Regional Algorithm of Quantitative Assessment of Cyanobacteria Blooms in the Eastern Part of the Gulf of Finland Using Satellite Ocean Color Data

Round 1

Reviewer 1 Report

The paper presents a significant contribution to the assessment of harmful algae blooms. Proposed algorithm was tested with two sets of data (in situ and satellite) and the results are satisfying. The paper is clearly written and well organised. I have only a few minor suggestions to improve the manuscript. 

Specific comments:

Figure 1 could additionally contain a larger map of the Baltic Sea.

L102 The equation should be rewritten or addressed directly with its number in the referenced paper.

Conclusions are too short, consider adding a sentence or two summarizing the performance of the multi-regression algorithm.

Author Response

Thanks for your careful reading and valuable comments. All comments were taken into account in the revised text of the manuscript.

Author Response File: Author Response.pdf

Reviewer 2 Report

In the MS, a regional algorithm for estimating the biomass of cyanobacteria and their bloom area in the Baltic Sea has been developed and validated, the topic is interesting, and the following concerns should be addressed before it goes to any future.

(1) For ABSTRACT, the evaluation of the method should be more detailed and include some quantitative indicators, and the conclusions of spatial and temporal variability should be given.

(2) Lines 81-83 on page 2, why isn’t phytoplankton biomass and chlorophyll sampling from traditional depth (the surface 0-0.5 m).

(3) For 2.3, I think it can be divided into separate section METHODS, and the theory and process of the proposed method (regional algorithm) should be described in detail. The technological flowchart should be added.

(4) Change 5. Conclusion to 5. Conclusions. There are some grammar and spelling errors, the language should be improved be a native speaker of English.

(5) I think the following manuscript can be improved the MS.

https://doi.org/10.1016/j.ocecoaman.2023.106554

https://doi.org/10.1109/TGRS.2022.3215677

 

 

Moderate.

Author Response

Thanks for your careful reading and valuable comments. All comments were taken into account in the revised text of the manuscript.

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors have presented a regional algorithm for estimating cyanobacteria biomass from satellite data in the eastern part of the Gulf of Finland, which was developed based on field measurements conducted during July-August 2012-2014. However, from my perspective, the paper requires significant technical and structural revisions. Here are some suggested improvements:

 

1- Clarify Novelty: The novelty of the research needs to be clearly highlighted in both the abstract and the latter part of the introduction. In the introduction, consider listing the specific novelties and providing a list of the goals that the authors aim to achieve in the manuscript.

 

2- Improved Map of In Situ Data: The map illustrating the in situ data should be enhanced for clarity. A revised version should include information about the northern orientation and the coordinate system. Using a color-coded version could better convey the necessary details.

 

3- Clear Explanation of "Development of a Regional Algorithm": The explanation regarding the development of the regional algorithm for cyanobacteria biomass estimation should be clarified. It's important to explicitly state whether the authors are presenting a new method or if this builds upon previous work. Additionally, the workflow of the research should be clearly presented in the main body of the paper.

 

4- Separate Evaluation Metrics: Consider organizing the evaluation metrics into a separate subsection. This will help provide a clear and structured overview of the metrics used to assess the performance of the algorithm.

 

5- Conclusive Support for Results: The conclusion section should provide comprehensive support for all the results presented in the paper. Ensure that the conclusions drawn align with the findings and results presented throughout the manuscript.

Author Response

Thanks for your careful reading and valuable comments. All comments were taken into account in the revised text of the manuscript.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

I think the concerns have been addressed.

Minor, please check the grammar and spelling carefully.

Author Response

Thanks for your careful reading and valuable comments. We have significantly revised the grammar and spelling of the manuscript, rewriting almost every sentence. We hope that the revision will make the manuscript easier to read.

Reviewer 3 Report

 

Most of my comments were well addressed by the authors. I have some minor suggestions to enhance the readability of the paper.

 

1- Please consider incorporating recent applications of remote sensing data for the Baltic Sea. For instance, there are emerging opportunities to utilize remote sensing data for time-series monitoring of shorelines, classification of coastal regions, and wetland monitoring in the Baltic Sea.

 

References:

https://doi.org/10.1016/j.rse.2017.08.024

https://doi.org/10.3389/fmars.2023.1207524

https://doi.org/10.1016/j.rse.2023.113464

https://doi.org/10.3390/rs14010089

Author Response

Thanks for your careful reading and valuable comments. We have expanded the manuscript by citing all the proposed papers:

There are recent applications of remote sensing data for the Baltic Sea. For instance, there are emerging opportunities to utilize these data for time-series monitoring of shorelines, classification of coastal regions, and wetland monitoring in the Baltic Sea [32-34]. Note that this algorithm can be applied to AERONET-OC Rrs data [35], which are free from atmospheric correction errors.

 

32. Tiede, J., Jordan, C., Moghimi, A. and Schlurmann, P., Long-term shoreline changes at large spatial scales at the Baltic Sea: remote-sensing based assessment and potential drivers. Frontiers in Marine Science, 2023, 10, p.1207524, doi: 10.3389/fmars.2023.1207524.
33. Cazzaniga, I., Zibordi, G. and Mélin, F., 2023. Spectral features of ocean colour radiometric products in the presence of cya-nobacteria blooms in the Baltic Sea. Remote Sensing of Environment, 2023, 287, p.113464, doi: 10.1016/j.rse.2023.113464.
34. Tilstone, G.H.; Pardo, S.; Simis, S.G.H.; Qin, P.; Selmes, N.; Dessailly, D.; Kwiatkowska, E. Consistency between Satellite Ocean Colour Products under High Coloured Dissolved Organic Matter Absorption in the Baltic Sea. Remote Sens. 2022, 14, 89. https://doi.org/10.3390/rs14010089
35. Qin, P., Simis, S.G. and Tilstone, G.H.. Radiometric validation of atmospheric correction for MERIS in the Baltic Sea based on continuous observations from ships and AERONET-OC. Remote sensing of environment, 2017, 200, pp.263-280 https://doi.org/10.1016/j.rse.2017.08.024.