Statistical evaluation of the influence of the uncertainty budget on B-spline curve approximation

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Original languageEnglish
Pages (from-to)215-230
Number of pages16
JournalJournal of Applied Geodesy
Volume11
Issue number4
Publication statusPublished - 26 Oct 2017

Abstract

In the field of engineering geodesy, terrestrial laser scanning (TLS) has become a popular method for detecting deformations. This paper analyzes the influence of the uncertainty budget on free-form curves modeled by B-splines. Usually, free-form estimation is based on scanning points assumed to have equal accuracies, which is not realistic. Previous findings demonstrate that the residuals still contain random and systematic uncertainties caused by instrumental, object-related and atmospheric influences. In order to guarantee the quality of derived estimates, it is essential to be aware of all uncertainties and their impact on the estimation. In this paper, a more detailed uncertainty budget is considered, in the context of the "Guide to the Expression of Uncertainty in Measurement" (GUM), which leads to a refined, heteroskedastic variance covariance matrix (VCM) of TLS measurements. Furthermore, the control points of B-spline curves approximating a measured bridge are estimated. Comparisons are made between the estimated B-spline curves using on the one hand a homoskedastic VCM and on the other hand the refined VCM. To assess the statistical significance of the differences displayed by the estimates for the two stochastic models, a nested model misspecification test and a non-nested model selection test are described and applied. The test decisions indicate that the homoskedastic VCM should be replaced by a heteroskedastic VCM in the direction of the suggested VCM. However, the tests also indicate that the considered VCM is still inadequate in light of the given data set and should therefore be improved.

Keywords

    B-spline approximation, deformations, Gauss-Markov model, GUM, model misspecification test, model selection test, Terrestrial laser scanning, uncertainty budget

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Statistical evaluation of the influence of the uncertainty budget on B-spline curve approximation. / Zhao, Xin; Alkhatib, Hamza; Kargoll, Boris et al.
In: Journal of Applied Geodesy, Vol. 11, No. 4, 26.10.2017, p. 215-230.

Research output: Contribution to journalArticleResearchpeer review

Zhao X, Alkhatib H, Kargoll B, Neumann I. Statistical evaluation of the influence of the uncertainty budget on B-spline curve approximation. Journal of Applied Geodesy. 2017 Oct 26;11(4):215-230. doi: 10.1515/jag-2017-0018
Zhao, Xin ; Alkhatib, Hamza ; Kargoll, Boris et al. / Statistical evaluation of the influence of the uncertainty budget on B-spline curve approximation. In: Journal of Applied Geodesy. 2017 ; Vol. 11, No. 4. pp. 215-230.
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AU - Zhao, Xin

AU - Alkhatib, Hamza

AU - Kargoll, Boris

AU - Neumann, Ingo

N1 - Publisher Copyright: © 2017 Walter de Gruyter GmbH, Berlin/Boston. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2017/10/26

Y1 - 2017/10/26

N2 - In the field of engineering geodesy, terrestrial laser scanning (TLS) has become a popular method for detecting deformations. This paper analyzes the influence of the uncertainty budget on free-form curves modeled by B-splines. Usually, free-form estimation is based on scanning points assumed to have equal accuracies, which is not realistic. Previous findings demonstrate that the residuals still contain random and systematic uncertainties caused by instrumental, object-related and atmospheric influences. In order to guarantee the quality of derived estimates, it is essential to be aware of all uncertainties and their impact on the estimation. In this paper, a more detailed uncertainty budget is considered, in the context of the "Guide to the Expression of Uncertainty in Measurement" (GUM), which leads to a refined, heteroskedastic variance covariance matrix (VCM) of TLS measurements. Furthermore, the control points of B-spline curves approximating a measured bridge are estimated. Comparisons are made between the estimated B-spline curves using on the one hand a homoskedastic VCM and on the other hand the refined VCM. To assess the statistical significance of the differences displayed by the estimates for the two stochastic models, a nested model misspecification test and a non-nested model selection test are described and applied. The test decisions indicate that the homoskedastic VCM should be replaced by a heteroskedastic VCM in the direction of the suggested VCM. However, the tests also indicate that the considered VCM is still inadequate in light of the given data set and should therefore be improved.

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