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

https://doi.org/10.17221/87/2018-JFSCitation:Matinnia B., Parsakhoo A., Mohamadi J., Shataee Jouibary S. (2018): Study of the LiDAR accuracy in mapping forest road alignments and estimating the earthwork volume. J. For. Sci., 64: 469-477.
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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.

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