Study on the Evolutionary Characteristics of Post-Fire Forest Recovery Using Unmanned Aerial Vehicle Imagery and Deep Learning: A Case Study of Jinyun Mountain in Chongqing, China
Round 1
Reviewer 1 Report (Previous Reviewer 1)
Comments and Suggestions for AuthorsThe authors have poorly modified the MS without respond to the reviewers questions and comments
Author Response
Dear Dr. Reviewer,
I'm sorry that our first response left you very dissatisfied. Please forgive us for the unpleasant experience we had with our first submission to Sustainability. If our unfamiliarity with the response process of the reviewer's report has offended you, we sincerely apologize. In the first response, we made some changes to the details and did not mention some parts of the reviewer's report that we did not understand. The fact proves that this is wrong. This time, we will provide a detailed response to each suggestion and highlight the changes we have made, and sincerely explain to you which parts we did not understand in the report and why we did not make any modifications.
Comments 1: The MS shows many inconsistencies and includes huge quantity of informatic details which does not agree with an ecological publication. Moreover, the MS structure is disorganized and neglected.
Response 1: We are very sorry that our English writing may have caused readers a bad reading experience. We made a lot of detailed changes to this point in the last article, including whether the placement of some statements in paragraphs is reasonable or whether the logic of some statements is coherent. This will also be reflected in some specific paragraph modifications later on. But from the results, it doesn't seem satisfactory. This time we will ask a professional English author to carefully examine the English writing of the entire article and help us correct some structural issues.
Comments 2: The title is not proper: the terminology (UAV and deep learning) is not known by all readers and the acronyms must not be used. Moreover, the country name is needed instead of the region name.
Response 2: Thank you very much for your suggestion. Regarding this issue, we have changed the original title "Study on the Evolution Characteristics of Post Fire Forest Re cover Using UAV Imagery and Deep Learning: A Case Study of Jinyun Mountain, Chongqing" to "Study on the Evolution Characteristics of Post Fire Forest Re cover Using Unmanned Aerial Vehicle Imagery and Deep Learning: A Case Study of Jinyun Mountain in Chongqing, China". We replaced the abbreviation "UAV" with its full expression "Unmanned Aerial Vehicle" and indicated the country where the research area is located. However, regarding 'Deep Learning', we apologize for finding it difficult to provide a detailed explanation in the title or abstract. If we were to use a more straightforward and understandable term for 'Artificial Intelligence', the title would appear too broad. Therefore, we have retained this section. And in the "Introduction", we explained the "deep learning" method and its temporal background. "Deep learning, which emerged as computational power advanced rapidly in the 21st century, uses multi-layer neural networks to extract deep and abstract features from data layer by layer." Lines 94-96
Comments 3: Abstract: the “UAV” and “deep learning” terms must be defined.
Response 3: We highly appreciate your suggestion. In the abstract, we describe "UAV" as "unmanned aerial vehicle (UAV)", which not only avoids confusion for readers but also explains the meaning of "UAV" that may appear in the main text. “deep learning” The meaning and background of the "deep learning" method will be explained in the "Introduction" section.
Comments 4: Lines 14-24: these sentences are not understandable because include many technical terms without explanation.
Response 4: We completely agree with your point. The abstract section indeed introduces many models and blocks used in deep learning, and using abbreviations here may make it difficult for readers who are encountering these concepts for the first time. We sincerely apologize for this. To address this, we will replace all abbreviations with their full names, including "Contextual Transformer (CoT)," "Efficient Multi-Scale Attention (EMA)," and "Efficiently Adaptive (EA)." However, we regret that we are still unable to provide a detailed explanation of the method in the abstract, as it would make the section too lengthy. We can only provide detailed explanations in the "Materials and Methods" section.
Comments 5: Line 31: “T Forest” needs explanation.
Response 5: The 'T' here is redundant and was left over during the conversion of Word document format. We have removed it in the last revision, thank you very much for your insight.
Comments 6: Lines 57-94: this indexes description is too much detailed. Please, summarize.
Response 6: Thank you very much for your valuable suggestions. We sincerely apologize for the imbalance in the introduction of previous related technologies in this section, which indeed made the content uneven, with some parts more detailed than others. In the last revision, we made adjustments to the structure of this section. The paragraph in Lines 53-57 describes the historical context of the related research; the paragraph in Lines 58-73 summarizes the technological research related to traditional vegetation indices, which corresponds to the previous Lines 57-94 before the revision; and finally, the paragraph in Lines 74-94 corresponds to the content in the previous Lines 94-104.
