Enhancing digital bathymetric models by advanced measurement uncertainty analysis

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  • German Federal Institute of Hydrology (BfG)
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Original languageEnglish
Pages (from-to)28-50
JournalThe International Hydrographic Review
Volume31
Issue number1
Publication statusPublished - 1 May 2025

Abstract

Accurate Digital Bathymetric Model (DBM)s are essential for ensuring safe navigation on waterways, yet they heavily depend on precise underwater measurements and robust modeling techniques. However, measurements taken in underwater environments are highly susceptible to uncertainties due to challenging environmental conditions and unknown underwater geometries, complicating the evaluation of both measurements and resulting models. This paper explores the impact of measurement uncertainty on DBM quality and presents a systematic pipeline for modeling these uncertainties to improve the reliability of resulting models. The methodology comprises of two primary stages. A detailed measurement uncertainty model is developed in the first stage based on error propagation principles. This model accounts for multiple uncertainty sources ranging from instrument accuracy to environmental influences. In the second stage, we implement a simulation-based approach to evaluate the influence of these uncertainties on the final DBM. To this end, we have developed a survey simulator that simulates a Multi-Beam Echo Sounder (MBES) system and generates realistic measurement uncertainties. The integration of these uncertainties as observation weights during the modeling process enhances model accuracy and reliability. The effectiveness and practicality of the proposed method are confirmed through validation in a controlled simulation environment with known geometry and uncertainties. The results underscore not only the technical benefits of incorporating measurement uncertainty in surface modeling but also highlight its critical importance in ensuring navigational safety through high-quality, reliable DBMs.

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Enhancing digital bathymetric models by advanced measurement uncertainty analysis. / Mohammadivojdan, Bahareh; Hake, Frederic; Lorenz, Felix et al.
In: The International Hydrographic Review , Vol. 31, No. 1, 01.05.2025, p. 28-50.

Research output: Contribution to journalArticleResearchpeer review

Mohammadivojdan, B, Hake, F, Lorenz, F, Bollert, JO, Weiss, R, Artz, T, Neumann, I & Alkhatib, H 2025, 'Enhancing digital bathymetric models by advanced measurement uncertainty analysis', The International Hydrographic Review , vol. 31, no. 1, pp. 28-50. https://doi.org/10.58440/ihr-31-1-a09
Mohammadivojdan, B., Hake, F., Lorenz, F., Bollert, J. O., Weiss, R., Artz, T., Neumann, I., & Alkhatib, H. (2025). Enhancing digital bathymetric models by advanced measurement uncertainty analysis. The International Hydrographic Review , 31(1), 28-50. https://doi.org/10.58440/ihr-31-1-a09
Mohammadivojdan B, Hake F, Lorenz F, Bollert JO, Weiss R, Artz T et al. Enhancing digital bathymetric models by advanced measurement uncertainty analysis. The International Hydrographic Review . 2025 May 1;31(1):28-50. doi: 10.58440/ihr-31-1-a09
Mohammadivojdan, Bahareh ; Hake, Frederic ; Lorenz, Felix et al. / Enhancing digital bathymetric models by advanced measurement uncertainty analysis. In: The International Hydrographic Review . 2025 ; Vol. 31, No. 1. pp. 28-50.
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abstract = "Accurate Digital Bathymetric Model (DBM)s are essential for ensuring safe navigation on waterways, yet they heavily depend on precise underwater measurements and robust modeling techniques. However, measurements taken in underwater environments are highly susceptible to uncertainties due to challenging environmental conditions and unknown underwater geometries, complicating the evaluation of both measurements and resulting models. This paper explores the impact of measurement uncertainty on DBM quality and presents a systematic pipeline for modeling these uncertainties to improve the reliability of resulting models. The methodology comprises of two primary stages. A detailed measurement uncertainty model is developed in the first stage based on error propagation principles. This model accounts for multiple uncertainty sources ranging from instrument accuracy to environmental influences. In the second stage, we implement a simulation-based approach to evaluate the influence of these uncertainties on the final DBM. To this end, we have developed a survey simulator that simulates a Multi-Beam Echo Sounder (MBES) system and generates realistic measurement uncertainties. The integration of these uncertainties as observation weights during the modeling process enhances model accuracy and reliability. The effectiveness and practicality of the proposed method are confirmed through validation in a controlled simulation environment with known geometry and uncertainties. The results underscore not only the technical benefits of incorporating measurement uncertainty in surface modeling but also highlight its critical importance in ensuring navigational safety through high-quality, reliable DBMs.",
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AU - Lorenz, Felix

AU - Bollert, Jan Ole

AU - Weiss, Robert

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