Abstract
Seafloor backscatter data from multibeam echosounders are now widely used in seafloor characterization studies. Accurate and repeatable measurements are essential for advancing the success of these techniques. This paper explores the impact of uncertainty in our knowledge of the local seafloor slope on the overall accuracy of the backscatter measurement. Amongst the various sources of slope uncertainty studied, the impact of bathymetric uncertainty and scale were identified as the major sources of slope uncertainty. The bottom slope affects two important corrections needed for estimating seafloor backscatter: (1) The insonified area and; (2) the seafloor incidence angle. The impacts of these slope-related uncertainty sources were quantified for a shallow water multibeam survey. The results show that the most significant uncertainty in backscatter data arises when seafloor slope is not accounted for or when low-resolution bathymetry is used to estimate seafloor slope. This effect is enhanced in rough seafloors. A standard method of seafloor slope correction is proposed to achieve repeatable and accurate backscatter results. Additionally, a standard data package, including metadata describing the slope corrections applied, needs to accompany backscatter results and should include details of the slope estimation method and resolution of the bathymetry used.
Highlights
Over the last few decades, there have been significant advances in the use of multibeam echo sounders (MBES) to acoustically determine the seafloor properties that are critical for a host of applications, including nautical charting, seabed habitat assessments, and geological interpretations [1,2,3,4]
Uncertainty of the insonified area and incidence angle caused by the seafloor slope uncertainty
Uncertainty quantification is a complex and important part of seafloor acoustic remote sensing that is integral to the repeatability of the processing and interpretation of backscatter data
Summary
Over the last few decades, there have been significant advances in the use of multibeam echo sounders (MBES) to acoustically determine the seafloor properties (e.g., depth, sediment type) that are critical for a host of applications, including nautical charting, seabed habitat assessments, and geological interpretations [1,2,3,4]. With the growing use of remote sensing data, the topic of uncertainty has been receiving increasing attention, in the terrestrial geographical sciences [5,6,7,8]. This focus has led to recommendations that the spatial output of remote sensing data, when compiled into a geographical information system (GIS), should be (at least) twofold: (i) A map of the variable of interest and (ii) some assessment of the measurement uncertainty in that map. Calls for including uncertainty estimates in remote sensing studies have been numerous, its practical application is challenging. The main reasons for this are: (1) Knowledge of uncertainty in the measurements is often not available; (2) the impact of the choice of spatial scale is inherently linked to the variable being mapped (which is essentially the unknown), the ambiguity as what should be the ideal spatial scale; (3) data processing tools are often not transparent, i.e., their algorithms can be proprietary, prohibiting the calculation of uncertainty propagation from input to the final outputs;
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
