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Article

Assessment of Close-Range Remote Sensing Methods for DTM Estimation in a Lowland Deciduous Forest

1
Division for Forest Management and Forestry Economics, Croatian Forest Research Institute, Trnjanska cesta 35, HR-10000 Zagreb, Croatia
2
Chair of Photogrammetry and Remote Sensing, Faculty of Geodesy, University of Zagreb, Kačićceva 26, HR-10000 Zagreb, Croatia
3
The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430070, China
*
Author to whom correspondence should be addressed.
Academic Editor: Clement Atzberger
Remote Sens. 2021, 13(11), 2063; https://doi.org/10.3390/rs13112063
Received: 24 March 2021 / Revised: 14 May 2021 / Accepted: 21 May 2021 / Published: 24 May 2021
(This article belongs to the Special Issue Thematic Information Extraction and Application in Forests)
Digital terrain models (DTMs) are important for a variety of applications in geosciences as a valuable information source in forest management planning, forest inventory, hydrology, etc. Despite their value, a DTM in a forest area is typically lower quality due to inaccessibility and limited data sources that can be used in the forest environment. In this paper, we assessed the accuracy of close-range remote sensing techniques for DTM data collection. In total, four data sources were examined, i.e., handheld personal laser scanning (PLShh, GeoSLAM Horizon), terrestrial laser scanning (TLS, FARO S70), unmanned aerial vehicle (UAV) photogrammetry (UAVimage), and UAV laser scanning (ULS, LS Nano M8). Data were collected within six sample plots located in a lowland pedunculate oak forest. The reference data were of the highest quality available, i.e., total station measurements. After normality and outliers testing, both robust and non-robust statistics were calculated for all close-range remote sensing data sources. The results indicate that close-range remote sensing techniques are capable of achieving higher accuracy (root mean square error < 15 cm; normalized median absolute deviation < 10 cm) than airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) data that are generally understood to be the best data sources for DTM on a large scale. View Full-Text
Keywords: UAV photogrammetry; ULS; TLS; PLS; DTM UAV photogrammetry; ULS; TLS; PLS; DTM
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MDPI and ACS Style

Jurjević, L.; Gašparović, M.; Liang, X.; Balenović, I. Assessment of Close-Range Remote Sensing Methods for DTM Estimation in a Lowland Deciduous Forest. Remote Sens. 2021, 13, 2063. https://doi.org/10.3390/rs13112063

AMA Style

Jurjević L, Gašparović M, Liang X, Balenović I. Assessment of Close-Range Remote Sensing Methods for DTM Estimation in a Lowland Deciduous Forest. Remote Sensing. 2021; 13(11):2063. https://doi.org/10.3390/rs13112063

Chicago/Turabian Style

Jurjević, Luka, Mateo Gašparović, Xinlian Liang, and Ivan Balenović. 2021. "Assessment of Close-Range Remote Sensing Methods for DTM Estimation in a Lowland Deciduous Forest" Remote Sensing 13, no. 11: 2063. https://doi.org/10.3390/rs13112063

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