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4 pages, 190 KiB

Open AccessEditorial

Advancements in Ocean Mapping and Nautical Cartography

by Giuseppe Masetti, Ian Church, Anand Hiroji and Ove Andersen

Geomatics 2024, 4(4), 433-436; https://doi.org/10.3390/geomatics4040023 - 28 Nov 2024

Viewed by 402

Abstract

Ocean mapping and nautical cartography are foundational to understanding and managing marine environments [...] Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

Research

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16 pages, 4625 KiB

Open AccessArticle

Classification of Coastal Benthic Substrates Using Supervised and Unsupervised Machine Learning Models on North Shore of the St. Lawrence Maritime Estuary (Canada)

by Guillaume Labbé-Morissette, Théau Leclercq, Patrick Charron-Morneau, Dominic Gonthier, Dany Doiron, Mohamed-Ali Chouaer and Dominic Ndeh Munang

Geomatics 2024, 4(3), 237-252; https://doi.org/10.3390/geomatics4030013 - 30 Jun 2024

Cited by 1 | Viewed by 1872

Abstract

Classification of benthic substrates is a core necessity in many scientific fields like biology, ecology, or geology, with applications branching out to a variety of industries, from fisheries to oil and gas. In the first part, a comparative analysis of supervised learning algorithms [...] Read more.

Classification of benthic substrates is a core necessity in many scientific fields like biology, ecology, or geology, with applications branching out to a variety of industries, from fisheries to oil and gas. In the first part, a comparative analysis of supervised learning algorithms has been conducted using geomorphometric features to generate benthic substrate maps of the coastal regions of the North Shore of Quebec in order to establish a quantitative assessment of performance to serve as a benchmark. In the second part, a new method using Gaussian mixture models is showcased on the same dataset. Finally, a side-by-side comparison of both methods is featured to provide a qualitative assessment of the new algorithm’s ability to match human intuition. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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34 pages, 51108 KiB

Open AccessArticle

Seafloor and Ocean Crust Structure of the Kerguelen Plateau from Marine Geophysical and Satellite Altimetry Datasets

by Polina Lemenkova

Geomatics 2023, 3(3), 393-426; https://doi.org/10.3390/geomatics3030022 - 10 Aug 2023

Cited by 1 | Viewed by 2343

Abstract

The volcanic Kerguelen Islands are formed on one of the world’s largest submarine plateaus. Located in the remote segment of the southern Indian Ocean close to Antarctica, the Kerguelen Plateau is notable for a complex tectonic origin and geologic formation related to the [...] Read more.

The volcanic Kerguelen Islands are formed on one of the world’s largest submarine plateaus. Located in the remote segment of the southern Indian Ocean close to Antarctica, the Kerguelen Plateau is notable for a complex tectonic origin and geologic formation related to the Cretaceous history of the continents. This is reflected in the varying age of the oceanic crust adjacent to the plateau and the highly heterogeneous bathymetry of the Kerguelen Plateau, with seafloor structure differing for the southern and northern segments. Remote sensing data derived from marine gravity and satellite radar altimetry surveys serve as an important source of information for mapping complex seafloor features. This study incorporates geospatial information from NOAA, EMAG2, WDMAM, ETOPO1, and EGM96 datasets to refine the extent and distribution of the extracted seafloor features. The cartographic joint analysis of topography, magnetic anomalies, tectonic and gravity grids is based on the integrated mapping performed using the Generic Mapping Tools (GMT) programming suite. Mapping of the submerged features (Broken Ridge, Crozet Islands, seafloor fabric, orientation, and frequency of magnetic anomalies) enables analysis of their correspondence with free-air gravity and magnetic anomalies, geodynamic setting, and seabed structure in the southwest Indian Ocean. The results show that integrating the datasets using advanced cartographic scripting language improves identification and visualization of the seabed objects. The results include 11 new maps of the region covering the Kerguelen Plateau and southwest Indian Ocean. This study contributes to increasing the knowledge of the seafloor structure in the French Southern and Antarctic Lands. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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11 pages, 2906 KiB

Open AccessArticle

Automating the Management of 300 Years of Ocean Mapping Effort in Order to Improve the Production of Nautical Cartography and Bathymetric Products: Shom’s Téthys Workflow

by Julian Le Deunf, Thierry Schmitt, Yann Keramoal, Ronan Jarno and Morvan Fally

Geomatics 2023, 3(1), 239-249; https://doi.org/10.3390/geomatics3010013 - 22 Feb 2023

Cited by 2 | Viewed by 1996

Abstract

With more than 300 years of existence, Shom is the oldest active hydrographic service in the world. Compiling and deconflicting this much history automatically is a real challenge. This article will present the types of data Shom has to manipulate and the different [...] Read more.

