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Peer-Review Record

An Automatic Method for Black Margin Elimination of Sentinel-1A Images over Antarctica

Remote Sens. 2020, 12(7), 1175; https://doi.org/10.3390/rs12071175
by Xianwei Wang 1,* and David M. Holland 1,2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2020, 12(7), 1175; https://doi.org/10.3390/rs12071175
Submission received: 4 March 2020 / Revised: 1 April 2020 / Accepted: 1 April 2020 / Published: 6 April 2020
(This article belongs to the Section Environmental Remote Sensing)

Round 1

Reviewer 1 Report

In this paper, an edge detector using a normal distribution and the maximum image gradient is designed to detect edges along the boundary to image center (BC) direction. Additionally, an automatic method to derive Black Margin (BM) of Sentinel-1A GRD images is designed. It has been proved with various applications that the use of Sentinel-1A gives successful results. Thus a solution for removing BM will be very useful for the applications covering large study areas, which will remove the restrictions along the large image margins as poor quality data.

To my knowledge, this paper is analytically consistent. The statistical analyses are satisfactory. Therefore my decision is "accept as is".

Author Response

Thank you for the review.

Reviewer 2 Report

The paper proposes a method to identify and remove black margins captured by Sentinel-1A satellites. 

From my understanding the paper has been well written. There are some questions in general that I have regarding the methodology followed to report errors. 

Is there a standard convention used to report error in range of few pixels ? I mean to say is , how can the authors effectively mention the error range within a few pixels? Please provide them as a feedback and mention it in the paper so that I can better understand its effectiveness in this context. 

The method provided comparable accuracy with human estimation. How is the human estimation of black margin carried out ? It would be a good idea to include that discussion for researchers who are not experts in remote sensing image rectification. 

Are there any pre-existing automated tools for black margin extraction that the method can be compared to such as automated bounding boxes ?

I would also recommend some editing changes 

  1. Equations can be formatted for better understanding. (Lines 237-238)
  2. Line 61: Move the URL to the reference section. 
  3. Figure 6a-d - Chart titles regarding image names are very small to be legible. 

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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