Research Article
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Comparison of Autonomous and Manual UAV Flights in Determining Forest Road Surface Deformations

Year 2022, , 77 - 84, 30.12.2022
https://doi.org/10.33904/ejfe.1206846

Abstract

The deterioration of the surface of forest roads is an important factor affecting the safe navigation of vehicles and traffic safety. In addition to traditional methods, automated methods are also used to determine the deterioration of the road surface. UAV systems, which are among the automated methods, are widely used to determine surface deformations with high accuracy. This study aimed to evaluate the advantages and disadvantages of two different flight modes of UAV, including autonomous flight and manual flight, in mapping road surface deformations. Within the scope of this study, the 50-meter section of the Type B forest road located in Kardüz Forest Management Chief (Düzce/Türkiye), was selected. For this study, first the pros and cons of the autonomous and manual flight data acquisition process were evaluated. Then, the photogrammetric data processing results were compared in terms of data size, with precision and accuracy. In addition, the deformation status on the surface within the selected road was determined using the average Z value differences obtained with two flight methods. The result of the study showed that, the number of images obtained from manual flights was 5.5 times higher than from autonomous flights and the flight time was taken four times longer. The average ground sampling distance of the orthophotos generated from two different light modes indicated that the manual flight mode provided seven times higher resolution than autonomous flight. Moreover, the results from the statistical tests for the two flight modes showed differences. When manual flights and autonomous flights are evaluated in terms of reducing the shadow effect, manual flights can be considered more advantageous. Furthermore, it was found that the dynamic mobility of erosion and accumulation on the road surface continued in time series in both flight methods.

Supporting Institution

Scientific and Technological Research Council of Turkey (TUBITAK)

Project Number

118O309

Thanks

We are very grateful to the Scientific and Technological Research Council of Turkey (TUBITAK) and we thank them for supporting this study (Project No. 118O309).

