Assessment of Carbon Sink and Carbon Flux in Forest Ecosystems: Instrumentation and the Influence of Seasonal Changes

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study presents valuable insights into evaluating forest ecosystem carbon sinks and carbon flux measurements utilizing remote sensing technology, particularly considering the effects of instrumental and seasonal variability. However, the manuscript contains several significant issues that need to be addressed: Abstract Clarity: The abstract lacks clear logic and coherence. It is recommended that the author rewrite this section. For instance, the terminology should be consistent; the first sentence refers to “estimation and drawing”, which should be unified with the rest of the abstract by using “measurement” instead; Introduction Organization: The introduction is poorly organized and requires logical re-division of paragraphs. It currently provides a weak rationale for the study, and the writing in this section needs substantial improvement. Section Clarity: The purpose and connection of the second part of the manuscript with parts 3, 4, and 5 are unclear. The author needs to elucidate these relationships. Additionally, the summary of monitoring methods in the second part is disorganized. It is recommended that the author significantly improve the structure and clarity of this section. Overall Professionalism: The writing throughout the manuscript lacks professionalism in several areas. It is advised to enhance the writing quality. Seeking assistance from a scholar with advanced English proficiency is recommended to improve the manuscript.

Furthermore, several minor issues persist: The text contains numerous Chinese symbols, particularly in the final paragraph of the introduction. The usage of sensor terminology is inconsistent; sometimes full names are used first followed by abbreviations in parentheses, and vice versa in other instances. The email addresses provided for the authors are all QQ email addresses, which appears unprofessional. The first sentence of the introduction should focus on the significance or impact of climate change.

In summary, substantial improvements are needed in the manuscript's writing quality before it can be considered for acceptance.

Comments on the Quality of English Language

The writing throughout the manuscript lacks professionalism in several areas. It is advised to enhance the writing quality. Seeking assistance from a scholar with advanced English proficiency is recommended to improve the manuscript.

Author Response

Please see the attachment.

Author Response File: Author Response.doc

Reviewer 2 Report

Comments and Suggestions for Authors

1

Comments

1.Lines 71-74: Citation number 14 (Webster et al.) it is not applied in here. These author`s haven’t use TLS to assess structural metrics, they did something else. Replace this author with another more representative study based on what you are describing (for ground based lidar). I would recommend adding the following reference.

2.In line76: Make a new sentence and add the advantages that lidar fusion can offer to solve the problem of monomodal (single) lidar data (you can also use the previous reference to support this statement). In this study scholars used high end products (TLS and UAV lidar) in managed forests of central Europe to assess how fusion can increase the structure of trees. They found that fusion of LIDAR technology based on TLS and UAV-LS can significantly reshape the modelled tree structures in all cases (broadleaves and conifers), which led to improved estimates of all tree metrics (crown and stem), opening the way for several precision forestry applications.

3.When you start talking about “satellite mounted lidar” make a new paragraph. In general, try to create more paragraphs to divide your thematic sections. Avoid long paragraphs like for instance lines 53-83.

4.In table 1. I would suggest to divide the methods in destructive and non-destructive or even in remote sensing and close-range sensing (something like that). Also, in line 5 column 2 when you are referring to the photogrammetric methods why do you mention lidar (it is not photogrammetric). In the same line, last column, you mentioned that “the equipment is expensive”, maybe you should add this limitation for the lidar since photo cameras are much cheaper. Did you make this table or you took it from somewhere else? If it’s the second case, add reference in the caption. In general, check again and elaborate more in your table 1 for such minor mistakes. The way it is now in some parts is kind of confusing. For example, in the last line, column 1, you mentioned “remote sensing of forestry”. That is confusing, what do you mean exactly? Please rephrase-explain.

5.Lines 180-186: That is a controversial statement in my opinion. It is not quite clear what you are trying to say. Initially, you say that “CRP is a solution of canopy parameters” and then you continue by saying “which consists of close-range sensing and TLS to measure…” That statement does not make any sense. Please, try to rephrase it and by the way I have a good solution to justify what you are try- ing to say because you will also need a reference for that statement. I believe what you wanted to say is that “the combination of CPR for under canopy and TLS can be successfully used to estimate structural parameters of individual trees”. This is ok to say but there is a “catch”, in a study from Panagiotidis et al., 2016 (I will add the reference below so you can use it) authors study the accuracy of structure-from-motion using CRP in comparison with TLS for the analysis of DBH -Height influence on error behaviour. What they found is that the lowest error (in point matching between the two different point clouds) was found near the ground. That also means that the error was negligible for all DBH estimations, but not for the height, where the the error was higher at higher stem portions (greater error ~ 11 cm). That was mainly because of the inability of camera during the alignment process to convert from 2d to 3d because of fewer matching points at that level. Of course this depends on several parameters, like latest technological advancements in hardware-software and the forest structure. You should mention that because it will increase the value of your statement. 

