Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis (Jan 2016)

Monitoring of Forest Hauling Roads Wearing Course Damage using Unmanned Aerial Systems

  • Petr Hrůza,
  • Tomáš Mikita,
  • Přemysl Janata

DOI
https://doi.org/10.11118/actaun201664051537
Journal volume & issue
Vol. 64, no. 5
pp. 1537 – 1546

Abstract

Read online

Currently, a large part of the forest roads that were built using the bituminous surface technology in the second half of the last century have been worn out. This means that forest owners and forest managers urgently need to determine the amount and extent of this damage and establish a suitable repair plan, which demands both time and staff. The aim of the study is to verify whether it is possible, and with what precision, to detect the damage of the wearing course by means of unmanned aerial systems, which would facilitate and accelerate this process and possibly make it cheaper. A 3D model of a forest road was created using photos of the current state of a damaged part of a forest road. The aerial photographs were taken by an unmanned aircraft. To verify the accuracy of the model, cross sections of the road surface were surveyed tachymetrically and compared with the cross sections created in the 3D model in ArcMap, from photogrammetric pointcloud using aerial photographs from the unmanned aircraft. The RMSE of the values of the control points in the 3D model cross sections compared to the values of the points in the tachymetric measurement of the cross sections reached to within 0.0198 m. The results of the tested road section showed that the unmanned aerial systems can be used to detect the forest road surface damage with the difference in accuracy being up to 2 cm compared with the accuracy of the current tachymetric methods. Based on the results we can conclude that the used method is appropriate for detailed monitoring of the condition of the asphalt wearing course of forest roads and allows for a precise and objective localization and quantification of damage.

Keywords