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Article
Peer-Review Record

A Comprehensive Evaluation of Flooding’s Effect on Crops Using Satellite Time Series Data

Remote Sens. 2023, 15(5), 1305; https://doi.org/10.3390/rs15051305
by Shuangxi Miao 1,2, Yixuan Zhao 1,2, Jianxi Huang 1,2,*, Xuecao Li 1,2, Ruohan Wu 1,2, Wei Su 1,2, Yelu Zeng 1,2, Haixiang Guan 1,2, Mohamed A. M. Abd Elbasit 3 and Junxiao Zhang 4
Reviewer 1:
Reviewer 2:
Reviewer 3:
Reviewer 4:
Remote Sens. 2023, 15(5), 1305; https://doi.org/10.3390/rs15051305
Submission received: 27 January 2023 / Revised: 24 February 2023 / Accepted: 24 February 2023 / Published: 26 February 2023
(This article belongs to the Special Issue Crop Quantitative Monitoring with Remote Sensing)

Round 1

Reviewer 1 Report

Synthetic Aperture Radar (SAR) data was employed to assess the damage of flood in Henan province, July 17, 2021. This is very interesting research. But some issues should be addressed. Firstly, the accuracy for double-Gaussian model should provide. Then the discussion part should be one dependent section rather than mixed with Result.

Major issues:

1.       You mention that “most of these studies only focus on the changes in the water area, with limited efforts on exploring the impact of flooding on crops”. Below research also make some attempt to assess the affect of flood for crops in Mozambique. So, the improvement of you research should be further concluded. Such as the classification of disaster levels

Bofana, J., Zhang, M.; Wu, B.; Zeng, H.;Nabil, M.; Zhang, N.; Elnashar, A.; Tian, F. How long did crops survive from floods caused by Cyclone Idai in Mozambique detected with multi-satellite data. Remote Sensing of Environment, 2022, 269: 112808.

2.       Line 125-126: What is the standard for three degree of crop damage? Figure 2 is informative. If you could link the figure with satellite images, it will provide more knowledge of crop damage and corresponding satellite image pattern.

3.       The discussion part is better to be independent section. Then the advantage and drawbacks of this research can be further explained.

4.       After the floods recede, the government encourages farmers to re-planted crops, such as vegetables and proved subsides. This will lead to the uncertainty of recovery analysis by comparing previous NDVI value with afterwards. The higher NDVI after the disaster may be caused by newly planted crops, not by the recovery of crops growing before the disaster. This point can be added in the discussion part. Also, more comparison should be done with previous research, such as the work in Mozambique(Bofana, 2022).

Minor issues:

1.       Line 15:” once-in-a-millennium flooding” need reference, you may add in introduction. Or avoid this terminology.

2.       Line 40-42: When you list the specific number, the readers may couldn’t catch the points quickly without a comparison. The percentage of increase is easier to understand.

3.       Could you provide the accuracy of Figure 4?

4.       The preprocess for Sentinel-1 SAR data is unclear.

5.       “The NDVI ratio between these two epochs across these four damage levels indicates crops' resilience. If this value is greater than 1, it means that the crops are gradually recovering after the disaster.” This is not clear.

6.       Figure 5, what is the background of grey?

7.       If you could link figure 6 with figure 2, it will be interesting and informative.

8.       Figure 7, what is the reason for the drop of NDVI on July 31 for normal crops. If the crop is maize, the NDVI curve should be the shape of slightly crop damage.

 

Author Response

Thanks so much for these kind comments and suggestions.

We have revised the manuscript point by point according to your comments.

We appreciate and hope that the revised version is acceptable for publication in your journal!

Author Response File: Author Response.docx

Reviewer 2 Report

Thank you for your interesting research paper and it is very important to suggest new indicator to provide some guidance to local government and citizen for flood disaster damage. However, I have several comments to refine / improve your paper as follow.

 

1)    About inundated area estimation accuracy, I could not find any information about inundated area (flood extent) using S1 in your paper. It is very important to know the accuracy to estimate flooding impacts. In addition, you apply two date data (before/after) with threshold of gaussian model. I believe VH polarization is powerful for this kind of study. Do you use VV/VH or what polarization?

2)    About severe damage indicator, I could not find any rule of your classification using ground base survey as training data of RF. Can you please add category definition of damage indicator shown in Figure 6?

3)    In figure 7, there are some anomaly trends in some data in July 31and August 20. Do you have any idea about why it is happened?

4)    To use NDVI, do you also consider the impact of cloud?

5)    In DEM in figure 11 and NDVI in Figure 13, I have a difficult time to understand the difference between normal and serve because there is not big trend at all in my understanding. I believe you need other information about the trend explanation.

Author Response

Thanks so much for these kind comments and suggestions.  We have revised the manuscript point by point according to your comments. We appreciate and hope that the revised version is acceptable for publication in your journal! 

Author Response File: Author Response.docx

Reviewer 3 Report

Dear  authors

please take my points (marked in the MS pdf) into account to enhance the quality of your work.

Comments for author File: Comments.pdf

Author Response

Thanks so much for these kind comments and suggestions.  We have revised the manuscript point by point according to your comments. We appreciate and hope that the revised version is acceptable for publication in your journal! 

Author Response File: Author Response.docx

Reviewer 4 Report

The paper sounds good but needs minor corrections to improve the paper for a large audience on remote sensing aplcation. See my cooment on attached review

Comments for author File: Comments.pdf

Author Response

Thanks so much for these kind comments and suggestions.  We have revised the manuscript point by point according to your comments. We appreciate and hope that the revised version is acceptable for publication in your journal! 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Major issues:

The discussion is too short. Many point deserved further discussed.:

1. The sentinel-1 is the major date source for flood area extraction. Now Sentinle1B is not work not. How is it effect for the flood area extraction in region?

2. Are these three degrees of crop damage appliable for other region? Is there some literature use this standard?

3. Is there some inaccurate source for comparing NDVI before (i.e., one month earlier) and after (i.e., one month later) the flooding event. Such as replant of crops recommended by local government.

4. Limitation of this research and perspective for the future work.

 

Specific:

Line 158-159lack of citation

Line 178-179: You’d better to provide a typical ground photo for each category.

Line 210: Did you use some method to remove the cloud mask?

Author Response

Thanks so much for these kind comments and suggestions.

We have revised the manuscript point by point according to your comments.

We appreciate and hope that the revised version is acceptable for publication in your journal!

Author Response File: Author Response.docx

Reviewer 2 Report

No futuer comment

Author Response

Thanks so much for these kind comments and suggestions.  We have revised the whole manuscript point by point according to your comments. We appreciate and hope that the revised version is acceptable for publication in your journal!

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