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Article
Peer-Review Record

A Technique for Generating Preliminary Satellite Data to Evaluate SUHI Using Cloud Computing: A Case Study in Moscow, Russia

Remote Sens. 2023, 15(13), 3294; https://doi.org/10.3390/rs15133294
by Minh Tuan Le * and Natalia Bakaeva
Reviewer 1:
Reviewer 2:
Remote Sens. 2023, 15(13), 3294; https://doi.org/10.3390/rs15133294
Submission received: 5 June 2023 / Revised: 22 June 2023 / Accepted: 24 June 2023 / Published: 27 June 2023
(This article belongs to the Section Environmental Remote Sensing)

Round 1

Reviewer 1 Report

Dear authors.

I am grateful for the opportunity to review the article "A technique for generating preliminary satellite data to evaluate UHI using cloud computing". The article is devoted to an actual scientific problem. The article has a large number of advantages that I do not see the point in listing. I will indicate only controversial and unclear points that require explanation by the authors. I sincerely hope that the answers to my questions will improve the quality of the article. And as a result, the article will be accepted.

 

1. I would recommend the authors to expand the title – and indicate the region of the study in the title (for example ...).

2. General comment on the quality of the drawings. Drawings of extremely low quality (dpi?). It is impossible to read the coordinate grid in the drawings and consider what is represented on them. I recommend the authors to improve the quality of drawings. I recommend using one style of drawings (including fonts).

3. The authors should distinguish sections 2 and 3 more clearly. Obviously, lines 180-200 should be in section 2. Similarly, lines 339-345. Perhaps this should be indicated in Section 2.4? I recommend that you describe Section 2.4.

4. In Figures 5, 9, 10, check the accuracy of the axis signatures. Specify the units of measurement. Also on the cards justify the need to specify the word VALUE?

5. I recommend that the authors expand sections 1 and 4. I would also recommend expanding the list of references and conducting a more in-depth analysis of the research problem. In section 4, compare the data you received with other regions of the world.

 

 

Author Response

Dear reviewer,

I would like to thank you for taking the time to review my work. Your feedback and constructive criticism are invaluable to me, and they will help me improve my skills and become better at what I do.

Your attention to detail and thoroughness in your review were truly impressive, and I appreciate the effort you put into it. Your suggestions and comments have given me a fresh perspective and helped me see things that I might have missed on my own.

Again, I cannot thank you enough for your time, effort, and expertise. Your feedback has been instrumental in shaping my work, and I look forward to incorporating your suggestions into future projects.

Respone  to comments from 1st Reviewer:

  1. The title of our paper has been revised to indicate the region of the study:

A technique for generating preliminary satellite data to evaluate SUHI using cloud computing: A case Study in Moscow, Russia”.

  1. We have updated the quality of the drawings in the article with a resolution of 300 dpi, the grid coordinates as well as the legend are clearly displayed.
  2. We agree with the reviewer's motion that lines 180-200 and lines 339-345 belong to section 2.4 and have been revised.
  3. In Figures 5, 9, 10 we have edited and clarified the units of measurement as well as captions to make it easier to understand.
  4. Under the suggestion of the reviewer. In part 4, we supplement and extend the results of the analysis of the impact of the surface urban heat island on the urban pollution island of the authors of other countries. Thereby showing the urgency to study the influence of UHI and UPI in Moscow. The extension is in lines 433 - 465.

 

Sincerely,

Professor, Dr. Natalia Bakaeva & Dr. Minh Tuan Le.

Reviewer 2 Report

see word doc

 

Comments for author File: Comments.pdf

see comments

Author Response

Dear reviewer,

I would like to thank you for taking the time to review my work. Your feedback and constructive criticism are invaluable to me, and they will help me improve my skills and become better at what I do.

Your attention to detail and thoroughness in your review were truly impressive, and I appreciate the effort you put into it. Your suggestions and comments have given me a fresh perspective and helped me see things that I might have missed on my own.

Again, I cannot thank you enough for your time, effort, and expertise. Your feedback has been instrumental in shaping my work, and I look forward to incorporating your suggestions into future projects.

Respone  to comments from 2nd Reviewer:

  1. On lines 15, 25 we wrote down the full meaning of the acronyms. In which, SUHI is surface urban heat island, UPI is urban pollution island and UTFVI is Urban Thermal Field Variance Index.
  2. we would like to replace the word "fine dust" with the more accurate word "particulate matter (PM)".
  3. Based on Figure 4 we would like to provide additional explanations as follows:
  • The NDVI index measures the amount of green in an image. The NDVI index value will range from -1 to 1, with values closer to 1 showing a denser green. Based on the pa-rameters shown in Figure 4, the NDVI index of Moscow gradually decreased from 0.794 (1997 yr.) to 0.563 (2021), showing a trend of vegetation decline in Moscow.
  • The Normalized Burn Ratio (NBR) index is commonly used to quantify forest fire zones. This index is a ratio between the wildfire wavelengths and the vicinity's average wavelengths. The NBR index will represent burnt areas with lower values than unburnt areas. In Figure 4, Moscow's NBR index decreased from 0.704 (1997 yr) to 0.45 (2021), in-dicating a tendency for forest fires and shrinking vegetation.
  • The Soil-Adjusted Vegetation Index (SWVI) measures the amount of vegetation along watercourses and open areas used for growing crops. The higher the SWVI index value, the denser the green is displayed. In Figure 4, Moscow's SWVI index decreased from 0.388 (1997 yr.) to 0.253 (2021 yr), indicating a trend of vegetation reduction along watercourses and croplands.
  1. We would like to provide a link to our project so that researchers could use the same lines of code to do the same calculations for the areas they chose to study.
  2. In Figure 9 and 10 we have added time of day.
  3. We agree with the reviewer's comments and have updated the name of the “urban heat island” effect in the paper as “surface urban heat island” effect.
  4. We have updated the reference Shukurov et al. (2020) to the list of references.
  5. We would like to explain more about Table 4 as follows:

The UTFVI values were categorized into six groups corresponding to an environ-mental assessment interpretation. Table 4 presents the threshold values for each urban area's six thermal field dispersion index categories, from no SUHI (excellent) if LSTurban-pixel < LSTurban-mean to strongest (worst) with UFTVI >0.02, a situation that occurs when the value of LSTurban-pixel is several degrees higher than LSTurban-mean.

  1. We have a text error, Fig. 11 is referred to actually Fig. 16 (line 389). We fixed it.

 

Sincerely,

Professor, Dr. Natalia Bakaeva & Dr. Minh Tuan Le.

 

Round 2

Reviewer 1 Report

Accept in present form

Reviewer 2 Report

accept

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