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ŠUMARSKI LIST 11-12/2018 str. 17     <-- 17 -->        PDF

mind that the applicability of this method is limited to mostly flat terrains. In other words, the method might not perform well for mountainous areas characterized by steep terrain; not because of the method inefficiency but rather due to a very low density of photogrammetric data in such forested areas. However, the method is expected to be highly applicable to forests with mostly flat terrain (slopes <10°), similar to those that occupy ≈27% of a total forest area in Croatia (Ministry of Agriculture, 2016).
CONCLUSIONS
Zaključci
This research presented a novel automated method for detection and removal of elevation errors in a photogrammetric DTM for forest areas characterized by flat terrain. By combining slope and tangential curvature values of raster DTM in the open source Grass GIS software, the method automatically detected and removed the elevation errors in a practical, fast and costless fashion. The comparison with the highly accurate LiDAR DTM confirmed that the presented method successfully detected and eliminated the elevation errors from photogrammetrically derived DTM in a dense lowland forest, and consequently greatly improved its vertical accuracy. Although the application of the method is limited to mostly flat terrain, the findings of this research could be of immense importance to other studies that consider similar forested areas particularly in the countries where the highly accurate LiDAR DTM are still unavailable.
ACKNOWLEDGMENTS
ZAHVALA
This research has been fully supported by the Croatian Science Foundation under the project IP-2016-06-7686 “Retrieval of Information from Different Optical 3D Remote Sensing Sources for Use in Forest Inventory (3D-FORINVENT)”. The authors wish to thank the company Hrvatske vode, Zagreb, Croatia, for providing LiDAR data.
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