Digital Elevation Models represent the 3D-dimensional shape of the earth's surface. A coastal DEM (CDEM) extends this representation to include the offshore region adjacent to the coastal areas. CDEMs are a critical tool for researchers and decision-makers to understand better and predict the environmental changes that affect coastal areas, namely coastal flood hazard mitigation in the face of sea level rise, storm surges, waves, river (fluvial) and precipitation (pluvial) flooding, and tsunamis, by utilizing DEMs to model various coastal processes. We initiated the project of developing CDEM for the city of Conception Bay South, located in the Avalon Peninsula near the provincial capital of St. John’s, Newfoundland and Labrador, Canada. Potential impacts on the provincial capital region are concerning due to the concentration of population and property value, playing a role of accurate data to inform different sectors in decision-making, including municipal and regional planning. The location of the project case study was chosen due to its coastal characteristics of low-laying coastal geomorphology zones, including barrier beaches and lagoons. The CDEM of CBS currently represents one of the highest-resolution DEMs of the province: Land DEMs derived from NRCan Lidar data with a resolution between ~1 m and the bathymetric data provided from the Canadian hydrographic services (CHS) with a resolution of ~2-5 m. We generated the CDEM through a standard process using free, open-source code CUDEM (VDATUM) for vertical datum transformation and data interpolation. We validate the land portion of the model with land control points and NASA’s Advanced Topographic Laser Altimeter system. The created model consists of a continuous land and offshore CBS area model, essential informative data for studying coastal hazards. This study will facilitate future efforts in generating data products covering all the province's coastal areas. We are hopeful that documentation of the demonstrated CDEM data integration and validation methods can inform coastal flood hazard mitigation studies across Canada.

The accurate detection and characterization of boulders in underwater environments are crucial for various marine applications, including habitat mapping, geological studies, etc. This research explores the application of the YOLO (You Only Look Once) model in automating boulder detection for enhanced geological analysis. Leveraging a diverse dataset provided by the National Oceanic and Atmospheric Administration (NOAA) encompassing various terrains and lighting conditions, we trained and fine-tuned the YOLOv8 model to robustly identify boulders within the given environment. The methodology involves preprocessing the dataset, optimizing hyperparameters, and validating the model’s performance through rigorous testing. The YOLOv8 model, known for its real-time object detection capabilities, proved to be highly efficient in recognizing boulders of different sizes and shapes. The integration of convolutional neural networks within the YOLOv8 framework facilitated the extraction of intricate features, ensuring accurate identification even in challenging scenarios such as low resolution, range, minimum detectable size, interpreter variability, etc. To validate the model’s reliability, an extensive experiment and comparison of the automated detection results with ground truth data collected through visual surveys was conducted. The outcomes reveal not only a significant reduction in processing time but also a commendable precision and recall rate, affirming the viability of our automated boulder detection model. This research contributes to the field of ocean mapping by offering a reliable and efficient tool for boulder detection, aiding in geological analysis, hazard assessment, and environmental monitoring. Implementing YOLOv8 in this context presents a scalable solution with potential applications in various geological studies. The findings pave the way for further advancements in automated object detection techniques, fostering a more streamlined and accurate approach to geospatial analysis.

Combined bathymetric and side scan sonars may represent an alternative to independent multi-beam echo sounders and side scan sonars for shallow water storm-response hydrographic survey. The Atlantic coast of the United States is dominated by shallow sand and silt bottom coastal and inland water areas prone to shoaling and other navigational hazards, especially after major storms. In the aftermath of such storms, areas of high navigational significance are typically technically challenging and dangerous areas for hydrographic survey teams to operate vessels. The historical limitations of phase differencing systems are generally well documented, however recent developments in combined bathymetric and side scan systems may offer hydrographers an improved survey tool for meeting strict hydrographic standards and declaring storm-impacted waterways safe for navigation. Phase measurement offers significantly greater angular coverage, allowing survey vessels to maintain safer distances from pier faces, large vessels, and charted dangers to navigation. Increased transducer receiver elements derive a higher number of phase measurements which may increase data density at nadir, as well as increase accuracy of bathymetry points and limit multipath effects. Full bathymetric coverage and co-registered side scan data allow for the confirmation of seabed features that would pose navigational risk to mariners. As identifying and reporting these dangers to navigation are a vital part of the storm response survey, the ability of the latest generation of combined systems to reliably detect and measure accurate least depths of discrete seafloor targets needs be investigated. Further testing must be performed to determine the current state of technology and whether PDBS systems warrant new consideration for NOAA nautical charting hydrographic survey. In this investigation, the object detection capabilities of the Edgetech 6205 Combined Bathymetry and Side Scan Sonar are tested, and its utility and ability to faithfully record least depths on navigationally significant seafloor targets are discussed.

In recent years technological advances in uncrewed systems have led to a number of platforms becoming viable for production level hydrographic survey. These systems have the potential to spark a paradigm shift in modern hydrographic practices. Traditional, crewed vessels come with multiple limitations that uncrewed surface vessels (USVs) can mitigate or eliminate. Without the requirements of sustaining and accommodating crew, USV’s could prove to be safer, more efficient, capable of greater endurance and more sea state tolerant. To characterize the potential use cases and capabilities of these new platforms, five principle operational modalities have been identified and investigated utilizing the USV DriX, a purpose-built hydrographic platform. Two DriXs were used for data collection and analysis within the context of this work: DriX08, which is owned and operated by the Center for Coastal and Ocean Mapping and the Joint Hydrographic Center, and DriX12, which is owned and operated by the United States National Oceanic and Atmospheric Administration. Ten case studies were conducted comparing DriX to traditional hydrographic platforms. Two surveys in which a DriX was a primary data collector in conjunction with a traditional crewed platform and eight baseline surveys in various locales completed using conventional methods were used for this investigation. The relative strengths and limitations of the DriX platform for these survey examples are described.

