Special Issue "Geological Seafloor Mapping"

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Geophysics".

Deadline for manuscript submissions: 30 December 2018

Special Issue Editors

Guest Editor
Dr. Markus Diesing

Geological Survey of Norway
Website | E-Mail
Interests: marine geology; habitat mapping; sediment dynamics; organic carbon; spatial prediction; object-based image analysis; machine learning
Guest Editor
Dr. Peter Feldens

Leibniz Institute for Baltic Sea Research Warnemünde
Website | E-Mail
Interests: marine geology; hydroacoustic methods; geomorphology; geology of the Baltic Sea; habitat mapping

Special Issue Information

Dear Colleagues,

The ocean floor is vast, yet largely uncharted. Although an ambitious pledge was made to map the entire ocean floor by the year 2030, this only pertains to the bathymetry of the oceans. Mapping the geological makeup of the seafloor remains one of the great challenges in marine geoscience. Recent advances in data acquisition, processing, analysis and dissemination should, however, put us in a better position to deliver accurate and detailed maps of seafloor sediment and substratum types.

A significant part of the analysis rests on the acoustic backscatter intensity of the seafloor gathered with sidescan sonars and, more recently, multibeam echosounders (MBES). We have witnessed significant advances in this field of technology in recent years, including global efforts to standardise the collection and processing of calibrated backscatter data and the introduction of multispectral MBES for seafloor mapping. Such advances will ultimately lead to better maps of the geology of the seafloor and the distribution of benthic habitats.

Progress has also been made by introducing methods of image analysis, spatial prediction and machine learning, widely utilised in terrestrial mapping applications, to geological seafloor mapping. These methods have several advantages over traditional mapping ‘by eye’, including repeatability, time-savings, cost-effectiveness and the provision of estimates of accuracy. More recently, attempts have been made in spatially predicting quantitative sediment properties (e.g., grain-size composition) rather than sediment classes. Such studies can also shed light on the relationships between sediment properties and the marine environmental drivers that determine the distribution of sediments on the seafloor.

It is generally acknowledged that due to the high costs involved in collecting marine datasets we should ‘collect once, use many times’. Efficient systems for data search and retrieval make it now much easier to search for relevant datasets and download them from databases.

The aim of this Special Issue of Geosciences is to showcase the latest developments in the field of geological seafloor mapping. We specifically invite contributions addressing the following aspects:

  • Studies assessing the potential of multispectral MBES for geological seafloor mapping
  • Systematic and quantitative comparisons of mapping approaches
  • The impact of spatial scale on mapping performance
  • The assessment and communication of mapping uncertainty and confidence
  • Quantification of the relationships between sediments and environmental drivers
  • Quantification of the relationships between sediments, benthic organisms, and backscatter
  • Case studies from local to global scales making innovative use of legacy data from data repositories

Dr. Markus Diesing
Dr. Peter Feldens
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geosciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 550 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Marine geology
  • Seafloor mapping
  • Sediment
  • Benthic habitats
  • Multibeam echosounder
  • Acoustic backscatter
  • Spatial prediction
  • Image analysis
  • Machine learning
  • Accuracy
  • Confidence
  • Spatial scale

Published Papers (2 papers)

