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Remote Sensing
Volume 13
Issue 16
10.3390/rs13163089
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Article
Peer-Review Record

An Enhanced Double-Filter Deep Residual Neural Network for Generating Super Resolution DEMs

Remote Sens. 2021, 13(16), 3089; https://doi.org/10.3390/rs13163089
by Annan Zhou 1, Yumin Chen 1,*, John P. Wilson 2, Heng Su 1, Zhexin Xiong 1 and Qishan Cheng 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2021, 13(16), 3089; https://doi.org/10.3390/rs13163089
Submission received: 25 June 2021 / Revised: 30 July 2021 / Accepted: 2 August 2021 / Published: 5 August 2021
(This article belongs to the Special Issue Perspectives on Digital Elevation Model Applications)

Round 1

Reviewer 1 Report

This article proposed a CNN-based enhanced double-filter deep residual neural network to obtain high-resolution DEM data over a large area. This paper is well written and the objective the results are discussed nicely. The idea and the findings from the articles very helpful to the other researcher in the field. I recommend accepting this article in the present form.

Author Response

Dear reviewer,

 

We feel great thanks for your professional review work on our manuscript.It is an honour to have your approval of our work

 

Thanks again！

Reviewer 2 Report

 

remotesensing-1293591-peer-review-v1

 

The manuscript “An Enhanced Double-filter Deep Residual Neural Network for Generating Super Resolution DEMs” addresses an interesting and up-to-date subject, which adhere to Remote Sensing journal policies.

 

The manuscript contains interesting results, and presents a fairly good RS and GIS application of DEM analysis. The manuscript needs to have improvements before it can be considered for publication

 

In my opinion the manuscript must be improved with the following:

 

  • English improvement and some better phrasing
  • The abstract and M&M needs improvement
  • Additional M&M information, it is unclear what DEM (source) you used and what software
  • Further explain the importance of the study area and how the obtained results can be reproduced on other locations
  • Please explain the limitations of the proposed model and if it is possible to implement in urbanised areas
  • Some figures inside the manuscript should be improved
  • Discussion chapter needs additional improvements and comparative discussions with citations regarding to previous findings

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The revised manuscript demonstrates the author’s commitment in improving the overall paper, thus obtaining a cohesive and interesting article.

Author Response

Dear reviewer,

 

We feel great thanks for your professional review work on our manuscript.It is an honour to have your approval of our work

 

Thanks again！

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