References

  • Akay, A.O., Akgul, M. Demir, M. 2018. Determınatıon of Temporal Changes on Forest Road Pavement Wıth Terrestrıal Laser Scanner. Fresenius Environmental Bulletin, 27 (3): 1437-1448.
  • Akgul, M., Yurtseven, H., Akburak, S., Demir, Cigizoglu, M. H. K., Ozturk, T., Eksi, M., Akay, A.O. 2017. Short Term Monitoring of Forest Road Pavement Degradation Using Terrestrial Laser Scanning. Measurement, 103: 283- 293.
  • Aydin, A., Turk, Y., Eker, R. 2019. Pros and Cons of the Manual and Autonomous UAV Flights in Mapping of the Forest Road Surface Deformations: Preliminary Results. 2nd International Symposium of Forest Engineering and Technologies (FETEC’19), p. 46-52, 4-6 September 2019, Tiran/Alabania.
  • Attoh-Okine, N., Adarkwa, O. 2013. ‘Pavement condition surveys–overview of current practices’. Phd thesis, University of Delaware, Newark, USA.
  • Bogus, S.M., Song, J., Waggerman, R., Lenke, L.R. 2010. Rank correlation method for evaluating manual pavement distress data variability. Journal of Infrastructure Systems, 16(1): 66-72.
  • Chang, K.T., Chang, J.R., Liu, J.K. 2005. Detection of pavement distresses using 3D laser scanning technology. In Proceedings of the 2005 ASCE international conference on computing in civil engineering (pp. 12-15).
  • Ciobanu, V., Alexandru, V., Saceanu S. 2012. Degradation Forms of Forests Gravel Road Roadways under heavy vehıcles used ın timber transport. Bulletin of the Transilvania University of Brasov, Series II. Forestry, Wood Industry, Agricultural Food Engineering,
  • Eker, R., Aydın, A., Hübl, J. 2018. Unmanned Aerial Vehicle (UAV)-Based Monitoring of a Landslide: Gallenzerkogel Landslide (Ybbs-Lower Austria) Case Study. Environ. Monit. Assess, 190 (28): 1-14.
  • GDF, 2011. Kardüz Forest Management Department Functional Forest Management Plan, Gölyaka Forest Management Directorate.
  • Herr, B. 2001. Calibration and Operation Of Pavement Profile Scanners. RPUG, Lake Tahoe.
  • Hrůza, P., Mikita, T., Janata, P. 2016. Monitoring of forest hauling roads wearing course damage using unmanned aerial systems. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 64(5): 1537-1546.
  • Huang, Y., Copenhaver, T., Hempel, P. 2011. Texas Department of Transportation 3D transverse profiling system for high-speed rut measurement. Journal of Infrastructure Systems, 19(2): 221-230.
  • Li, Q., Yao, M., Yao, X., Xu, B. 2009, A real-time 3D scanning system for pavement distortion inspection. Measurement Science and Technology, 21(1): 015702.
  • McGhee, K.H. 2004. Automated Pavement Distress Collection Techniques. Washington: Transportation Research Board.
  • Nasiri, M., Hojjati, S.M. 2012. Designing geometric specifications of main access road and its effect on pavement rutting. Annals of Biological Research, 3(5). 2491-2499.
  • Ozdamar, K., 2002. Statistical Data Analysis with Packet Programs, Kaan Bookstore Press, 4. Edition, Eskisehir. (in Turkish).
  • Săceanu, C. 2013. Forest Roads Degradation İn Correlation with Traffic Characteristics. In Proceedings of the Biennial International Symposium, Forest and Sustainable Development, (pp. 133-138).
  • Tighe, S., Haas, R., Ponniah, J. 2003. Life-Cycle Cost Analysis of Mitigating Reflective Cracking. Journal of the Transportation Research Board, 1823: 73-79.
  • Tsai, Y.J., Li, F., Wu, Y. 2013. A new rutting measurement method using emerging 3D line-laser-imaging system. International Journal of Pavement Research and Technology, 6(5): 667.
  • Turk, Y., Boz, F., Aydin, A., Eker, R. 2019a. Evaluation of UAV usage possibility in determining the forest road pavement degradation: preliminary results. 3rd International Engineering Research Symposium, September 05-07, 2019. Düzce Turkey, 630-633.
  • Turk, Y., Aydin, A., Eker, R. 2019b. Effectiveness of open top culverts in forest road deformations: preliminary results from a forest road section, Düzce-Turkey. 2nd International Symposium of Forest Engineering and Technologies, 04-06 September 2019 Tirana, pp.147-152.
  • Wang, H. 2005. Development of laser system to measure pavement rutting Doctoral Thesis, University of South Florida. 73 p.
  • Wang, K.C., Gong, W., Tracy, T., Nguyen, V. 2011. Automated survey of pavement distress based on 2D and 3D laser images (No. MBTC DOT 3023).
  • Yurtseven, H., Demir, M., Akgul, M., Akay, A.O. 2016. Comparison of Drone Based Photogrammetry and Terrestrial Laser Scanning for Forest Road Surface Modeling, 1st International Symposium of Forest Engineering and Technologies (FETEC 2016), Bursa, Turkey, vol.1, pp.22-22.
Year 2022, , 77 - 84, 30.12.2022
https://doi.org/10.33904/ejfe.1206846

