Date of Award

Spring 2023

Project Type

Thesis

Program or Major

Ocean Engineering

First Advisor

Brian Calder

Second Advisor

Brian Miles

Third Advisor

Andrew Armstrong

Abstract

Towards Automation of Volunteered and AuthoritativeBathymetric Data Comparisons By LT Patrick J. Debroisse, NOAA University of New Hampshire, May 2023 Hydrographic data, including sonar, positioning, and oceanographic data used for sea floor mapping, are used all over the world for many purposes. Large volumes of high-quality hydrographic data are required to create high-accuracy nautical charts and bathymetric models required by national defense, resource management, shipping, and scientific interest groups, among others. However, across the world, the amount of highquality data available is limited. Volunteered Bathymetric Information (VBI) is a relatively untapped data source that could be used in many ways such as filling data gaps and informing future data collection expeditions. Determining the quality of VBI, especially Crowdsourced Bathymetry (CSB), has been difficult and time consuming leading to limited use in official nautical charts by national Hydrographic Offices. Despite this, the International Hydrographic Organization continues to collect and store CSB in its Data Centre for Digital Bathymetry (DCDB) in the hopes of widespread future use. Recent developments in VBI quality assessment have made its regular use more viable, however data discovery, acquisition, and correlation with authoritative data is still a time-consuming and error-prone manual process that must be improved upon before more widespread use of VBI is possible. In the case of CSB, data discovery involves the use of the DCDB web map viewers to identify and request individual files via email. There is currently no permanent programmatic solution to data discovery in DCDB. In a world of limited staff resources, automating this process will help to increase the speed with which VBI could be assessed for quality and incorporated into nautical charts, bathymetric models, survey planning, and decision-making tools. Herein, the design of an open source, Python-based tool called VBI Compare is described. VBI Compare automates the data discovery and acquisition phase of VBI quality analysis workflows and allows for VBI data reputation calculations to be initiated. As part of the data discovery process, VBI Compare ensures co-location of VBI and authoritative chart data and displays the data collected and processing status to the user. Further, the functionality of VBI Compare is demonstrated by a case study in the Houston Ship Channel, United States using the NOAA National Bathymetric Source (NBS) as the source of authoritative data and DCDB CSB data as the VBI input. This case study shows the start-to-finish use of VBI Compare to locate and collect required data and feed it into VBI reputation calculation tools being developed by the Center for Coastal and Ocean Mapping. This case study demonstrates the real-world utility of VBI Compare to a Hydrographic Office for VBI evaluation.

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