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Article
Peer-Review Record

General Five-Component Scattering Power Decomposition with Unitary Transformation (G5U) of Coherency Matrix

Remote Sens. 2023, 15(5), 1332; https://doi.org/10.3390/rs15051332
by Rashmi Malik 1, Gulab Singh 2,*, Onkar Dikshit 1 and Yoshio Yamaguchi 3
Reviewer 1:
Reviewer 2:
Remote Sens. 2023, 15(5), 1332; https://doi.org/10.3390/rs15051332
Submission received: 19 December 2022 / Revised: 30 January 2023 / Accepted: 25 February 2023 / Published: 27 February 2023
(This article belongs to the Special Issue SAR, Interferometry and Polarimetry Applications in Geoscience)

Round 1

Reviewer 1 Report

The paper deals with the solution of inverse problems to retrieve 5 powers from POLSAR data. Reducing the number of unknowns in an inverse problem containing noise can provide a stable solution. Then, the concept of this proposed method seems appropriate. The manuscript is interesting and well written, and the proposed methodology is clear and innovative for scattering power decomposition of POLSAR data. I thus recommend publication after the following minor issues are addressed:

1)     In the experimental results, G5U tends to have a strong double scattering component at the location of the hill areaa. From the concept of azimuth shift, I think that the surface scattering component is stronger than the double scattering component. Moreover, on hills, there is a slope. In this case, the main scattering components are the surface scattering and volume scattering models. Authors know very well the following paper.

Anthony Freeman, “Fitting a Two-Component Scattering Model to Polarimetric SAR Data From Forests”,     IEEE Transactions on Geoscience and Remote Sensing 45(8):2583 – 2592, September 2007.

On the slope area, the double scattering component was not considered. The author should comment on this matter.

2)   In judging the quality of image decomposition, I think that frequency should also be a parameter in the case of POLSAR. However, in this manuscript, only polarization data of PALSAR2 of L-band SAR is used. Polarization data results for other frequencies should also be added. (If possible)

3)     At line 305 in pp.8, I think that “L-band” of “the L-band San Francisco quad pol. data. ..” is not needed.

 

 

 

Author Response

Attached.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Scattering power decomposition is very important for SAR polarimetric classification et al. A decomposition method is proposed in this manuscript. By preprocessing coherency matrix, surface scattering, double bounce scattering, volume scattering, oriented dipole scattering and dipole scattering powers are retrieved directly.

There are some points to be modified:

1. In section 2 and 3, some theories and methods are quoted from the other documents. You should mark the references.

2. Many materials are the same as Reference [10]. For example, most of section 2.1 and 2.2, most of Fig. 3, et al. The repeated contents are suggested to be deleted. The statements should be focused on the work of this manuscript.

3. In data experiments, the comparison between G5U and G4U should be emphasized. What is the new advantages from G5U on the basis of G4U?

Author Response

Attached.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thanks for the replies.

It is suggested to modify Fig.2 to emphasize G5U's difference from G4U.

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