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Article
Peer-Review Record

Characterizing Canopy Structure Variability in Amazonian Secondary Successions with Full-Waveform Airborne LiDAR

Remote Sens. 2024, 16(12), 2085; https://doi.org/10.3390/rs16122085
by Aline D. Jacon 1, Lênio Soares Galvão 1, Rorai Pereira Martins-Neto 2, Pablo Crespo-Peremarch 3,4, Luiz E. O. C. Aragão 1, Jean P. Ometto 5, Liana O. Anderson 6, Laura Barbosa Vedovato 7, Celso H. L. Silva-Junior 8, Aline Pontes Lopes 1, Vinícius Peripato 1, Mauro Assis 1, Francisca R. S. Pereira 1, Isadora Haddad 1, Catherine Torres de Almeida 9, Henrique L. G. Cassol 1,10 and Ricardo Dalagnol 11,12,*
Reviewer 1:
Reviewer 2:
Reviewer 3: Anonymous
Remote Sens. 2024, 16(12), 2085; https://doi.org/10.3390/rs16122085
Submission received: 6 May 2024 / Revised: 30 May 2024 / Accepted: 6 June 2024 / Published: 9 June 2024
(This article belongs to the Special Issue Retrieving Leaf Area Index Using Remote Sensing)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Secondary successions hold significant potential for actively sequestering carbon in the biomass. This paper primarily investigates the changes in canopy structure of secondary forests in the Amazon at different recovery stages, using FWF LiDAR data for analysis. The work is commendable, but there are still some minor arguments and incomplete experimental results in this paper.

1. Part of the laser signal is backscattered by the forest canopy. Whether it will affect the accurate for representing the vertical canopy structure of secondary successions, and further limiting the comprehensive understanding of the understory structure

 

2. This study has some limitations that should be considered climatological conditions, other factors affect the magnitude and sustainability of the vegetation regeneration process after land abandonment. What is the author's plan for the future research?

Author Response

See in attachment the responses for R1 and other reviewers.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

1. The experimental analysis of the research is well written in the paper. However, the technical methods need to be included in the abstract.

2. Illustrate the difference between various stages of secondary succession in a Figure.

3. The second-stage analysis and third-stage analysis need to be better described. Please elaborate on the technical part of the methodology.

4. It is not understandable why the RF was selected for the analysis.

5. Analysis of various algorithms should be included in the Results section for the comparison with Random Forest.

6. The discussion should be shorter. The findings of the research need to be clearly understood.

7. How is the data analyzed? It should be included in the conclusion section.

8. The research outcomes must be clearly described in the conclusion section.

Author Response

See in attachment the responses for R2 and other reviewers.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

 This manuscript uses full-waveform LiDAR (FWF) data to illustrate recovery rates from secondary succession, and the article is well organized and informative. My question is the authors propose to use the FWF metric to illustrate recovery rates in different areas, what is the source of this metric? Is it supported by literature? Is it reliable?Please add a description of the FWF indicator.

 

Line89-100:It is described here that precipitation differences are important factors affecting the process of vegetation regeneration and the authors use laser technology to identify factors such as canopy height rather than precipitation, what is the relationship between them? Or please add the importance of the vegetation canopy in secondary succession.

 

Section Introduction:Missing from this section is a description of how Full Waveform Lidar (FWF) works.

 

Section 3.4:What is the reason for the variability in performance when using FWF data to classify secondary successional stages? Is it that the FWF metrics are less stable for classification?

 

Fig11:How is the importance of these eight indicators concluded?

 

Section results:Here the calculated FWF metrics are subjected to a series of analyses that in fact lack the ability to verify the consistency of the metrics with the real situation or to be able to prove the truth of the metrics.

Author Response

See in attachment the responses for R3 and other reviewers.

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Thanks, my concerns have beend addressed.

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