the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 May 2025
High-resolution hydroacoustic datasets for over 7000 km2 of Southern Baltic
Abstract. This study presents high-resolution hydroacoustic datasets covering over 7,000 km² of Polish Marine Areas in the Southern Baltic, acquired between April 2022 and December 2023 as part of a national initiative to map benthic habitats using advanced sonar technologies. Utilizing a fleet of seven vessels and the expertise of approximately 250 personnel, the project collected bathymetric and side-scan sonar data along more than 95,000 km of survey lines, adhering to International Hydrographic Organization S-44 Order 1a standards. The resulting datasets include detailed bathymetric grids at 50 x 50 cm resolution and sonar mosaics at 20 x 20 cm resolution, with robust quality control ensuring at least 95% data completeness per grid cell. These data provide unprecedented insight into the underwater topography and sediment characteristics of the region, supporting applications in scientific research, environmental management, offshore wind farm planning, and underwater archaeology. The datasets, available at DOI: https://doi.org/10.26408/southern-baltic-hydroacoustic-datasets, lay a solid foundation for future studies and the development of science-informed policies to promote sustainable and resilient marine ecosystems in the Baltic Sea.
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Status: open (until 26 Oct 2025)
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RC1: 'Comment on essd-2025-270', Benjamin Misiuk, 21 Jun 2025
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RC2: 'Image failed to upload', Benjamin Misiuk, 21 Jun 2025
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It seems my attached image failed to upload. I've attached a PDF of my comments with the image here.
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RC2: 'Image failed to upload', Benjamin Misiuk, 21 Jun 2025
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RC3: 'Comment on essd-2025-270', Marc Roche, 24 Sep 2025
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1. General Comments
This manuscript presents a highly valuable hydroacoustic dataset covering over 7,300 km² of the Southern Baltic. It is one of the largest high-resolution mapping initiatives in the region, employing multibeam echosounder (MBES) and side-scan sonar (SSS) surveys under IHO Order 1a standards. The dataset is openly available via DOI and has broad interdisciplinary value for habitat mapping, offshore wind energy, marine archaeology, and environmental monitoring. The dataset is robust, and the article is appropriate for Earth System Science Data. Minor clarifications would strengthen the paper.
2. Specific Comments
- Novelty and usefulness: The dataset is new, cost-intensive, and unique at this scale. Usefulness across disciplines is clear.
- Appropriateness for ESSD: Focuses on dataset acquisition, validation, and accessibility. Some methods sections are overly verbose.
- Data quality: Meets IHO standards with ≥95% completeness. MBES BS processed only to BL0 seriously hinders the use of this data. Legacy datasets heterogeneous.
- Significance: Excellent uniqueness and usefulness; minor issues with completeness.
- Consistency: No inconsistencies. Figures/tables are of good quality.
- Presentation quality: Well structured but verbose in Methods.
- Reusability: Data in GeoTIFF with metadata ensures long-term reuse.
- Reference: checked.
3. Specific questions - remarks
- L76 azoic zones : Do such areas exist? How can we know if there is no life?
- L119 replace (Iho, 2020) with (IHO, 2020)
- General question about quality level S-44 1a order : Have you taken measurements in a reference area where the bathymetry and a reference point are known with precision in order to evaluate the error in Z and XY (= classical cross-check test)?
- Table 3 Scanning frequency means ping rate?
- L185 in proprietary software : Could you clarify that?
- L262 and Tables 4 et 5: Shouldn't the Reson 7125 also be considered in Tables 4 and 5?
4. Suggested Additions for Authors
On MBES backscatter limitation: It should be noted that MBES backscatter data were processed only to BL0 format, meaning no angular compensation or full radiometric corrections were applied. While this ensures consistency and timely delivery, it also limits direct quantitative applications (e.g., sediment classification, habitat modelling). Users may need to perform additional post-processing depending on the intended use.
On legacy dataset heterogeneity: Some legacy datasets (e.g., Słupsk Bank, Koszalin Bay) were integrated into the collection. These differ in resolution and do not include MBES backscatter, which introduces some heterogeneity. They are included to ensure coverage but should be used with caution for comparative analyses.
