3/W8): 242-247.
    12. Espinoza F., Owens R.E. (2007): Identifying roads and trails hidden under canopy using LiDAR. [MSc Thesis.] Monterey, Naval Postgraduate School: 25.
    13. Evans J.S., Hudak A.T., Faux R., Smith A.M.S. (2009): Discrete return LiDAR in natural resources: Recommendations for project planning, data processing, and deliverables. Remote Sensing, 1: 776-794. Go to original source...
    14. Ferraz A., Mallet C., Chehata N. (2016): Large-scale road detection in forested mountainous areas using airborne topographic lidar data. ISPRS Journal of Photogrammetry and Remote Sensing, 112: 23-36. Go to original source...
    15. Gomes-Pereira L.M., Janssen L.L.F. (1999): Suitability of laser data for DTM generation: A case study in the context of road planning and design. ISPRS Journal of Photogrammetry and Remote Sensing, 54: 244-253. Go to original source...
    16. Grote A., Heipke C., Rottensteiner F. (2012): Road network extraction in suburban areas. The Photogrammetric Record, 27: 8-28. Go to original source...
    17. He Y., Song Z., Liu Z. (2017): Updating highway asset inventory using airborne LiDAR. Measurement, 104: 132-141. Go to original source...
    18. Hickerson T.F. (1964): Route Location and Design. New York, McGraw-Hill: 634.
    19. Hinz S., Baumgartner A. (2003): Automatic extraction of urban road networks from multi-view aerial imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 58: 83-98. Go to original source...
    20. Hui Z., Hu Y., Jin S., Yevenyo Y.Z. (2016): Road centerline extraction from airborne LiDAR point cloud based on hierarchical fusion and optimization. ISPRS Journal of Photogrammetry and Remote Sensing, 118: 22-36. Go to original source...
    21. Ichihara K., Tanaka T., Sawaguchi I., Umeda S., Toyokawa K. (1996): The method for designing the profile of forest roads supported by genetic algorithm. Journal of Forestry Research, 1: 45-49. Go to original source...
    22. Krogstad F., Schiess P. (2004): The allure and pitfalls of using LiDAR topography in harvest and road design. In: Nelson J., Clark M. (eds): Proceedings of the Joint Conference of IUFRO 3.06 Forest Operations in Mountainous Conditions and the 12th International Mountain Logging Conference, Vancouver, June 13-16, 2004: 1-10.
    23. Lacoste C., Descombes X., Zerubia J. (2005): Point processes for unsupervised line network extraction in remote sensing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27: 1568-1579. Go to original source... Go to PubMed...
    24. Liu K., Sessions J. (1993): Preliminary planning of road systems using digital terrain models. Journal of Forest Engineering, 4: 27-32. Go to original source...
    25. Mayer H., Hinz S., Bacher U., Baltsavias E. (2006): A test of automatic road extraction approaches. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 36: 209-214.
    26. Mena J., Malpica J. (2005): An automatic method for road extraction in rural and semi-urban areas starting from high resolution satellite imagery. Pattern Recognition Letter, 26: 1201-1220. Go to original source...
    27. Mnih V., Hinton G. (2012): Learning to label aerial images from noisy data. In: Langford J., Pineau J. (eds): Proceedings of the 29th International Conference on Machine Learning, Edinburgh, June 26-July 1, 2012: 203-210.
    28. Reutebuch S.E., McGaughey R.J., Andersen H., Carson W. (2003): Accuracy of a high-resolution lidar terrain model under a conifer forest canopy. Canadian Journal of Remote Sensing, 29: 527-535. Go to original source...
    29. Robinson C., Duinker P., Beazley K. (2010): A conceptual framework for understanding, assessing, and mitigating ecological effects of forest roads. Environment Reviews, 18: 61-86. Go to original source...
    30. Saito M., Aruga K., Matsue K., Tasaka T. (2008): Development of the filtering technique of the intersection angle method using LiDAR data of the Funyu Experimental Forest. Journal of the Japan Forest Engineering, 22: 265-270.
    31. Satio M., Goshima M., Aruga K., Matsue K., Shuin Y., Taska T. (2013): Study of automatic forest road design model considering shallow landslides with LiDAR data of Funyu Experimental Forest. Croatian Journal of Forest Engineering, 34: 1-15.
    32. Sessions J., Wimer J., Costales F., Wing M. (2010): Engineering considerations in road assessment for biomass operations in steep terrain. Western Journal of Applied Forestry, 25: 144-153. Go to original source...
    33. Sidle R.C., Ziegler A.D. (2012): The dilemma of mountain roads. Nature Geoscience, 5: 437-438. Go to original source...
    34. Souleyrette R., Hallmark S., Pattnaik S., O'Brien M., Veneziano D. (2003): Grade and Cross Slope Estimation from LiDAR-based Surface Models. Ames, Midwest Transportation Consortium, Iowa State University: 73.
    35. Türetken E., Benmansour F., Andres B., Pfister H., Fua P. (2013): Reconstructing loopy curvilinear structures using integer programming. In: Le Borgne H., Moo Yi K., Karaman S., Tron R., Khan S. (eds): Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Portland, June 23-28, 2013: 1822-1829. Go to original source...
    36. Umeda S., Suzuki H., Yamaguchi S. (2007): Considerations in the construction of a spur road network. Journal of the Japan Forest Engineering Society, 22: 143-152.
    37. Veneziano D., Souleyrette R., Hallmark S. (2002): Elevation of LiDAR for highway planning, location and design. In: Zhou G., Kafatos M. (eds): Proceedings of the 15th William T. Pecora Memorial Remote Sensing Symposium/Landsatellite Information IV/ISPRS Commission I/FIEOS 2002 Conference, Denver, Nov 10-15, 2002: 10-22.
    38. White R.A., Dietterick B.C., Mastin T., Strohman R. (2010): Forest roads mapped using LiDAR in steeps forested terrain. Remote Sensing, 2: 1120-1141. Go to original source...
    39. Xiao L., Wang R., Dai B., Fang Y., Liu D., Wu T. (2017): Hybrid conditional random field based camera-LIDAR fusion for road detection. Information Sciences, 432: 543-558. Go to original source...
    40. Ziems M., Breitkopf U., Heipke C., Rottensteiner F. (2012): Multiple-model based verification of road data. ISPRS Annals of the Photogrammetry, Remote Sensing & Spatial Information Sciences, I-3: 329-334. Go to original source...

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