Comments 7: Line 95: contrarily, the “machine learning” and the “deep learning” terms definition is absent: algorithms?
Response 7: Your suggestion has been extremely helpful. In the original manuscript, our description of this section was overly concise, and it was your recommendation that made us realize that such brevity might present difficulties for readers. In the last revision, we devoted more space to describe some of the methods in a clearer way. To prevent confusion among readers who are new to the field of artificial intelligence, we replaced the term "machine learning and deep learning" with "neural networks" to avoid conceptual ambiguity. Following this, when describing methods involving "deep learning," we provided a detailed explanation: "Deep learning, which emerged as computational power advanced rapidly in the 21st century, uses multi-layer neural networks to extract deep and abstract features from data layer by layer." We sincerely appreciate your valuable feedback, which has helped us improve the clarity and accessibility of our work.
Comments 8: Lines 106-111: the MS objective is unclear. Change by: “To test the accurately of the UAV use and the deep learning segmentation method for identifying the burned areas evolution…."Moreover, the line 109 sentence is not proper: the Mask2Former has not been mentioned before and the “various technique” term is ambiguous. Please, clarify.
Response 8: After carefully reviewing the paragraph, we found that the issue you pointed out indeed exists. In our last revision, we modified the text to: "Our approach integrates the Mask2Former model with several other techniques to distinguish between burned areas, unburned or recovering zones, and roads within forests affected by fire, aiding in the analysis of post-fire forest evolution characteristics." This change was made to better highlight the research objective of the manuscript. However, we now realize that combining the research method and research objective in a single sentence makes it difficult to clearly convey the intended message, especially given the technical terminology involved, which might still create challenges for readers.
In this revision, we have optimized the structure of the sentence by separating the research objective and research method. The revised version reads: "In our deep learning approach, we use semantic segmentation to distinguish different regions in post-fire forests, thus helping to analyze the evolutionary characteristics of the forest after a fire. The semantic segmentation model we use is Mask2Former, which has become a classic in recent years, and we have improved on the Mask2Former model to make it more adaptable to the complex environment in post-fire forests."
We sincerely thank you for your suggestion, which has given us the opportunity to critically examine and improve the structure of our manuscript.
Comments 9: Line 113: the “Overview” word is not necessary: eliminate.
Response 9: Thank you for your suggestion. In our last revision, we removed the "Overview" section. We sincerely appreciate your valuable input and apologize for any inconvenience.
Comments 10: Lines 114-117: again, the country name and the study area size must be added. Moreover, the geographic coordinates must be shown in conventional format.
Response 10: We have added the country name to the description of the study area and modified the geographic coordinates to list latitude before longitude. Thank you for your suggestion. It has made our geographic formatting more standardized.
Comments 11: Figure 1: the picture “(b)” is not necessary: eliminate. Moreover, the map references must be added.
Response 11: We fully agree with your point. In the last revision, we removed the map of the study area and replaced it with an updated representation. The new map not only provides readers with the geographic location of the study area but also helps them intuitively understand its size. We will indicate the source in the map's footnote: "Source from: https://www.google.com.hk/maps/. Source from: http://www.bigemap.com/." We hope this will make the map citation more appropriate. Thank you very much for your valuable suggestion, and we sincerely appreciate your input.
Comments 12: Table 1: please don’t repeat “altitude about” in all rows (4th column)
Response 12: Thank you for your advice. You are absolutely right that this part seemed somewhat repetitive. We have removed all instances of "altitude about" except for the one at the top of the table. We sincerely appreciate your feedback.
Comments 13: Lines 148-155: these paragraphs are out of context: please move them at the MS end.
Response 13: We sincerely apologize for the oversight that led to non-standard writing in this section. We originally thought that this part needed to be stated in the material acquisition section according to the template requirements. However, it turns out that this was merely a prompt in the template and does not need to be retained. Appreciate you for your keen insight, and we will remove this part accordingly.
Comments 14: Lines 157-171: again, this information is out of context. It corresponds to the introduction section.
Comments 15: Figure 2: it has not sense: is it a result? when the imagens were taken? The “different times” term is ambiguous: eliminate.
