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Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR

机译:RIEGL RiCOPTER无人机LiDAR得出的机盖高度和DBH与地面LiDAR的比较

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摘要

In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX®-1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Models (DTMs), Digital Surface Models (DSMs) and finally Canopy Height Models (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 cm higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 cm. We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).
机译:近年来,光检测和测距(LiDAR)尤其是陆地激光扫描(TLS)系统显示出通过提供空前的3D数据来革新森林结构特征的潜力。但是,载人机载激光扫描(ALS)需要昂贵的战役并产生相对较低的点密度,而TLS则需要大量劳动并且需要大量时间。介于两者之间的方式可能是无人飞行器(UAV)进行的激光扫描。在这项研究中,我们介绍了带有VUX ® -1UAV ALS系统的RIEGL RiCOPTER的初步结果和经验,并将其与经过良好测试的RIEGL VZ-400 TLS系统进行了比较。我们在两天内用两种系统扫描了相同的森林地块。我们从所得的点云中得出了数字地形模型(DTM),数字表面模型(DSM),最后是冠层高度模型(CHM)。在不同冠层条件下的五个样地中,ALS CHM平均高出11.5 cm。这表明TLS不能始终检测到树冠的顶部。此外,我们同时提取了58棵用于ALS和TLS的树的树干段,其中39棵可用于建模“乳房高度”(DBH)。 ALS DBH与TLS DBH具有高度一致性,相关系数为0.98,均方根误差为4.24 cm。我们得出的结论是,在研究的森林条件下,RiCOPTER在评估森林冠层高度和DBH方面具有与TLS相当的潜力。应当进行进一步的研究,以测试无人飞行器的LiDAR,以对整个树木进行显式3D建模,以估计树木的体积,然后估算地上生物量(AGB)。

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