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Peer-Review Record

A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation

Remote Sens. 2022, 14(16), 3858; https://doi.org/10.3390/rs14163858
by Taoning Mao 1, Wei Shangguan 1,*, Qingliang Li 2, Lu Li 1, Ye Zhang 1, Feini Huang 1, Jianduo Li 3, Wei Liu 4 and Ruqing Zhang 1
Reviewer 1:
Reviewer 2:
Remote Sens. 2022, 14(16), 3858; https://doi.org/10.3390/rs14163858
Submission received: 3 July 2022 / Revised: 3 August 2022 / Accepted: 5 August 2022 / Published: 9 August 2022
(This article belongs to the Section AI Remote Sensing)

Round 1

Reviewer 1 Report

My sincere congratulations to the authors, although there are works with similar objectives in the bibliography, the proposed methodology is adequately detailed and facilitates the interpretation of the results obtained, showing an arduous scientific and technical work for its processing. I encourage you to continue on the path you have begun.

Author Response

Thank you for the positive comments and encouragement on our future work.

Reviewer 2 Report

Dear colleagues,

I believe your manuscript may be helpful for a wide audience. However, there are a few minor flaws and problems, including numerous typos.

The goals of the study should be noted in some very explicit manner at the end of the Introduction.

Some parts of the text (e.g., lines 143-146, ) should be re-written because some ideas should be explained in a very explicit manner.

In line 20, I suggest the word "Novel" should be removed or another appropriate word should be used.

In lines, 162-164 author mentioned the reason for the sensor breakdown and they have deleted some values (high and low) to control the quality but my question about the data accuracy is if the sensor may occur to breakdown how can we rely on data and what was the measuring unit author have defined for abnormal values to be deleted. The accuracy statement should be mentioned.

In line 204 there is a proper citation available on the USGS website for SRTM.

In line 226 it's written flow chat > flow chart. Also in line 257.

In Discussion, "Authors should discuss the results and how they can be interpreted in perspective of previous studies and the working hypotheses. The findings and their implications should be addressed in the broadest context possible and the limitations of the work highlighted. It is also essential to discuss the strengths and limitations of one’s study. Comments on sources of uncertainty and error are appropriate for most papers. Future research directions may also be highlighted.

Author Response

please see the word file

Author Response File: Author Response.docx

Reviewer 3 Report

The article is interesting, as it deals with the “spatial downscaling method for remote sensing soil moisture based on random forest considering soil moisture memory and mass conservation”. The authors assessed downscaled SM in the Pearl River Basin of China. The methodology is very comprehensive and the results are encouraging.  Although the study itself is valuable, the advantages of your study were not sufficiently appealed and restructuring might be required in order to improve the scientific level.

Moreover, the novelty of this work should be comprehensively presented. As the paper stands right now it needs some minor improvements. The primary concern I have are listed below:

1)     I think the results can be presented a bit better. You can identify instances where downscaled SM fails. Are there any particular commonalities where the new downscaling model with lagged SM variables fails/succeeds? That would be useful to the readers.

 

2)      On what basis did you choose the auxiliary data was not sufficiently put.  The readers may ask, why don’t we use other SM products such as  ESA CCI in this downscaling scheme. 

Author Response

Please see the word file

Author Response File: Author Response.docx

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