An Empirical Study of the Influence of Seafloor Morphology on the Uncertainty of Bathymetric Data

Abstract

The estimation of the uncertainty related to bathymetric data is essential in determining the quality of the data acquisition. This estimation is based on the covariance propagation considering the classical sounding georeferencing model. The estimation of the uncertainty using the Total Propagated Uncertainty (TPU) model is well described in the literature. Developing on this model, this study introduces an analysis of the morphological influence of the seafloor on the uncertainty value of the sounded points. Advancing the comprehension of the influence of the seafloor on the uncertainty value of the bathymetric data would improve the processing and interpretation of the seafloor surface as well as the structures present on the seafloor.

Keywords:

• Bathymetric data
• Bathymetric data uncertainty
• Morphological Uncertainty

Acknowledgments

The authors would like to thank Université Laval for providing access to the equipment and laboratories required to conduct this research. Also, the authors thank the CIDCO (Centre Interdisciplinaire en Développement en Cartographie des Océans), Mathieu Rondeau and Ghislain Bouillon of the Canadian Hydrographic Service (CHS) for providing the data used in this research. Thanks to the companies for the licenses of the software as QPS for Qimera 1.7.6, ESRI for ArcGIS 10.7 and Matlab R2019a—Classroom use. The authors acknowledge Vincent Dupont, M.Sc., for his comments and involvement in the results production phase.

Disclosure statement

The authors declare no conflicts of interest.

Data availability statement

The data are not publicly available. The data were a courtesy of the Canadian Hydrographic Service for this research. They can be available upon request to the corresponding author.

Additional information

Funding

This work was supported by the FRQ-NT (Fonds de Recherche Nature et Technologie Québec) under grant 2018-PR-206875. The authors thank Mitacs, CN (Canadien National), Faculté de Foresterie, Géographie et Géomatique de l’Université Laval, Fond Joncas, l’Association de Géomatique Municipale du Québec (AGMQ) and Canadian Institute of Geomatics (CIG) for their financial support.