AusSeabed workshop - Pydro and Hydroffice - Days 2 and 3

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Slides presented by Giuseppe Masetti (UNH, CCOM/JHC) and Tyanne Faulkes (NOAA, OCS PHB) during the "Effective Seabed Mapping Workflow" Workshop. June 19 and 20, 2019. Canberra, ACT, Australia

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AusSeabed workshop - Pydro and Hydroffice - Days 2 and 3

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Authors: G.Masetti, T.Faulkes, C.Kastrisios The presentation was given at the U.S. Hydro 2019 Conference. Abstract: The rising trend in automation is constantly pushing the hydrographic field toward the exploration and the adoption of more effective approaches for each step of the ping-to-public workflow. However, the large amount of data collected by modern acquisition systems - especially when paired with the force multiplier factor provided by autonomous vessels - conflict with the increasing timeliness expected by today’s final users. Such a situation represents a processing challenge for the largely human-centered solutions that are currently available, and the adoption of automated and semi-automated data quality procedures seems the only scalable and long-term solution to the problem. At the same time, there is an inherent value in propagating the application of such procedures upstream in the survey workflow. In fact, capturing potential issues close (in time and space) to their occurrence has the advantages of reducing the efforts required for their solution and limiting their extent. As such, modern surveys should rely more and more on robust data quality procedures that are applied in near real-time. With the challenge to automate and standardize a large portion of the quality controls used to analyze hydrographic data, NOAA’s Office of Coast Survey and the UNH Center for Coastal and Ocean Mapping have jointly developed (and made publicly available) a pair of software solutions - QC Tools for quality control and CA Tools for chart adequacy - that collect algorithmic implementations for a number of these tasks. Their aim is to verify whether the acquired data satisfy the adopted agency standards (and, in a more general sense, fit for the intended purpose). These standards usually focus on data quality aspects like data density, coverage, and uncertainty evaluation which are largely automated by the developed tools discussed in this paper, leaving to the experienced hydrographer the duty to review the results and supervise the validation process. After an overview of the tools (and the relevant recent improvements driven by field feedback), this work focuses on a new chart adequacy algorithm as well as an experimental approach for bathymetric anomaly detection and classification. A number of examples that use the publicly available solutions in real-world scenarios are also illustrated.

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Authors: G.Masetti, J-M.Augustin, M.Malik, C.Poncelet, X.Lurton, L.Mayer, G.Rice, M.Smith The presentation was given at the U.S. Hydro 2019 Conference. Abstract: Most ocean mapping surveys collect seafloor reflectivity (backscatter) along with bathymetry. While the consistency of bathymetry processed by commonly adopted algorithms is well established, surprisingly large variability is observed between the backscatter mosaics generated by different software packages when processing the same dataset. Such a situation severely limits the use of acoustic backscatter for quantitative analysis (e.g., monitoring seafloor change over time, or remote characterization of seafloor characteristics) and other commonly attempted tasks (e.g., merging mosaics from different origins). Acoustic backscatter processing involves a complex sequence of steps, but inasmuch as commercial software packages mainly provide end-results, comparisons between those results offer little insight into where in the workflow the differences are generated. In addition, preliminary results of a software-inter-comparison working group have shown that each processing algorithm tends to adopt a distinct, unique workflow; this causes large disagreements even in the initial per-beam reflectivity values resulting from differences in basic operations such as snippet averaging and evaluation of flagged beams. Far from ideal, this situation requires a clear shift from the past closed-source approach that has caused it. As such, the Open Backscatter Toolchain (OpenBST) project aims to provide the community with an open-source and metadata-rich modular implementation of a toolchain dedicated to acoustic backscatter processing. The long-term goal is not to create processing tools that would compete with available commercial solutions, but rather a set of open-source, community-vetted, reference algorithms usable by both developers and users for benchmarking their processing algorithms. As a proof-of-concept, we present a prototype implementation with the key elements of the OpenBST approach: • The data conversion from a native acquisition format (i.e., Kongsberg EM Series) to NetCDF-based data structures (components of the eXtensible Sounder Format) better suited to data exploration, processing and metadata coupling. • A processing pipeline constituted by a set of interlocking, task-oriented tools simplifying their substitution with alternative approaches. • The creation of final products (i.e., angular response curves and backscatter mosaics) capturing relevant acquisition and processing metadata.

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Backscatter mosaics of the seafloor are now routinely produced from multibeam sonar data, and used in a wide range of marine applications. However, significant differences (up to 5 dB) have been observed between the levels of mosaics produced by different software processing a same dataset. This is a major detriment to several possible uses of backscatter mosaics, including quantitative analysis, monitoring seafloor change over time, and combining mosaics. A recently concluded international Backscatter Working Group (BSWG) identified this issue and recommended that “to check the consistency of the processing results provided by various software suites, initiatives promoting comparative tests on common data sets should be encouraged […]”. However, backscatter data processing is a complex (and often proprietary) sequence of steps, so that simply comparing end-results between software does not provide much information as to the root cause of the differences between results. In order to pinpoint the source(s) of inconsistency between software, it is necessary to understand at which stage(s) of the data processing chain do the differences become substantial. We have invited willing software developers to discuss this framework and collectively adopt a list of intermediate processing steps. We provided a small dataset consisting of various seafloor types surveyed with the same multibeam sonar system, using constant acquisition settings and sea conditions, and have the software developers generate these intermediate processing results, to be eventually compared. If the experiment proves fruitful, we may extend it to more datasets, software and intermediate results. Eventually, software developers may consider making the results from intermediate stages a standard output as well as adhering to a consistent terminology, as advocated by Schimel et al. (2018). To date, the developers of four software (Sonarscope, QPS FMGT, CARIS SIPS, MB Process) have expressed their interest in collaborating on this project.

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Authors: Giuseppe Masetti1*, Jean-Marie Augustin2, Xavier Lurton2, Brian R. Calder3 1. CCOM/JHC, University of New Hampshire, Durham, NH, USA, gmasetti@ccom.unh.edu 2. Institut Français de Recherche pour l’Exploitation de la Mer (Ifremer), Brest, France 3. CCOM/JHC, University of New Hampshire, Durham, NH, USA An objective measurement of the bathymetric uncertainty introduced by sonar bottom detection has been proposed (Lurton and Augustin, 2009) to overcome the sonar-specific heuristic solutions proposed by constructors. This approach pairs each sounding with an estimation of sonar detection uncertainty (SDU) based on the width of the signal envelope (amplitude detection) or the noise level of the phase ramp (phase detection), thus capturing the intrinsic quality of the received signal and any applied signal-processing step. Along with the environment characterization and the motion sensor accuracy, the SDU represents a major contributor to the total vertical uncertainty (TVU). As such, the monitoring of the SDU statistics by detection types, acquisition modes, and transmission sectors (when available) provides an effective way to alert the surveyor about ongoing issues in the data collection. It also has potential application in the evaluation of the health status of the sonar - for example, by comparing SDU-derived performance of repeated surveys on the same seafloor area and estimating the uncertainty contributions from environment and motion. Finally, the SDU may be integrated in multiple stages of the data processing workflow, from data pre-filtering to hydrographic uncertainty modeling, up to more advanced applications like hypotheses disambiguation in statistical gridding algorithms (e.g., CUBE). Based on such considerations, we conducted a study to explore possible applications of the estimated SDU values for survey quality control and data processing. The results of the analysis applied to real data – collected using multibeam echosounders from manufacturers who are early adopters of this metric (i.e., Kongsberg Maritime and Teledyne Reson) – provide evidence that SDU is a useful tool for survey monitoring.

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