Response 14 & 15: We sincerely apologize for not making changes to this part, but this is not because your suggestion was unhelpful. Please forgive us if we seem a bit confused regarding this issue, as this section is not merely an introduction to traditional techniques, but also an analysis of their strengths and weaknesses, and the rationale for choosing deep learning methods based on the limitations of traditional techniques. Including Figure 2 is not just an illustration or an irrelevant visual; it actually presents different characteristics of the same forest area at different times to highlight the shortcomings of traditional methods and how deep learning addresses these challenges.
You were correct in pointing out that the phrase "different times" is ambiguous, and we will remove it. We greatly appreciate your suggestion, and if there are still aspects of this section that are unclear, we welcome your criticisms and further recommendations. Thank you for your valuable input.
Comments 16: Lines 177-190: again, this paragraph is meaningless: it seems to be a result.
Response 16: This part is indeed the result obtained using traditional vegetation indices and conventional image processing methods, aiming to illustrate the limitations of traditional techniques through data. However, this is not the primary research method used in this manuscript. We sincerely thank you for your suggestion.
In fact, during the last review, we sensed that there might be some misunderstanding between us regarding the main content of the manuscript, but we were uncertain whether we should point out this issue in our response to the reviewer, or whether expressing our differing view might be disrespectful to you.
Looking back, we realize that our approach was mistaken; even if there are differing views, we should have communicated with you more actively and in a timely manner. We greatly appreciate your patience and understanding, and we deeply regret any lack of communication on our part. Thank you for your insightful comments.
Comments 17: Lines 191-200: again, this paragraph is out of context. Moreover, it repeats the introduction information.
Response 17: After summarizing the limitations of traditional techniques, this part discusses the research methods we have chosen and the experimental preparations needed when adopting these methods. Thank you very much for your suggestion. Perhaps this section appears somewhat abrupt, and we will ask the English author to help improve the transition here to make the logical flow more coherent. For instance, we plan to add the following to the beginning of the paragraph: "Compared to the limitations exhibited by vegetation indices, deep learning approaches are much more flexible." or "As long as the data are trained at different times and in various environments, the network model can have the ability to recognize and differentiate between different areas under complex conditions, thus allowing for better observation of the evolutionary characteristics of the areas."
We sincerely appreciate your insight and will work to ensure that the text flows more smoothly, making the content easier to follow.
Comments 18: Lines 209-350: the detailed model description (and the figures) must be moved to the supplementary material.
Response 18: We sincerely apologize for any inconvenience. We considered that since this part represents the main research method we adopted, including it only in the supplementary materials rather than in the main text might make the paper appear lacking in substance, potentially leading readers to feel confused or doubtful about our research methods and logic. Please trust that we had no intention of questioning or offending you—this may be due to the fact that our research methods are uncommon in the field of Forestry.
We deeply appreciate your valuable suggestion and are more than willing to clarify any questions regarding this part. Thank you again for your understanding and patience.
Comments 19: Lines 353-374: again, these paragraphs are out of context: they correspond to the methods section (not results). moreover, the “comparison models” has not been mentioned in the MS objective.
Response 19: We completely agree with your point, and it indeed represents the experience many readers may have when going through this section. In fact, the mathematical formulas and "comparison models" mentioned here are part of the experimental content. The "comparison models" serve as a declaration for the "Comparative experiment" in Section 3.3.1 later in the text. Initially, we placed this part in the "Result" section because we believed that the experimental part was closely related to the results.
However, it now seems that renaming the "Result" section to "Experiment and Result" might be more appropriate. We are unsure whether such a change would align with the template guidelines, and we would greatly appreciate your further guidance on this matter. Thank you very much for your valuable insight and understanding.
Comments 20: Lines 376-386: again, this paragraph is a mix between methods and results. Moreover, the “Cityscapes” word has not been mentioned before, and again, the comparative experiment has neither been mentioned in the MS objective nor in the methods.
Comments 21: Table 2: again, what the “Cityscapes” baseline refers to? The columns´ title references are absent
Response 20&21: Thank you very much for your constructive criticism; we believe your viewpoint is very fair. In our last revision, we added a brief explanation stating "the Cityscapes dataset, an open-source image segmentation dataset." However, we realize that this may not be sufficient, and we have decided to place this part in the "Experiment" subsection of the "Experiment and Result" section, separating it from the result portion and providing a more detailed explanation. In fact, the "Cityscapes dataset" is also intended for use in the "Comparative experiment." We sincerely appreciate your valuable feedback, and we will continue to work on making our manuscript clearer and more informative for readers.
Comments 22: Lines 391-394: is this footnote explanation a result or a method?
