Szczegóły publikacji
Opis bibliograficzny
Accuracy of forest road Digital Terrain Models captured using Airborne and Mobile Light Detection and Ranging Technology and Photogrammetry / Miroslav Kardoš, Łukasz Borowski, Ivan Sačkov, Julián Tomaštík, Daniel Čurila, Kamil MACIUK, Michal Ferenčík, Izabela BASISTA // Advances in Geodesy and Geoinformation [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2720-7242. — 2025 — vol. 74 no. 1 art. no. e65, s. 1-17. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 15-17, Abstr. — Publikacja dostępna online od: 2025-06-17
Autorzy (8)
- Kardoš Miroslav
- Borowski Łukasz
- Sačkov Ivan
- Tomaštík Julián
- Čurila Daniel
- AGHMaciuk Kamil
- Ferenčík Michal
- AGHBasista Izabela
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 160591 |
|---|---|
| Data dodania do BaDAP | 2025-06-27 |
| Tekst źródłowy | URL |
| DOI | 10.24425/agg.2025.154149 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Geodesy and Cartography (Warsaw) |
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.
