High-Resolution PM_2.5 Estimation Based on the Distributed Perception Deep Neural Network Model

Round 1

Reviewer 1 Report

The paper is well written. However, it seems Figure 1 has been reused without permission. Authors may kindly clarify whether they have reused the figure from another source or they have drawn the image based on the available data. In case, the figure is from another source, the authors have to follow the standard procedures for reusing a figure including- citing the original figure, obtaining permission from the original source etc.

Author Response

Response to Reviewer 1 Comments

Point 1:  The paper is well written. However, it seems Figure 1 has been reused without permission. Authors may kindly clarify whether they have reused the figure from another source or they have drawn the image based on the available data. In case, the figure is from another source, the authors have to follow the standard procedures for reusing a figure including- citing the original figure, obtaining permission from the original source etc.

 

Response 1: Thank you for your comments and kind reminders.  This picture doesn't have these problems(Due to the change of content, the number of this figure is Fig.2).  Besides, I remade the picture. Translate Chinese into English.  Thank you again for your advice.

Reviewer 2 Report

1、Line 79 “resualting in a single…” please elaborate clearly.

2、Table1 and line 288, the format of the units should be checked.

3、line 206, the format of the context should be checked.

4、lines 235-242, please explain more on how did the authors address the problem of “spatially”.

5、lines 248 and 410, check the format of the variables.

6、lines 358-367, how did the authors performed the linear transformation for “full connected layer” please explain.

Author Response

Please see the attachment. And thank you for your valuable advice.

Author Response File: Author Response.pdf

Reviewer 3 Report

The paper topic is interesting, this paper proposes a spatio-temporal
multi-view interpolation model to improve the interpolation efficiency, however, there are some recommendations to authors to improve the paper.

1- The paper contribution must be clearly highlighted.

2- The research methodology figure is missing

3- The Interpolation algorithm, better to put in a table using the line numbers

4- The figure resolution is not good (Figure 6, and Figure 7).

5- Abstract need to rewrite and highlight the paper objective (add an introduction, problem statement, exiting methods, the paper objective, the results, and the benefits of the paper)

Author Response

Please see the attachment. And thank you again for your valuable advice.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

The paper has been improved compared to the previous one.