Next Article in Journal
Application of Deep Neural Network to Predict the High-Cycle Fatigue Life of AISI 1045 Steel Coated by Industrial Coatings
Next Article in Special Issue
On the Genesis of the South China Sea Mesoscale Eddies
Previous Article in Journal
Buckling of a Composite Cylindrical Shell with Cantilever-like Boundary Conditions under Hydrostatic Pressure
Previous Article in Special Issue
Estimation of Wave-Breaking Index by Learning Nonlinear Relation Using Multilayer Neural Network
 
 
Article
Peer-Review Record

Investigating Spatial Distribution of Green-Tide in the Yellow Sea in 2021 Using Combined Optical and SAR Images

J. Mar. Sci. Eng. 2022, 10(2), 127; https://doi.org/10.3390/jmse10020127
by Yufei Ma 1, Kapo Wong 2, Jin Yeu Tsou 3 and Yuanzhi Zhang 1,3,*
Reviewer 1:
Reviewer 2: Anonymous
J. Mar. Sci. Eng. 2022, 10(2), 127; https://doi.org/10.3390/jmse10020127
Submission received: 4 December 2021 / Revised: 6 January 2022 / Accepted: 12 January 2022 / Published: 19 January 2022
(This article belongs to the Special Issue Data Modelling for Coastal-Ocean Environments and Disasters)

Round 1

Reviewer 1 Report

This is actually a good work done by authors. Still I have some queries, which are marked in the review section of manuscript. I request you to kindly address the queries and make necessary changes in the manuscript. 

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

Thank you for your comments. We have revised and improved according to your suggestions.

Yours sincerely,

Yuanzhi Zhang

On behalf of all co-authors

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper is a study to investigate green tide using a combination of optical images and SAR images. Research on grasping the green tide has been very active in recent years, centering on the FAI algorithm. Improving the frequency of observations using SAR images is an extremely important theme for the field of remote sensing. However, this paper cannot evaluate the reliability of the green tide distribution because the validity of the analysis results of optical and SAR images has not been evaluated. Therefore, it should be rejected unless the following points are corrected.

 

  1. The derivation of the result in Figure 3 is too sudden. The author should show not only Figure 2 but also an example of the processing process of the optical image before binarization and the SAR image. For example, it is necessary to present the original RGB image (optical), DVI image (optical), original GRDvv image (SAR), and dab image (SAR) at a minimum.
  2. What is the rationale for the distribution in Figure 3? Verification using field data (validity evaluation of green tide distribution extracted by satellite) is required.
  3. The method of detecting green tide by SAR is ambiguous. The rationale for binarizing the contrast between Ulva proliferation and seawater by SAR in 2.2.1 should be shown in figures and texts. This is because the area of the green tide distribution is easily changed by this process. In general, the detection of green tide by SAR is more difficult than that by optics, so you should carefully consider the validity of your method.

That’s all

Author Response

Dear Reviewer,

Thank you for your comments. We have revised and improved according to your suggestions.

Yours sincerely,

Yuanzhi Zhang

On behalf of all co-authors

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Although not sufficient, the reviewer's point has been corrected. Therefore, I accept it.

Back to TopTop