International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 575–582, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-575-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 575–582, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-575-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  21 Aug 2020

21 Aug 2020

COMPARING THE GENERATION OF DTM IN A FOREST ECOSYSTEM USING TLS, ALS AND UAV-DAP, AND DIFFERENT SOFTWARE TOOLS

P. Crespo-Peremarch, J. Torralba, J. P. Carbonell-Rivera, and L. A. Ruiz P. Crespo-Peremarch et al.
  • Geo-Environmental Cartography and Remote Sensing Group (CGAT), Department of Cartographic Engineering, Geodesy and Photogrammetry, Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain

Keywords: Digital Terrain Model, Terrestrial Laser Scanning, Airborne Laser Scanning, Unmanned Aerial Vehicle, LiDAR, LAStools, FUSION/LDV

Abstract. Remote sensing and photogrammetry techniques have demonstrated to be an important tool for the characterization of forest ecosystems. Nonetheless, the use of these techniques requires an accurate digital terrain model (DTM) for the height normalization procedure, which is a key step prior to any further analyses. In this manuscript, we assess the extraction of the DTM for different techniques (airborne laser scanning: ALS, terrestrial laser scanning: TLS, and digital aerial photogrammetry in unmanned aerial vehicle: UAV-DAP), processing tools with different algorithms (FUSION/LDV© and LAStools©), algorithm parameters, and plot characteristics (canopy and shrub cover, and terrain slope). To do this, we compare the resulting DTMs with one used as reference and extracted from classic surveying measurements. Our results demonstrate, firstly, that ALS and reference DTMs are similar in the different scenarios, except for steep slopes. Secondly, TLS DTMs are slightly less accurate than those extracted for ALS, since items such as trunks and shrubs cause a great occlusion due to the proximity of the instrument, and some of the points filtered as ground correspond to these items as well, therefore a finer setting of algorithm parameters is required. Lastly, DTMs extracted for UAV-DAP in dense canopy scenarios have a low accuracy, however, accuracy may be enhanced by modifying the processing tool and algorithm parameters. An accurate DTM is essential for further forestry applications, therefore, to know how to take advantage of the available data to obtain the most accurate DTM is also fundamental.