Accuracy of forest road Digital Terrain Models captured using Airborne and Mobile Light Detection and Ranging Technology and Photogrammetry

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.

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Publication Details

Journal
Advances in Geodesy and Geoinformation
Published
2025-06-17
DOI
https://doi.org/10.24425/agg.2025.154149
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
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article

Accuracy of forest road Digital Terrain Models captured using Airborne and Mobile Light Detection and Ranging Technology and Photogrammetry

Łukasz Borowski, Izabela Basista, Kamil Maciuk, Ivan Sačkov et al.
Advances in Geodesy and Geoinformation
Remote Sensing and LiDAR Applications
article

Accuracy of forest road Digital Terrain Models captured using Airborne and Mobile Light Detection and Ranging Technology and Photogrammetry

Łukasz Borowski, Izabela Basista, Kamil Maciuk, Ivan Sačkov, Julián Tomaštík, D. Curilă, Miroslav Kardoš, Michal Ferenčík
article en

Abstract

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.

Advances in Geodesy and Geoinformation
Jagiellonian University (PL), Technická univerzita vo Zvolene (SK), National Forest Centre (SK), AGH University of Krakow (PL)
Openalex Percentile: Top 87%
Remote Sensing and LiDAR Applications
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