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Research

Open AccessArticle Detection of Stones in Marine Habitats Combining Simultaneous Hydroacoustic Surveys
Geosciences 2018, 8(8), 279; https://doi.org/10.3390/geosciences8080279
Received: 18 June 2018 / Revised: 24 July 2018 / Accepted: 26 July 2018 / Published: 28 July 2018
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Abstract
Exposed stones in sandy sublittoral environments are hotspots for marine biodiversity, especially for benthic communities. The detection of single stones is principally possible using sidescan-sonar (SSS) backscatter data. The data resolution has to be high to visualize the acoustic shadows of the stones.
[...] Read more.
Exposed stones in sandy sublittoral environments are hotspots for marine biodiversity, especially for benthic communities. The detection of single stones is principally possible using sidescan-sonar (SSS) backscatter data. The data resolution has to be high to visualize the acoustic shadows of the stones. Otherwise, stony substrates will not be differentiable from other high backscatter substrates (e.g., gravel). Acquiring adequate sonar data and identifying stones in backscatter images is time consuming because it usually requires visual-manual procedures. To develop a more efficient identification and demarcation procedure of stone fields, sidescan sonar and parametric echo sound data were recorded within the marine protected area of “Sylt Outer Reef” (German Bight, North Sea). The investigated area (~5.900 km2) is characterized by dispersed heterogeneous moraine and marine deposits. Data from parametric sediment echo sounder indicate hyperbolas at the sediment surface in stony areas, which can easily be exported. By combining simultaneous recorded low backscatter data and parametric single beam data, stony grounds were demarcated faster, less complex and reproducible from gravelly substrates indicating similar high backscatter in the SSS data. Full article
(This article belongs to the Special Issue Geological Seafloor Mapping)
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Open AccessArticle Improved Interpretation of Marine Sedimentary Environments Using Multi-Frequency Multibeam Backscatter Data
Geosciences 2018, 8(6), 214; https://doi.org/10.3390/geosciences8060214
Received: 8 May 2018 / Revised: 8 June 2018 / Accepted: 9 June 2018 / Published: 12 June 2018
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Abstract
Backscatter mosaics based on a multi-frequency multibeam echosounder survey in the continental shelf setting of the North Sea were compared. The uncalibrated backscatter data were recorded with frequencies of 200, 400 and 600 kHz. The results showed that the seafloor appears mostly featureless
[...] Read more.
Backscatter mosaics based on a multi-frequency multibeam echosounder survey in the continental shelf setting of the North Sea were compared. The uncalibrated backscatter data were recorded with frequencies of 200, 400 and 600 kHz. The results showed that the seafloor appears mostly featureless in acoustic backscatter mosaics derived from 600 kHz data. The same area surveyed with 200 kHz reveals numerous backscatter anomalies with diameters of 10–70 m deviating between −2 dB and +4 dB from the background sediment. Backscatter anomalies were further subdivided based on their frequency-specific texture and were attributed to bioturbation within the sediment and the presence of polychaetes on the seafloor. While low frequencies show the highest overall contrast between different seafloor types, a consideration of all frequencies permits an improved interpretation of subtle seafloor features. Full article
(This article belongs to the Special Issue Geological Seafloor Mapping)
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Figure 1

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Evaluation of Multispectral Multibeam Backscatter for Seafloor Surficial Geology and Benthic Habitat Mapping
Craig J. Brown
NSERC Industrial Research Chair: Integrated Ocean Mapping Technologies

Seafloor Classification Using Machine Learning: A Review and Perspective
Daniel David Buscombe
Northern Arizona University, Flagstaff, USA

Automating the Physical Characterisation of Reef Habitat Using Terrain Variables
Eimear O’Keeffe and Oliver Tully
Marine Institute, Galway, Ireland

​Acoustically Noisy Substrates in Space and Time: Insights on the Half-Diel Variability of MBES Seafloor Backscatter from Field Measurements in the Belgian Continental Shelf
Giacomo Montereale-Gavazzi 1, 2, Marc Roche 3, Nathan Terseleer 1, Frederic Francken 1, Matthias Baeye 1, Vera Van Lancker 1, 2
1 Royal Belgian Institute of Natural Sciences, Operational Directorate of Nature, Gulledelle 100, B, 1200 Brussels, Belgium
2 Renard Centre of Marine Geology Department of Geology and Soil Science, Geological Institute, Ghent University Krijgslaan 281 s.8, B-9000 Gent, Belgium
3 Federal Public Service Economies, Continental Shelf Service, Boulevard du Roi Albert II, 16, 1000 Brussels, Belgium

Effects of Grain Size Data Aggregation on Multiscale Seabed Sediment Distribution Models
Benjamin Misiuk(a), Markus Diesing(b), Evan Edinger(a), Alec Aitken(c), Trevor Bell(a)
(a) Department of Geography, Memorial University of Newfoundland, St.John's, Newfoundland, Canada
(b) Marine Geology, Geological Survey of Norway, Trondheim, Norway
(c) Department of Geography and Planning, University of Saskatchewan, Saskatoon, Saskatchewan, Canada

Legacy Data: How Decades of Seabed Sampling can Produce Robust Predictions and Versatile Products
Peter J Mitchell1, John Aldridge1 and Markus Diesing2
1 Centre for Environment, Fisheries and Aquaculture Science (Cefas), Pakefield Road, Lowestoft, NR33 0HT, UK.
2Geological Survey of Norway (NGU), Postal Box 6315 Torgarden, 7491 Trondheim, Norway.

New Seafloor Sediment Mappings for the Gulf of Mexico, with Spatial Heterogeneity Statistics
Chris J Jenkins
INSTAAR, University of Colorado at Boulder, USA

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