With more than 300 years of existence, Shom is the oldest active hydrographic service in the world. Compiling and deconflicting this much history automatically is a real challenge. This article will present the types of data Shom has to manipulate and the different steps of the workflow that allows Shom to compile over 300 years of bathymetric knowledge. The Téthys project for Shom will be presented in detail. The implementation of this type of process is a scientific, algorithmic, and infrastructure challenge. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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14 pages, 9913 KiB

Open AccessArticle

Performing a Sonar Acceptance Test of the Kongsberg EM712 Using Open-Source Software: A Case Study of Kluster

by Eric Younkin and S. Harper Umfress

Geomatics 2022, 2(4), 540-553; https://doi.org/10.3390/geomatics2040029 - 29 Nov 2022

Viewed by 2574

Abstract

In the world of seafloor mapping, the ability to explore and experiment with a dataset in its raw and processed forms is critical. Kluster is an open-source multibeam data processing software package written in Python that enables this exploration. Kluster provides a suite [...] Read more.

In the world of seafloor mapping, the ability to explore and experiment with a dataset in its raw and processed forms is critical. Kluster is an open-source multibeam data processing software package written in Python that enables this exploration. Kluster provides a suite of multibeam processing features, including analysis, visualization, gridding, and data cleaning. We demonstrated these features using a recently acquired dataset from a Kongsberg EM712 multibeam echosounder aboard NOAA Ship Fairweather. This test dataset served to illustrate the fundamental analysis abilities of the software, as well as its utility as a troubleshooting tool both in the field and during post-processing. Kluster has the capability to perform the Sonar Acceptance Test in full, including common experiments like the patch test, extinction test, and accuracy test, which are generally performed on new systems. When questions arise regarding the integration or parameter settings of a system, this software allows the user to quickly and clearly visualize much of the raw data and its associated metadata, which is a vital step in any investigative effort. With its emphasis on accessibility and ease of use, Kluster is an excellent tool for users who are inexperienced with multibeam sonar data processing. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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13 pages, 4322 KiB

Open AccessEditor’s ChoiceArticle

Denmark’s Depth Model: Compilation of Bathymetric Data within the Danish Waters

by Giuseppe Masetti, Ove Andersen, Nicki R. Andreasen, Philip S. Christiansen, Marcus A. Cole, James P. Harris, Kasper Langdahl, Lasse M. Schwenger and Ian B. Sonne

Geomatics 2022, 2(4), 486-498; https://doi.org/10.3390/geomatics2040026 - 11 Nov 2022

Cited by 5 | Viewed by 4688

Abstract

Denmark’s Depth Model (DDM) is a Digital Bathymetric Model based on hundreds of bathymetric survey datasets and historical sources within the Danish Exclusive Economic Zone. The DDM represents the first publicly released model covering the Danish waters with a grid resolution of 50 [...] Read more.

Denmark’s Depth Model (DDM) is a Digital Bathymetric Model based on hundreds of bathymetric survey datasets and historical sources within the Danish Exclusive Economic Zone. The DDM represents the first publicly released model covering the Danish waters with a grid resolution of 50 m. When modern datasets are not available for a given area, historical sources are used, or, as the last resort, interpolation is applied. The model is generated by averaging depths values from validated sources, thus, not targeted for safety of navigation. The model is available by download from the Danish Geodata Agency website. DDM is also made available by means of Open Geospatial Consortium web services (i.e., Web Map Service). The original datasets—not distributed with the model—are described in the auxiliary layers to provide information about the bathymetric sources used during the compilation. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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17 pages, 6949 KiB

Open AccessArticle

Effective Automated Procedures for Hydrographic Data Review

by Giuseppe Masetti, Tyanne Faulkes, Matthew Wilson and Julia Wallace

Geomatics 2022, 2(3), 338-354; https://doi.org/10.3390/geomatics2030019 - 25 Aug 2022

Cited by 3 | Viewed by 3193

Abstract

Reviewing hydrographic data for nautical charting is still a predominately manual process, performed by experienced analysts and based on directives developed over the years by the hydrographic office of interest. With the primary intent to increase the effectiveness of the review process, a [...] Read more.

Reviewing hydrographic data for nautical charting is still a predominately manual process, performed by experienced analysts and based on directives developed over the years by the hydrographic office of interest. With the primary intent to increase the effectiveness of the review process, a set of automated procedures has been developed over the past few years, translating a significant portion of the NOAA Office of Coast Survey’s specifications for hydrographic data review into code (i.e., the HydrOffice applications called QC Tools and CA Tools). When applied to a large number of hydrographic surveys, it has been confirmed that such procedures improve both the quality and timeliness of the review process. Increased confidence in the reviewed data, especially by personnel in training, has also been observed. As such, the combined effect of applying these procedures is a novel holistic approach to hydrographic data review. Given the similarities of review procedures among hydrographic offices, the described approach has generated interest in the ocean mapping community. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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18 pages, 2092 KiB

Open AccessFeature PaperArticle

Multigrid/Multiresolution Interpolation: Reducing Oversmoothing and Other Sampling Effects

by Daniel Rodriguez-Perez and Noela Sanchez-Carnero

Geomatics 2022, 2(3), 236-253; https://doi.org/10.3390/geomatics2030014 - 22 Jun 2022

Cited by 3 | Viewed by 3094

Abstract

Traditional interpolation methods, such as IDW, kriging, radial basis functions, and regularized splines, are commonly used to generate digital elevation models (DEM). All of these methods have strong statistical and analytical foundations (such as the assumption of randomly distributed data points from a [...] Read more.