Response 22: Thank you very much for your reminder. Upon review, we realized that placing this part in the footnote was indeed inappropriate. Strictly speaking, this content belongs to the experimental preparation phase, and including it in the footnote could easily blur the line between results and methods.
In the last revision, we removed it from the footnote and instead added a statement in the main text: "Due to the limited size of our dataset, we used the lightweight Swin-Tiny version of Swin-Transformer in the Mask2former approach. Similarly, the ResNet network used for comparison was ResNet50, which has a similar computational complexity. For Segformer and DeepLabv3+, we used MixVIT and ResNet101 as the backbone networks, which showed the best experimental results; using ResNet50 would have resulted in lower performance."
In this revision, we will place this content in the "Experiment" subsection of the "Experiment and Result" section. We truly appreciate your valuable input, which has greatly helped us improve the clarity and logical flow of our manuscript.
Comments 23: Lines 397-402: again, this paragraph corresponds to the methods section.
Response 23: We completely agree with your point, and we will separate the experimental process from the experimental results, placing the relevant parts in the "Experiment" section. Thank you for your suggestion; it will certainly improve the quality of the manuscript. We sincerely appreciate your help.
Comments 24: Table 3: again, the “Jinyunshan” word has not been mentioned before and the columns´ titles need the reference.
Response 24: We sincerely apologize for this oversight. In our last revision, we had already corrected "Jinyunshan" to "Jinyun Mountain", and the inconsistency was indeed due to our error. We are truly sorry for the confusion caused to readers, and we are very grateful to you for identifying this issue. Your feedback will certainly help make the manuscript better. Thank you very much for your valuable assistance.
Comments 25: Lines 416-417: this sentence and the figure 8 are not possible to understand because the explanation is absent. The “some segmentation results” term is ambiguous. It is an essential point which need a clear description highlighting the differences among models.
Response 25: We agree with your point that the phrasing of this sentence might confuse readers. Our revised version is: "As shown in Figure 8, it is the segmentation effect of 5 segmentation models in 5 different regions in the Comparative experiment." This means that Figure 8 is a partial representation of the aforementioned experiment, while "5 segmentation models in Comparative experiment" refers to the models "DeeplabV3+", "Segformer", "Resnet50-Mask2former", "Swin-Mask2former", and "EAswin-Mask2former" mentioned in the experiment.
Thank you very much for your suggestion. It will help readers better understand the content of the article. We truly appreciate your valuable input.
Comments 26: Lines 421-424: again, the “ablation experiments” have neither been mentioned in the objective nor in the methods.
Response 26: Your perspective has been incredibly helpful to us. The role of "ablation experiments" here is referenced in Section 3.3.2: "In order to further validate the effectiveness of the EA Block, ablation experiments need to be performed on the EA Block, CoT Block, and EMA Block respectively." However, we realize that this may be a challenging description for readers who are new to deep learning. Therefore, we have decided to provide a more detailed explanation of "ablation experiments" in the "Experiment" section and emphasize its necessity in the experimental results.
Comments 27: Figure 9: the graph is not proper because the data have not continuous values (different models). Please, change the line graph by column graph.
Response 27: We sincerely apologize if we may not have fully understood your concern, but please do not be upset—we will make changes to the image accordingly. Perhaps what you meant is that the data between different models is discrete rather than continuous, making it inappropriate to use a line graph? Our original intention was to use a line graph to better demonstrate the changes in experimental results when using different models. However, we realize that this may have had the opposite effect, and we will change it to a column graph instead.
Thank you very much for your valuable suggestion. If we have misunderstood your question in any way, please feel free to provide further guidance. We truly appreciate your patience and help in improving our work.
Comments 28: Lines 452-454: this sentence repeats the lines 422-424: eliminate.
Response 28: Thank you very much for your careful reading, and we sincerely apologize for our oversight. Similar to the issue with "T Forest," this was caused by some formatting errors when transferring the manuscript into the template document. We have removed it in the last revision. We once again offer our heartfelt apologies for the less-than-ideal reading experience this has caused. We are very grateful for your understanding and patience.
Comments 29: Figure 10: it corresponds to the results section. Moreover, this figure has not sense without description and references.