SatBathy is a new Satellite-Derived Bathymetry (SDB) processing tool developed by NOAA (currently in beta version 2.1.6). It integrates a Graphical User Interface (GUI) with advanced processing capabilities for improving the speed, accessibility, and quality of SDB products. This tool combines open and closed source web and desktop technologies, using 10 meter resolution multispectral satellite imagery from the Copernicus Sentinel-2 mission, Amazon Web Services (AWS), and the ACOLITE atmospheric correction processor. The methodological foundation of SatBathy involves a multi-temporal SDB approach. This includes an atmospheric correction process, a physically-based algorithm, and a multi-scene compositing method to address turbidity effects. A switching model is also utilized for improved mapping in shallow waters. The tool is designed to minimize manual input, requiring users only to define a time range for imagery and perform a simplified calibration process. The SatBathy GUI, created using the customizable Flask web framework, enables users to generate Areas of Interest (AOIs) dynamically, query and preview imagery across various time frames, adjust for cloud coverage, and access image metadata. Moreover, SatBathy can convert “pseudo” bathymetry (pSDB) outputs into actual bathymetric measurements (SDB in meters relative to a datum) through an automated vertical referencing step that correlates pSDB with ground truth data. SatBathy's capabilities for reconnaissance bathymetry are especially useful in planning field operations in poorly charted or dynamically changing seafloor regions, such as Alaska. This tool enables efficient, accurate preliminary mapping of remote environments. It can be used to identify where dangerous shoaling is likely within the extinction depth, providing critical information on how to safely and efficiently survey the area. This poster will detail the functionalities of the SatBathy tool, its current capabilities, and its development roadmap. It will also highlight ongoing research activities that are contributing to the enhancement and evolution of the SatBathy tool.

As the National Oceanic and Atmospheric Administration (NOAA) continues its retirement of traditional paper chart products, some constituents expressed the need to continue a form of hard-copy chart for planning and situational awareness. The NOAA Custom Chart (NCC) provides the mariner with a paper chart derived from the latest electronic navigational chart (ENC) data using traditional paper chart symbology and labels. The NOAA Custom Chart application has improved as a result of similar exercises conducted by others in the industry and will continue to do so through thoughtful and deliberate critique. This project aims to use cartographic assessment to highlight the differences between automated marine chart outputs and their traditional paper chart predecessors to prioritize improvements to the NCC application. This poster compares an automated NCC output of Campobello Island and surrounding waters along the United States/Canada boundary in southwest Passamaquoddy Bay to its corresponding paper chart, NOS Chart 13396 Edition 7 (discontinued 11/29/2023), identifying the differences in output between the automatically generated NOAA Custom Chart output and the traditionally compiled paper chart. The display features a sample of discrepancies between the two charts, with a brief description of their nature. The types of discrepancies include symbology, labeling, and formatting of notes and other chart information. Then, each exhibit will be scored one through five, from benign, meaning the variance is of little consequence to the user, to severe, meaning the variance could confuse the user and hinder comprehension of the data. Finally, a solution to each exhibit will be proposed.

As a result of major recent flooding events in Canada, the Communauté Métropolitaine de Québec (CMQuébec) recognized the need for highly accurate surveys of its watercourses to inform flood preparedness and civil security. CMQuébec conducted its first surveys in 2019, then commissioned NV5 Geospatial to survey eight additional watercourses, covering a total area of more than 7,000 acres, in autumn 2022. This article explores the techniques used to achieve an exceptional degree of precision in the topobathymetric Lidar survey, as well as the logistical challenges that can impact the success of similar projects.

The Colorado River is the lifeblood of the Southwest US. Severe drought and overuse of water resources has left stakeholders significantly concerned about the future health and viability of the river. In August 2021, the US Bureau of Reclamation contracted River Restoration.Org (RRO), to map the Southern Colorado River. RRO contracted NV5 Geospatial for the collection of 342 miles of shallow water bathymetry via airborne remote sensing. Other team members included Precision Surveys (ground survey), River Restoration and Survey Systems, Inc (sonar), and Tetra Tech (data integration). The largest comprehensive mapping project for a non-navigable river in US history. The bathymetric lidar survey was a complicated collection that required significant coordination with the client and ground survey teams to maneuver around dam release schedules, flow controls, and ground control field work. Further, the NV5G crew had to coordinate the proposed low flow acquisition schedule from the Hoover Dam with additional restricted airspace constraints. Simply the mere length of the river surveyed, at 342 total miles, was unprecedented for a continuous riverine bathymetric survey with high accuracy. Results of the Lower Colorado River bathymetric lidar survey provide several societal and economic benefits on both a local and global scale. Since the 1900s, the BOR has periodically collected bathymetric data or studied the sediment to try to record and document changes in the Colorado River. Stakeholders can now study, model, and monitor the river to better mitigate the impacts of a changing climate and water use on the river’s capacity to provide water and energy. The project also serves as a prototype for comprehensive bathymetric mapping of inland non-navigable rivers, demonstrating that airborne bathymetric lidar is a more cost-effective method for surveying shallow water zones of lengthy river systems. When used to pinpoint where more expensive vessel-based methods are necessary, airborne bathymetry facilitates achieving wall-to-wall bathymetric coverage without breaking the bank.