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首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >Multitemporal terrestrial laser scanning point clouds for thaw subsidence observation at Arctic permafrost monitoring sites
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Multitemporal terrestrial laser scanning point clouds for thaw subsidence observation at Arctic permafrost monitoring sites

机译：北极永久冻土监测网站下解冻沉降观测的多立体陆地激光扫描点云

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This paper investigates different methods for quantifying thaw subsidence using terrestrial laser scanning (TLS) point clouds. Thaw subsidence is a slow (millimetre to centimetre per year) vertical displacement of the ground surface common in ice-rich permafrost-underlain landscapes. It is difficult to quantify thaw subsidence in tundra areas as they often lack stable reference frames. Also, there is no solid ground surface to serve as a basis for elevation measurements, due to a continuous moss-lichen cover. We investigate how an expert-driven method improves the accuracy of benchmark measurements at discrete locations within two sites using multitemporal TLS data of a 1-year period. Our method aggregates multiple experts' determination of the ground surface in 3D point clouds, collected in a web-based tool. We then compare this to the performance of a fully automated ground surface determination method. Lastly, we quantify ground surface displacement by directly computing multitemporal point cloud distances, thereby extending thaw subsidence observation to an area-based assessment. Using the expert-driven quantification as reference, we validate the other methods, including in-situ benchmark measurements from a conventional field survey. This study demonstrates that quantifying the ground surface using 3D point clouds is more accurate than the field survey method. The expert-driven method achieves an accuracy of 0.1 +/- 0.1 cm. Compared to this, in-situ benchmark measurements by single surveyors yield an accuracy of 0.4 +/- 1.5 cm. This difference between the two methods is important, considering an observed displacement of 1.4 cm at the sites. Thaw subsidence quantification with the fully automatic benchmark-based method achieves an accuracy of 0.2 +/- 0.5 cm and direct point cloud distance computation an accuracy of 0.2 +/- 0.9 cm. The range in accuracy is largely influenced by properties of vegetation structure at locations within the sites. The developed methods enable a link of automated quantification and expert judgement for transparent long-term monitoring of permafrost subsidence. (c) 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd
机译：本文研究了使用地面激光扫描（TLS）点云量化解冻沉降的不同方法。解冻沉降是一种缓慢的（毫米到每年厘米）耐冰的永久冻土危险景观的地面垂直位移。难以量化苔原地区的解冻沉降，因为它们通常缺乏稳定的参考框架。而且，由于连续的苔藓 - 地衣盖，没有实心的地面用作升高测量的基础。我们调查专家驱动的方法如何在使用1年期间的多立体TLS数据的两个站点内的离散位置提高基准测量的准确性。我们的方法在基于Web的工具中聚集了多个专家的3D点云中的地面的确定。然后，我们将其与全自动地面确定方法的性能进行比较。最后，我们通过直接计算多立体点云距离来量化地面位移，从而将解冻沉降观察扩展到基于区域的评估。使用专家驱动量化作为参考，我们验证了其他方法，包括来自传统现场调查的原位基准测量。本研究表明，使用3D点云量化地面比现场测量方法更准确。专家驱动的方法达到0.1 +/- 0.1厘米的精度。与此相比，单次测量仪的原位基准测量结果产生0.4 +/- 1.5厘米的精度。两种方法之间的这种差异很重要，考虑到在网站上观察到1.4厘米的位移。通过全自动基准的方法进行解冻沉降量化，精度为0.2 +/- 0.5厘米，直接云距离计算的精度为0.2 +/- 0.9厘米。精度的范围主要受到位点内位置的植被结构的性质的影响。开发方法使自动化量化和专家判断的联系能够透明的永久冻结沉降的透明长期监测。 （c）2020作者。 John Wiley＆Sons Ltd发布的地球表面流程和地貌

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