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Article
Peer-Review Record

Greater Greening Trend in the Loess Plateau of China Inferred from Long-Term Remote Sensing Data: Patterns, Causes and Implications

Forests 2022, 13(10), 1630; https://doi.org/10.3390/f13101630
by Wei Guo 1,2,*, Hao He 1, Xiaoting Li 1 and Weigang Zeng 3
Reviewer 1:
Reviewer 2: Anonymous
Forests 2022, 13(10), 1630; https://doi.org/10.3390/f13101630
Submission received: 7 September 2022 / Revised: 25 September 2022 / Accepted: 30 September 2022 / Published: 5 October 2022
(This article belongs to the Special Issue Forest Climate Change Revealed by Tree Rings and Remote Sensing)

Round 1

Reviewer 1 Report

I think that the writing should be revised again, specially in the results and discussion sections

 

Page 2

 

- Line 77: better use “is due to multiple factors

- Line 83: could help in regulating

 

Page 4

 

- Line 129: “using the Python software” I don ´t know if that phrase is propper, maybe use “using Python scripting” instead? Anyway, it would be nice to know what packages and libraries were used.

 

Page 5

 

- Line 199: “vegetation activity in the LP generally increased with a...

- Line 203: “ trend continued reaching maximums in 2013.”

 

Page 6

 

- Line 207: use residual instead of remainder

- Line 211: “Since linear regression analysis has been criticized for its inability to reflect

- Lines 211 to 213: This whole phrase is not clear

 

Page 8

 

- Line 262: “the highest proportion of areas with significantly increasing trend

- Line 265: “GGP had achieved an overall restoration of forests” I think that this statement should be supported by evidence from other studies

 

Page 9

 

- Lines 269 to 270: This paragraph states that the greening trends are a result of the restoration practices, but the next paragraph suggests that the trends in NDVI are closely related to the climatic factors.

 

Page 12

 

- Figure 8: The ranks of the correlation maps should be the same between all subplots, and also it would help to include a legend in each subplot indicating which variable is being correlated. Maybe also mask non-significant correlations

 

Page 14

 

- Line 360: “vegetation dynamics is complex and involves long-term processes

- Line 378: I suggest “BFAST method was found to be helpful for detecting features of vegetation dynamics

- Line 381: use “tailored” instead of “tailor

- Line 387: “which provides hydrothermal conditions” this statement is not accurate and it is not necessary

 

Page 15

 

 

- Line 393: “dynamics” instead of “dynamic

 

- Line 408: “human activities, such as reforestation and land-use change, were the major drivers. Even greater than climatic factors in ABP after the GGP implementation-

 

- Line 417: I think this sub-section should go in the results section

 

Page 16

 

- Line 429: “The major reason behind this reversing trend may be attributed to shortages in the water supply

 

 

 

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

This is a nice paper, well written, good figures, and brings a new approach to monitoring vegetation changes using readily available satellite imagery. I have two suggestions for improvement. 

I am not convinced your conclusions pertaining to vegetation types are founded and think you should be very clear that this is just a hypothesis that could explain your results.

I think it would benefit the paper to discuss other research attempts to monitor vegetation after similar restoration using satellite imagery/NDVI and more laborious approaches. This will help demonstrate the value of your new idea and results, by comparing sensors, processes, and findings. In addition, it would benefit to compare internationally, for readers outside of China. I suggest you include in your intro and/or discussion these two papers:  https://doi.org/10.1016/j.ecoleng.2014.05.012 and https://doi.org/10.1080/01431161.2018.1437297 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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