1,355
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

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

, , &
Pages 496-518 | Received 28 Sep 2021, Accepted 05 May 2022, Published online: 18 May 2022

References

  • Amante, C. J., and B. W. Eakins. 2016. Accuracy of interpolated bathymetry in digital elevation models. Journal of Coastal Research 76:123–33.
  • AML Oceanographic. 2020. Base-X product description. Accessed December 7, 2021. http://www.mdsys.co.kr/down/AML/Base_X.pdf.
  • AML Oceanographic. Micro-X product description. Accessed December 7, 2021. https://stema-systems.nl/wp-content/uploads/2015/08/Micro-X_Brochure.pdf.
  • Applanix. 2019. POS MV OceanMaster, 2. Accessed December 7, 2021. https://www.applanix.com/downloads/products/specs/posmv/POS-MV-OceanMaster.pdf.
  • Beaudoin, J., B. Calder, J. Hiebert, and G. Imahori. 2009. Estimation of sounding uncertainty from measurements of water mass variability. International Hydrographic Review November 2009:20–38.
  • Bjorn, J, and B. Einar. 2006. Time referencing in offshore survey systems. FFI/RAPPORT-2006/01666. Forsv Arets Forskninginstitutt (Norwegian Defence Research Establishment), 122.
  • Byrne, J. S, and V. E. Schmidt. 2015. Uncertainty modeling for AUV acquired bathymetry. U. S. Hydrographic Conference (US HYDRO), Gaylord Hotel, National Harbor, Maryland, USA, 25
  • Calder, B. R., and L. A. Mayer. 2003. Automatic processing of high-rate, high-density multibeam echosounder data. Geochemistry Geophysics Geosystems 4 (6):22.
  • Canadian Hydrographic Service (CHS). 2012. Traitement et analyse de données bathymétriques de CUBE. Pêches et Océans Canada, 7 p.
  • Cassol, W. N. 2018. Définition d'un modèle d'incertitude-type composée pour les Systèmes LiDAR mobiles, Master thesis, Université Laval, Québec, Canada, 111 p.
  • Debese, N. 2013. Bathymétrie. Sondeurs, traitements des données, modèles numériques de terrain. Cours et exercices corrigés. Paris, France: TECHNOSUP, éditions ellipses, 404 p.
  • Debese, N., J. J. Jacq, and T. Garlan. 2016. Extraction of sandy bedforms features through geodesic morphometry. Geomorphology 268:82–97.
  • Di Stefano, M., and L. A. Mayer. 2018. An automatic procedure for the quantitative characterization of submarine bedforms. Geosciences 8 (1):28.
  • van Dijk, T. J. A. van Dalfsen, V. Van Lancker, R. A. van Overmeeren, S. van Heteren, and P. J. Doornenbal. 2012. 13—Benthic habitat variations over tidal ridges, North Sea, the Netherlands. In Seafloor Geomorphology as Benthic Habitat; 241–9. Elsevier: Amsterdam, The Netherlands. ISBN 9780123851406.
  • Dupont, V. 2020. Élaboration d’une méthode d’extraction de plans par croissance de régions dans un nuage de points bathymétriques servant à alimenter des estimateurs d’erreur hydrographique. Université Laval, Québec, Canada, 120 p.
  • Godin, A. 1998. The calibration of shallow water multibeam echo-sounding systems. Fredericton, Canada: Department of Geodesy and Geomatics Engineering, University of New Brunswick, 76–120.
  • Goulden, T. 2009. Prediction of error due to terrain slope in LiDAR observations. Technical Repport no. 265. Department of Geodesy and Geomatics Engineering, University of New Brunswick, 150 p.
  • Goulden, T., and C. Hopkinson. 2010. The forward propagation of integrated system component error within airborne LiDAR data. Photogrammetric Engineering & Remote Sensing 76 (5):589–601.
  • Hare, R. 1995. Depth and position error budgets for multibeam sounding. International Hydrographic Review, Monaco LXXII (2):37–69.
  • Hare, R., B. Eakins, and C. Amante. 2011. Modelling bathymetric uncertainty. International Hydrographic Review November 2011: 31–42.
  • Hughes Clarke, J. E. 2018. The impact of acoustic imaging geometry on the fidelity of seabed bathymetric models. Geosciences 8 (4):109.
  • International Hydrographic Organization. 2020. Standards for Hydrographic Surveys, No. 44, 6th ed., 49 p. Principauté de Monaco: IHO Publication.
  • Joint Committee for Guides in Metrology. 2008. Evaluation of measurement data—Guide to the expression of uncertainty in measurement. 1st ed., September 2008, 134 p. Sèvres, France: Bureau International des Poids et Mesures (BIPM).
  • Kongsberg. 2021. EM 2040 multibeam Echosounder, 2 p. Accessed December 7, 2021. https://www.kongsberg.com/contentassets/e8fa4f09f25f4b1e86eda52cc1355dc7/em-2040–-mkii-data-sheet.pdf
  • Lecours, V., M. F. J. Dolan, A. Micallef, and V. L. Lucieer. 2016. A review of marine geomorphometry, the quantitative study of the seafloor. Hydrology and Earth System Sciences 20 (8):3207–44.
  • Lurton, X. 2003. Theoretical modelling of acoustical measurement accuracy for swath bathymetric sonars. International Hydrographic Review 4 (2):17–30.
  • Naankeu Wati, G., J. B. Geldof, and N. Seube. 2016. Error budget analysis for surface and underwater survey system. International Hydrographic Review May 2016: 21–46.
  • Schaer, P., Skaloud, J., Landtwing, S. and Legat, K. 2007. Accuracy estimation for laser point cloud including scanning geometry. 5th International symposium on mobile mapping technology, Padova, Italy, May 29–31, 8 p.
  • Seube, N., and R. Keyetieu. 2017. Multibeam echo sounders-IMU automatic boresight calibration on natural surfaces. Marine Geodesy 40 (2–3):172–86.
  • Spectra Geospatial. 2020. SP90m GNSS receiver, 3 pages, viewed June 2021.
  • Thibaud, R., G. Del Mondo, T. Garlan, A. Mascret, and C. Carpentier. 2013. A spatio-temporal graph model for marine dune dynamics analysis and representation. Trans GIS 17:742–62.
  • Tidd, R. A. 2005. The impact of varying seafloor topographies, and object geometris on resolution for multibeam echosounders and multi-angle swath bathymetry systems. Proceedings of OCEANS 2005 MTS/IEEE, Washington DC,Vol. 3,2224–2227.