Traditional interpolation methods, such as IDW, kriging, radial basis functions, and regularized splines, are commonly used to generate digital elevation models (DEM). All of these methods have strong statistical and analytical foundations (such as the assumption of randomly distributed data points from a gaussian correlated stochastic surface); however, when data are acquired non-homogeneously (e.g., along transects) all of them show over/under-smoothing of the interpolated surface depending on local point density. As a result, actual information is lost in high point density areas (caused by over-smoothing) or artifacts appear around uneven density areas (“pimple” or “transect” effects). In this paper, we introduce a simple but robust multigrid/multiresolution interpolation (MMI) method which adapts to the spatial resolution available, being an exact interpolator where data exist and a smoothing generalizer where data are missing, but always fulfilling the statistical requirement that surface height mathematical expectation at the proper working resolution equals the mean height of the data at that same scale. The MMI is efficient enough to use K-fold cross-validation to estimate local errors. We also introduce a fractal extrapolation that simulates the elevation in data-depleted areas (rendering a visually realistic surface and also realistic error estimations). In this work, MMI is applied to reconstruct a real DEM, thus testing its accuracy and local error estimation capabilities under different sampling strategies (random points and transects). It is also applied to compute the bathymetry of Gulf of San Jorge (Argentina) from multisource data of different origins and sampling qualities. The results show visually realistic surfaces with estimated local validation errors that are within the bounds of direct DEM comparison, in the case of the simulation, and within the

10 %

of the bathymetric surface typical deviation in the real calculation. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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Review

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24 pages, 4029 KiB

Open AccessFeature PaperReview

Introducing Smart Marine Ecosystem-Based Planning (SMEP)—How SMEP Can Drive Marine Spatial Planning Strategy and Its Implementation in Greece

by Stilianos Contarinis, Byron Nakos and Athanasios Pallikaris

Geomatics 2022, 2(2), 197-220; https://doi.org/10.3390/geomatics2020012 - 13 May 2022

Viewed by 6576

Abstract

This paper introduces smart marine ecosystem-based planning (SMEP), a marine spatial planning (MSP) strategy for more participatory and responsive marine governance by leveraging “smart” digital services. SMEP denotes an iterative MSP process with planning cycles that incorporate continuous data gathering of spatial–temporal natural [...] Read more.

This paper introduces smart marine ecosystem-based planning (SMEP), a marine spatial planning (MSP) strategy for more participatory and responsive marine governance by leveraging “smart” digital services. SMEP denotes an iterative MSP process with planning cycles that incorporate continuous data gathering of spatial–temporal natural phenomena and human activities in coastal and marine areas, with ongoing data mining to locate key patterns and trends, to strive for periodic refinement of the MSP output. SMEP aims to adopt an ecosystem-based approach, taking into account both living and nonliving aspects of the marine environment, and making use of all available spatial data at various resolutions. In pursuit of SMEP implementation, the paper examines the current state of the MSP process in Greece and relates its long-term success with the establishment of a marine spatial data infrastructure (MSDI), employing contemporary nautical cartography standards along with hydrospatial data services. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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Other

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22 pages, 15308 KiB

Open AccessEditor’s ChoiceProject Report

A Wide-Area Deep Ocean Floor Mapping System: Design and Sea Tests

by Paul Ryu, David Brown, Kevin Arsenault, Byunggu Cho, Andrew March, Wael H. Ali, Aaron Charous and Pierre F. J. Lermusiaux

Geomatics 2023, 3(1), 290-311; https://doi.org/10.3390/geomatics3010016 - 22 Mar 2023

Cited by 4 | Viewed by 6239

Abstract

Mapping the seafloor in the deep ocean is currently performed using sonar systems on surface vessels (low-resolution maps) or undersea vessels (high-resolution maps). Surface-based mapping can cover a much wider search area and is not burdened by the complex logistics required for deploying [...] Read more.

Mapping the seafloor in the deep ocean is currently performed using sonar systems on surface vessels (low-resolution maps) or undersea vessels (high-resolution maps). Surface-based mapping can cover a much wider search area and is not burdened by the complex logistics required for deploying undersea vessels. However, practical size constraints for a towbody or hull-mounted sonar array result in limits in beamforming and imaging resolution. For cost-effective high-resolution mapping of the deep ocean floor from the surface, a mobile wide-aperture sparse array with subarrays distributed across multiple autonomous surface vessels (ASVs) has been designed. Such a system could enable a surface-based sensor to cover a wide area while achieving high-resolution bathymetry, with resolution cells on the order of 1 m² at a 6 km depth. For coherent 3D imaging, such a system must dynamically track the precise relative position of each boat’s sonar subarray through ocean-induced motions, estimate water column and bottom reflection properties, and mitigate interference from the array sidelobes. Sea testing of this core sparse acoustic array technology has been conducted, and planning is underway for relative navigation testing with ASVs capable of hosting an acoustic subarray. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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