Citation: https://doi.org/10.5194/essd-2025-270-RC3
Data sets
High-resolution hydroacoustic datasets of the Polish Southern Baltic Sea (2022–2023) Łukasz Janowski et al. https://doi.org/10.26408/southern-baltic-hydroacoustic-datasets
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General comments
Janowski et al. provide a clear description of what appears to be a comprehensive seabed mapping dataset in the Southern Baltic. This is an exciting dataset, and the authors have achieved a high standard of accessibility by making all data open. I believe this is exactly what seabed mapping researchers should be doing to further the field given the great expense and effort required to collect such data, and as we collectively work towards regional and global mapping goals such as Seabed 2030.
The data itself seems to be generally of high quality and usefulness, but some exceptions should be acknowledged. From what I can tell from the manuscript, and from downloading a few samples, the MBES bathymetric data look to be of high quality and resolution – suitable for geomorphic, habitat or other analyses. The authors report that the MBES backscatter were not fully processed, foregoing angular compensation. This is really unfortunate, and limits the usefulness of such an important data source. I cannot understand why the backscatter data were not fully processed, as it seems the authors had access to the necessary tools to do so. If possible, I would encourage the authors to revisit the MBES backscatter at some point and try to update their dataset with an angular-compensated product. The SSS data look to be mostly high quality, but there are some obvious geometric errors that are not mentioned. In fact, the authors state that the SSS data are high quality and free of geometric errors, which is not quite true. See a specific example below.
Specific comments
Abstract. Not clear what the difference is between “detailed bathymetric grids at 50 x 50 cm resolution and sonar mosaics at 20 x 20 cm resolution” in the abstract. I believe “sonar mosaics” refers to side scan backscatter, but perhaps make this clear.
Table 1. I’m not sure what is meant by “Seldom MBES and SSS datasets…”
101-102 and onward. Suggest being consistent with use of abbreviations once they have been introduced throughout the manuscript (e.g., “MBES”, “SSS”).
Figure 1. The quality of this figure could be improved. The base map contains many labels that cannot be read. All labels with the individual survey sheets are too small to be read at normal page size. Legend entries do not need to be complete sentences and could be reduced for conciseness; for example, “The offshore wind energy area excluded from the hydroacoustic study” could just be “Excluded offshore wind area”. This is explained previously in the text.
174-175. I am not sure what is meant by “The processing of bathymetric data included the elimination of acoustic noise and imaging of the seabed regarding mean sea level”. Does imaging refer to backscatter? Consider rewording/rephrasing.
188. It is a shame that angular corrections were not applied to the MBES backscatter. This greatly reduces the utility of the data for other users. I’m not entirely clear on why this wasn’t performed… both the QPS suite and BeamWorx contain functionality for angular correction as part of the backscatter processing, which takes no additional time. Why use proprietary software that cannot perform a basic AVG correction? This seems like a major shortcoming.
Figure 5. Suggest adding some indication of the backscatter units here – maybe just in the caption. It looks to be possibly just signed 8-bit integer values? Some readers may be confused if expecting to see a dB representation. The use of signed integers and a divergent colour ramp is also a bit odd… This is a unipolar variable being mapped (i.e., low to high values). The convention would be a sequential colour scheme ranging from light to dark. A divergent palette makes it look like the negative and positives are meaningful (they are not).
Figure 5. We see the impact of foregoing the angular correction here. The usefulness of these data for any sort of quantitative analysis is greatly reduced.
253-255, 288-305. In these lines, I believe the quality of the SSS data may be overstated. It is stated that, “The final mosaics exhibited strong geometric correctness, with minimal distortion or artefacts, and high contrast, facilitating the discrimination of objects based on shape, size, and shadow”. There are some very obvious geometric discrepancies though, with misalignment of features by at least 20 m (see Figure 1 attached). This is not uncommon for sidescan data, but these limitations should really be acknowledged – these are not perfect datasets.
Figure 1. SSS survey OWF_SSS_20cm_1A.
281-282. I’m not sure I fully agree with this statement. The MBES backscatter were not subjected to full angular correction, and probably are not suitable for quantitative geomorphological/geological/habitat mapping analyses. The processing of these data is essentially incomplete.