Comments 30: Figure 11: again, it shows results
Response 29&30: Thank you very much for raising such a constructive question. Figure 11 represents an illustration of our experimental results, showing the segmentation capability of the trained EAswin-Mask2former model in observing the evolution characteristics of a specific area. Figure 10, on the other hand, shows satellite remote sensing imagery, not the images obtained through an Unmanned Aerial Vehicle (UAV). Its primary role is for comparison, rather than presenting results. The images obtained by UAV tend to be high-resolution and more localized, while satellite remote sensing images provide broader coverage. We arranged the content in this way to highlight the unique features of the UAV images.
Perhaps our description in this part of the manuscript was not sufficiently clear, and we will ask the English author to help optimize the language to make it easier for readers to understand. As a last resort, we may consider removing Figure 10 or replacing it with another satellite image to avoid confusion.
We sincerely appreciate your insights and patience in helping us improve the clarity of our manuscript.
Comments 31: Lines 495-506: again, this paragraph and the figure 12 correspond to the results section.
Response 31: Thank you very much for your suggestion. Indeed, we struggled with this part as well. Lines 495-506 and Figure 12 should indeed be part of the results section, but our discussion needs to be based on those results, making it challenging to balance. We will move that part to the results section, and the discussion will serve as an analysis based on the results, which seems to be a more reasonable approach.
Comments 32: figure 12: line 508: “this location” term is ambiguous. Please, mention it.
Response 32: We sincerely appreciate your suggestion. Our description here was indeed somewhat ambiguous, affecting the readability for our audience. In the last revision, we clarified "this location" to "Region A," and we have stated this clearly in both the preceding text and the figure captions. We hope this makes it easier for readers to understand the subject we are describing. Thank you once again for your valuable input.
Comments 33: Lines 511-521: these comments need the literature reference.
Response 33: You are absolutely right. This part of the description should indeed include a literature reference to make it more reasonable, authoritative, and compliant with writing standards. Thank you for your keen insight—such details will make the manuscript more convincing. We sincerely appreciate your valuable feedback.
Comments 34: Lines 523-525: this paragraph is not proper (nor necessary). The conclusions must not repeat the MS abstract.
Response 34: We sincerely apologize for the excessive overlap between the content of the abstract and the conclusion, which is due to our limited English writing skills. We will ask an English author to help us better balance these two sections. Perhaps we will revise the conclusion to make it more summative, rather than simply repeating the content of the abstract. Thank you very much for your suggestion—it is extremely helpful to us.
Comments 35: Lines 526-533: these important comments must be mentioned in the results and justified in the discussion section, instead of the detailed informatic procedures (which comparison results are not commented in the conclusions).
Response 35: Yes, we will move the main content of this paragraph to the "Results and Discussion" section and place more summarizing language in the conclusion. We sincerely thank you for your help in optimizing the structure of our paper, making it more logical. Your guidance has been incredibly valuable to us.
We sincerely apologize once again for any misunderstanding. We never intended to disregard you, nor did we believe that your suggestions were without value. In fact, we made several revisions after receiving the initial Reviewer Report, but unfortunately, we did not provide you with timely feedback. This oversight was due to our inexperience with the rules of responding to reviewers during our first submission, and we deeply regret any unintended offense.
Additionally, we found ourselves uncertain about some of your comments when we first received them, but we hesitated to reply because we were afraid it might seem disrespectful. However, we now realize that we should have communicated with you promptly to address these questions, which would have helped clarify our mutual concerns and avoid unnecessary misunderstandings.
Your questions and suggestions are immensely valuable, and we are truly grateful for your insight. We apologize for any lack of communication on our part, and we will strive to improve in this regard. Thank you once again for your patience and invaluable support.
Faithfully,
Peiji Yang
yangpeiji1@zqsfdx144.wecom.work
Author Response File: 
Author Response.pdf
Reviewer 2 Report (Previous Reviewer 2)
Comments and Suggestions for Authors1) Figures and tables must be revised according to the template. For example, the description of Figure 4 is as follows: 'Figure 4. Swin Transformer Network Architecture (left) and Swin Transformer Block Structure (right). Please follow the template’s instructions to describe figures correctly.
2) Figures and tables must also be aligned to the right margin as specified in the template.
3) Further explanation is needed on the ecological insights.
4) Careful proofreading will enhance readability.
Comments on the Quality of English LanguageCareful proofreading will enhance readability.
Author Response
Dear Dr. Reviewer,
Thank you very much for your valuable suggestions. Your feedback will greatly help us improve our manuscript, making it more refined and compliant with standards. We also deeply appreciate your positive remarks. We will make the following revisions in response to the issues you have raised:
Comments 1: Figures and tables must be revised according to the template. For example, the description of Figure 4 is as follows: 'Figure 4. Swin Transformer Network Architecture (left) and Swin Transformer Block Structure (right). Please follow the template’s instructions to describe figures correctly.
