Deformation and displacement monitoring of arch dams is usually conducted by measurement methods that gained widespread acceptance. Mostly pointwise measurements acquired within different epochs serve as the basis for deformation analysis. The uncertainty information of these observations is generally established. When referring to surface-based deformation monitoring, terrestrial laser scanning (TLS) is intensively hyped up. Nevertheless, current knowledge about stochastic modelling of TLS observations is scarce and very often reduced to a diagonal variance-covariance matrix (VCM). This neglects the exiting correlations within the point clouds. Aiming to fill the gap, this paper shows one possibility of obtaining a fully populated variance-covariance matrix using the elementary error model (EEM). Previous publications on this topic described the application of EEM for the Leica HDS 7000 laser scanner and showed results on simulated data for laboratory objects. Within this paper instrumental errors of the same scanner are modeled differently, according to recent work. A real scan of the arch dam Kops in Austria highlights influences on the variances, covariances and correlations of points within the point cloud for two instrument error models. Findings show that the model choice does not bring a notable change in the error of positions, but influences the correlation coefficients up to a level of $\Delta$$\rho$þinspace=þinspace0.2.
%0 Conference Paper
%1 kerekes2021determining
%A Kerekes, Gabriel
%A Schwieger, Volker
%B Contributions to International Conferences on Engineering Surveying
%C Cham
%D 2021
%E Kopácik, Alojz
%E Kyrinovic, Peter
%E Erdélyi, Ján
%E Paar, Rinaldo
%E Marendić, Ante
%I Springer, Cham
%K 2021 iigs
%P 57--68
%R https://doi.org/10.1007/978-3-030-51953-7_5
%T Determining Variance-Covariance Matrices for Terrestrial Laser Scans: A Case Study of the Arch Dam Kops
%X Deformation and displacement monitoring of arch dams is usually conducted by measurement methods that gained widespread acceptance. Mostly pointwise measurements acquired within different epochs serve as the basis for deformation analysis. The uncertainty information of these observations is generally established. When referring to surface-based deformation monitoring, terrestrial laser scanning (TLS) is intensively hyped up. Nevertheless, current knowledge about stochastic modelling of TLS observations is scarce and very often reduced to a diagonal variance-covariance matrix (VCM). This neglects the exiting correlations within the point clouds. Aiming to fill the gap, this paper shows one possibility of obtaining a fully populated variance-covariance matrix using the elementary error model (EEM). Previous publications on this topic described the application of EEM for the Leica HDS 7000 laser scanner and showed results on simulated data for laboratory objects. Within this paper instrumental errors of the same scanner are modeled differently, according to recent work. A real scan of the arch dam Kops in Austria highlights influences on the variances, covariances and correlations of points within the point cloud for two instrument error models. Findings show that the model choice does not bring a notable change in the error of positions, but influences the correlation coefficients up to a level of $\Delta$$\rho$þinspace=þinspace0.2.
%@ 978-3-030-51953-7
@inproceedings{kerekes2021determining,
abstract = {Deformation and displacement monitoring of arch dams is usually conducted by measurement methods that gained widespread acceptance. Mostly pointwise measurements acquired within different epochs serve as the basis for deformation analysis. The uncertainty information of these observations is generally established. When referring to surface-based deformation monitoring, terrestrial laser scanning (TLS) is intensively hyped up. Nevertheless, current knowledge about stochastic modelling of TLS observations is scarce and very often reduced to a diagonal variance-covariance matrix (VCM). This neglects the exiting correlations within the point clouds. Aiming to fill the gap, this paper shows one possibility of obtaining a fully populated variance-covariance matrix using the elementary error model (EEM). Previous publications on this topic described the application of EEM for the Leica HDS 7000 laser scanner and showed results on simulated data for laboratory objects. Within this paper instrumental errors of the same scanner are modeled differently, according to recent work. A real scan of the arch dam Kops in Austria highlights influences on the variances, covariances and correlations of points within the point cloud for two instrument error models. Findings show that the model choice does not bring a notable change in the error of positions, but influences the correlation coefficients up to a level of $\Delta$$\rho${\thinspace}={\thinspace}0.2.},
added-at = {2022-05-12T11:10:08.000+0200},
address = {Cham},
author = {Kerekes, Gabriel and Schwieger, Volker},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2e2d364dcb8028c6984edbb24af9b7cdf/larsplate},
booktitle = {Contributions to International Conferences on Engineering Surveying},
doi = {https://doi.org/10.1007/978-3-030-51953-7_5},
editor = {Kop{\'a}{\v{c}}ik, Alojz and Kyrinovi{\v{c}}, Peter and Erd{\'e}lyi, J{\'a}n and Paar, Rinaldo and Marendi{\'{c}}, Ante},
interhash = {758b174fb26341f5a8a59a4aaca68f43},
intrahash = {e2d364dcb8028c6984edbb24af9b7cdf},
isbn = {978-3-030-51953-7},
keywords = {2021 iigs},
pages = {57--68},
publisher = {Springer, Cham},
timestamp = {2022-05-13T07:35:24.000+0200},
title = {Determining Variance-Covariance Matrices for Terrestrial Laser Scans: A Case Study of the Arch Dam Kops},
year = 2021
}
