Quantifying and Reducing the Uncertainty of 3D Displacement Estimates from Terrestrial Laser Scanner Point Clouds
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2025
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Conference Paper
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Abstract
Terrestrial laser scanning (TLS) can offer an effective solution to geomonitoring problems by providing highresolution point clouds, which serve as a basis for estimating dense 3D displacements. The uncertainty of such estimates, as well as the means of reducing it remain largely unexplored. We present a case study to evaluate the accuracy of TLS-based deformation estimates from an alpine monitoring campaign consisting of 6 scanning epochs between 2019 and 2022. The point clouds acquired with a Riegl VZ-4000 scanner were processed using the Feature to Feature Supervoxel-based Spatial Smoothing (F2S3) algorithm to estimate the 3D displacement vectors. We compared these vectors to sparsely distributed ground truth measurements, acquired using Global Navigation Satellite System (GNSS) stations. The results showed that, if adequately spatially averaged over large areas, the 3D vectors can be estimated with an accuracy of a few centimeters despite the long distances of up to 4 km. This corresponds to an accuracy of a few centimeters for the displacement magnitude, and a few degrees for the direction (if the magnitude is large enough for a meaningful
estimate of the direction). Herein, we additionally explore several strategies to reduce the uncertainty, where temporal averaging of multiple consecutive scans from a single epoch proved to be the most promising one, while vegetation filtering and a careful selection of the registration approach indicated limitations that require further investigations.
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Karlsruhe Institute of Technology
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6th Joint International Symposium on Deformation Monitoring (JISDM 2025)
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Subject
geomonitoring; terrestrial laser scanning (TLS); point clouds; 3D displacement vector field
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03964 - Wieser, Andreas / Wieser, Andreas