6.Lines 262-266: You need to add individual references for each “task” (here you have my suggestions highlighted with yellow color) The UAV can carry a hyperspectral sensor to identify tree species (Ballanti, L.; Blesius, L.; Hines, E.; Kruse, B. Tree Species Classification Using Hyperspectral Imagery: A Comparison of Two Classifiers. Remote Sens. 2016, 8, 445. https://doi.org/10.3390/rs8060445), a visible digital camera to identify tree height and biomass measurements (José M Peña, Ana I de Castro, Jorge Torres-Sánchez, Dionisio Andújar, Carolina San Martín, José Dorado, César Fernández-Quintanilla, Francisca López-Granados. Estimating tree height and biomass of a poplar plantation with image-based UAV technology[J]. AIMS Agriculture and Food, 2018, 3(3): 313-326. doi: 10.3934/agrfood.2018.3.313), a multispectral sensor to identify canopy structure and determine attributes (Abdollahnejad, A.; Panagiotidis, D. Tree Species Classification and Health Status Assessment for a Mixed Broadleaf-Conifer Forest with UAS Multispectral Imaging. Remote Sens. 2020, 12, 3722. https://doi.org/10.3390/rs12223722), a thermal infrared camera to identify canopy structure and determine attributes (Elnaz Neinavaz, Martin Schlerf, Roshanak Darvishzadeh, Max Gerhards, Andrew K. Skidmore, Thermal infrared remote sensing of vegetation: Current status and perspectives, International Journal of Applied Earth Observation and Geoinformation,Volume 102,2021,102415, ISSN 1569-8432, https://doi.org/10.1016/j.jag.2021.102415.), and LiDAR (to identify canopy structure, characteristics, and biomass delineation) [46].

In overall, it is a well-written, synopsis of the state-of-art for all available methods existing covering all the scales. I would just strongly recommend adding the missing references and enhance a bit the parts which I mentioned, to increase even more the quality of this review paper.

I'd be happy to review the updated manuscript after it has been edited.

Author Response

Please see the attachment.

Author Response File: Author Response.doc

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

In general, the author has made some revisions to the paper, which have enhanced the quality of the manuscript. However, it appears that the author did not give due consideration to my comments, and the responses provided were somewhat perfunctory. If the author is uncertain about addressing specific feedback, I recommend consulting a peer for assistance rather than responding superficially to the review comments. I hope that the author will approach the revision process with greater diligence and take the necessary steps to improve the manuscript significantly before it can be considered for acceptance. For instance, I have made some revisions to the abstract and keywords below as an example.

 

Accurate measurement and estimation of forest carbon sinks and fluxes are essential for developing effective national and global climate strategies aimed at reducing atmospheric carbon concentrations and mitigating climate change. Various errors arise during forest monitoring, especially measurement instability due to seasonal variations, which require to be adequately addressed in forest ecosystem research and applications. Seasonal fluctuations in temperature, precipitation, aerosols, and solar radiation can significantly impact the physical observations of mapping equipment or platforms, thereby reducing the data's accuracy. Here, we review the technologies and equipment used for monitoring forest carbon sinks and carbon fluxes across different remote sensing platforms, including ground-based, airborne, and spaceborne remote sensing. We further investigate the uncertainties introduced by seasonal variations to the observing equipment, compare the strengths and weaknesses of various monitoring technologies, and propose the corresponding solutions and recommendations. We aim to gain a comprehensive understanding of the impact of seasonal variations on the accuracy of forest map data, thereby improving the accuracy of forest carbon sinks and fluxes.

 

 

Keywords: Seasonal variations, Forest, Carbon sink, Carbon flux, Remote sensing platforms

Comments on the Quality of English Language

I recommended that the author carefully consider the intended message in various sections of this article and seek assistance from a scholar with advanced language skills to enhance the quality of the manuscript.

Author Response

Please see the attachment.

Author Response File: Author Response.doc