Abstract

Project Number

118O309

References

  • Akay, A.O., Akgul, M. Demir, M. 2018. Determınatıon of Temporal Changes on Forest Road Pavement Wıth Terrestrıal Laser Scanner. Fresenius Environmental Bulletin, 27 (3): 1437-1448.
  • Akgul, M., Yurtseven, H., Akburak, S., Demir, Cigizoglu, M. H. K., Ozturk, T., Eksi, M., Akay, A.O. 2017. Short Term Monitoring of Forest Road Pavement Degradation Using Terrestrial Laser Scanning. Measurement, 103: 283- 293.
  • Aydin, A., Turk, Y., Eker, R. 2019. Pros and Cons of the Manual and Autonomous UAV Flights in Mapping of the Forest Road Surface Deformations: Preliminary Results. 2nd International Symposium of Forest Engineering and Technologies (FETEC’19), p. 46-52, 4-6 September 2019, Tiran/Alabania.
  • Attoh-Okine, N., Adarkwa, O. 2013. ‘Pavement condition surveys–overview of current practices’. Phd thesis, University of Delaware, Newark, USA.
  • Bogus, S.M., Song, J., Waggerman, R., Lenke, L.R. 2010. Rank correlation method for evaluating manual pavement distress data variability. Journal of Infrastructure Systems, 16(1): 66-72.
  • Chang, K.T., Chang, J.R., Liu, J.K. 2005. Detection of pavement distresses using 3D laser scanning technology. In Proceedings of the 2005 ASCE international conference on computing in civil engineering (pp. 12-15).
  • Ciobanu, V., Alexandru, V., Saceanu S. 2012. Degradation Forms of Forests Gravel Road Roadways under heavy vehıcles used ın timber transport. Bulletin of the Transilvania University of Brasov, Series II. Forestry, Wood Industry, Agricultural Food Engineering,
  • Eker, R., Aydın, A., Hübl, J. 2018. Unmanned Aerial Vehicle (UAV)-Based Monitoring of a Landslide: Gallenzerkogel Landslide (Ybbs-Lower Austria) Case Study. Environ. Monit. Assess, 190 (28): 1-14.
  • GDF, 2011. Kardüz Forest Management Department Functional Forest Management Plan, Gölyaka Forest Management Directorate.
  • Herr, B. 2001. Calibration and Operation Of Pavement Profile Scanners. RPUG, Lake Tahoe.
  • Hrůza, P., Mikita, T., Janata, P. 2016. Monitoring of forest hauling roads wearing course damage using unmanned aerial systems. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 64(5): 1537-1546.
  • Huang, Y., Copenhaver, T., Hempel, P. 2011. Texas Department of Transportation 3D transverse profiling system for high-speed rut measurement. Journal of Infrastructure Systems, 19(2): 221-230.
  • Li, Q., Yao, M., Yao, X., Xu, B. 2009, A real-time 3D scanning system for pavement distortion inspection. Measurement Science and Technology, 21(1): 015702.
  • McGhee, K.H. 2004. Automated Pavement Distress Collection Techniques. Washington: Transportation Research Board.
  • Nasiri, M., Hojjati, S.M. 2012. Designing geometric specifications of main access road and its effect on pavement rutting. Annals of Biological Research, 3(5). 2491-2499.
  • Ozdamar, K., 2002. Statistical Data Analysis with Packet Programs, Kaan Bookstore Press, 4. Edition, Eskisehir. (in Turkish).
  • Săceanu, C. 2013. Forest Roads Degradation İn Correlation with Traffic Characteristics. In Proceedings of the Biennial International Symposium, Forest and Sustainable Development, (pp. 133-138).
  • Tighe, S., Haas, R., Ponniah, J. 2003. Life-Cycle Cost Analysis of Mitigating Reflective Cracking. Journal of the Transportation Research Board, 1823: 73-79.
  • Tsai, Y.J., Li, F., Wu, Y. 2013. A new rutting measurement method using emerging 3D line-laser-imaging system. International Journal of Pavement Research and Technology, 6(5): 667.
  • Turk, Y., Boz, F., Aydin, A., Eker, R. 2019a. Evaluation of UAV usage possibility in determining the forest road pavement degradation: preliminary results. 3rd International Engineering Research Symposium, September 05-07, 2019. Düzce Turkey, 630-633.
  • Turk, Y., Aydin, A., Eker, R. 2019b. Effectiveness of open top culverts in forest road deformations: preliminary results from a forest road section, Düzce-Turkey. 2nd International Symposium of Forest Engineering and Technologies, 04-06 September 2019 Tirana, pp.147-152.
  • Wang, H. 2005. Development of laser system to measure pavement rutting Doctoral Thesis, University of South Florida. 73 p.
  • Wang, K.C., Gong, W., Tracy, T., Nguyen, V. 2011. Automated survey of pavement distress based on 2D and 3D laser images (No. MBTC DOT 3023).
  • Yurtseven, H., Demir, M., Akgul, M., Akay, A.O. 2016. Comparison of Drone Based Photogrammetry and Terrestrial Laser Scanning for Forest Road Surface Modeling, 1st International Symposium of Forest Engineering and Technologies (FETEC 2016), Bursa, Turkey, vol.1, pp.22-22.
There are 24 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Yılmaz Türk 0000-0001-7644-7886

Abdurrahim Aydın 0000-0002-6572-3395

Remzi Eker 0000-0002-9322-9634

Project Number 118O309
Publication Date December 30, 2022
Published in Issue Year 2022

Cite

APA Türk, Y., Aydın, A., & Eker, R. (2022). Comparison of Autonomous and Manual UAV Flights in Determining Forest Road Surface Deformations. European Journal of Forest Engineering, 8(2), 77-84. https://doi.org/10.33904/ejfe.1206846

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The works published in European Journal of Forest Engineering (EJFE) are licensed under a  Creative Commons Attribution-NonCommercial 4.0 International License.