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Article
Peer-Review Record

A Multiscale Productivity Assessment of High Andean Peatlands across the Chilean Altiplano Using 31 Years of Landsat Imagery

Remote Sens. 2019, 11(24), 2955; https://doi.org/10.3390/rs11242955
by Roberto O. Chávez 1, Duncan A. Christie 2,3,*, Matías Olea 1 and Talia G. Anderson 4
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3:
Remote Sens. 2019, 11(24), 2955; https://doi.org/10.3390/rs11242955
Submission received: 31 October 2019 / Revised: 5 December 2019 / Accepted: 6 December 2019 / Published: 10 December 2019
(This article belongs to the Special Issue Remote Sensing of Peatlands II)

Round 1

Reviewer 1 Report

Thank you for providing a well written and interesting manuscript. I enjoyed reading your paper and am impressed by the amount of work that has been undertaken. The figures are all very neat, tidy and easy to understand. I have a few small comments, but I am happy to recommend your paper for review. 1) You processed an immense amount of data! Why not use Google Earth Engine? There is no methodological advantage with GEE but it might have been easier for you to extract all of the "good" pixels. If you are interested in collaborating to move this analysis into GEE let me know and I will contact you after your paper is published. 2) In section 2.3, you mention that you use the maximum extent of the peatlands to assess expansion and contract. I found this a bit confusing (but eventually think I understand). Perhaps a few more sentences explaining how you assessed expansion/contraction would be helpful. 3) In section 3.1, you mention the mean size of the peatlands is 0.09 km2 - could you put this in context of the size of a Landsat pixel for the readers? 4) In section 3.2 you mention "0.79 agreement". What does this mean? is this R2? Perhaps you just need to remind the reader what agreement method you are using? 5) At the regional and individual scale, you don’t really specify the means are applied to which time frame. You say they used their full digital inventory. So is it the mean per year? Or the mean of the 31 years you have? I think I need bit of clarification here. 6) You reconstructed the annual phenological cycle and based on the data you have from the growing seasons, you reconstructed the cycle for a whole year, for all the years you had. Then you did a NDVI yearly sum with this reconstructed data. Correct? I’m not sure where the mean calculated in the previous step comes in at this step. Do you reconstruct the annual phenological cycle with the mean? Again, I think I just need a bit of clarification.

Author Response

Dear reviewer, please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Review of Chavez et al. Nov 2019

This is a very interesting and important paper, I am glad I had the opportunity to provide a review.

In this work, the authors analyze a very large Landsat dataset extracting the NDVI signal in order to describe the evolution of peatland vegetation. Considering the amount of work put into this analysis, I believe that the inventory produced by the authors is of great value.

I only have some minor comments and suggestions. As a general comment, I strongly suggest the authors to merge Appendix 1 into the main text. In the present form, I found the Methods section too short and incomplete. Further descriptions of the methods applied are needed and the descriptions included in Appendix 1 can help.

Paragraph 2.2 – Study site: What vegetation develops in these peatlands? what is the typical biomass and density? Far more details about the vegetation is needed considering that the methodology aims at capturing the vegetation cycle.

Paragraph 2.3: it is not clear to me how the correlation between NDVI and biomass of this specific vegetation (what vegetation is it?) has been established. Why 50-55 Landsat scenes were selected? Why this specific range? The Appendix 1 should be merged also because here it is not clear how the threshold 0.23 was selected.

Paragraph 2.3 : one word is missing in this sentence: “With npphen, all NDVI observations (Figure 4a) are by the phenological year (from July to the following June for the Southern Hemisphere) (Figure 4b).”

Paragraph 2.5: please describe in detail the methods, so that readers do not have to download the cited papers to understand your methodology.

Fig. 5: very interesting results indeed! Looking at Fig. 5 a and c I think it would be very interesting to look at the correlation between elevation and NDVI, i.e. selecting different range of elevation and looking at the distribution of NDVI within each elevation range.

I suggest the publication of this manuscript with minor revisions.

 

Author Response

Dear reviewer, please see the attachment

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors have used 31 Landsat data and discussed Peatland inventory. The study is important but the authors have not stated important of studies. I would like to suggest authors to include discussion of Peatland in climate change. In the abstract. authors may mention that they have analyzed 31 years data (1986-2017). I wouldAVHRR with Landsat, although resolution could be a problem but overall one can compare NDVI.

It will be interesting if the authors analyze surface temperature data at three different locations during the study periods so that readers can see how the Peatland area is related to surface temperature. English of the manuscript must be carefully checked.        

Author Response

Dear reviewer, please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Manuscript may be accepted

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