Response 1: Thank you for your suggestion. Indeed, the template does not include our original approach for presenting images. We have decided to replace the "left" and "right" descriptions with (a) and (b), and provide corresponding explanations for (a) and (b) in the footnote. We sincerely appreciate your help, as this will make our manuscript more standardized.
Comments 2: Figures and tables must also be aligned to the right margin as specified in the template.
Response 2: We sincerely apologize for the misunderstanding regarding the layout of figures and tables according to the template. We will make further adjustments in accordance with the image layout requirements in the "sustainability-template.dot." Currently, our approach to figure alignment is to align them to the left if the size does not exceed the main text, and to the right if it does. We will revise the current layout based on your suggestions.
We are very grateful for your constructive advice and would appreciate your further guidance on our manuscript. Thank you once again for your patience and support.
Comments 3: Further explanation is needed on the ecological insights.
Response 3: Thank you very much for raising this point. We indeed lack references to ecology-related literature, which makes this part of the description less convincing. We will add relevant citations in the analysis of secondary succession in burned forests to make this section more authoritative and professional. We sincerely appreciate your valuable suggestion, as it will greatly help in improving the credibility of our manuscript.
Comments 4: Careful proofreading will enhance readability.
Response 4: We sincerely apologize for the suboptimal reading experience caused by our limited English writing skills and some oversights. We will thoroughly proofread the manuscript to correct any logical errors, and we will seek assistance from an English author to improve the quality of the language. We hope this will enhance the overall reading experience for our audience. Thank you very much for your patience and understanding.
Once again, we extend our sincere gratitude to you. Your efforts have been tremendously helpful to us, and we are truly thankful.
Faithfully,
Peiji Yang
yangpeiji1@zqsfdx144.wecom.work
Author Response File: Author Response.pdf
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe MS shows many inconsistencies and includes huge quantity of informatic details which does not agree with an ecological publication. Moreover, the MS structure is disorganized and neglected
The title is not proper: the terminology (UAV and deep learning) is not known by all readers and the acronyms must not be used. Moreover, the country name is needed instead of the region name.
Abstract: the “UAV” and “deep learning” terms must be defined.
Lines 14-24: these sentences are not understandable because include many technical terms without explanation
Line 31: “T Forest” needs explanation
Lines 57-94: this indexes description is too much detailed. Please, summarize.
Line 95: contrarily, the “machine learning” and the “deep learning” terms definition is absent: algorithms?
Lines 106-111: the MS objective is unclear. Change by: “To test the accurately of the UAV use and the deep learning segmentation method for identifying the burned areas evolution…."Moreover, the line 109 sentence is not proper: the Mask2Former has not been mentioned before and the “various technique” term is ambiguous. Please, clarify
Methods
Line 113: the “Overview” word is not necessary: eliminate
Lines 114-117: again, the country name and the study area size must be added. Moreover, the geographic coordinates must be shown in conventional format
Figure 1: the picture “(b)” is not necessary: eliminate. Moreover, the map references must be added
Table 1: please don’t repeat “altitude about” in all rows (4th column)
Lines 148-155: these paragraphs are out of context: please move them at the MS end
Lines 157-171: again, this information is out of context. It corresponds to the introduction section
Figure 2: it has not sense: is it a result? when the imagens were taken? The “different times” term is ambiguous: eliminate
Lines 177-190: again, this paragraph is meaningless: it seems to be a result
Lines 191-200: again, this paragraph is out of context. Moreover, it repeats the introduction information
Lines 209-350: the detailed model description (and the figures) must be moved to the supplementary material
Results
This section is confusing and disorganized because shows too many inconsistencies regarding to the MS objectives and includes methodological aspects which are not mentioned before
Lines 353-374: again, these paragraphs are out of context: they correspond to the methods section (not results). moreover, the “comparison models” has not been mentioned in the MS objective
Lines 376-386: again, this paragraph is a mix between methods and results. Moreover, the “Cityscapes” word has not been mentioned before, and again, the comparative experiment has neither been mentioned in the MS objective nor in the methods.
Table 2: again, what the “Cityscapes” baseline refers to? The columns´ title references are absent
Lines 391-394: is this footnote explanation a result or a method?
Lines 397-402: again, this paragraph corresponds to the methods section
Table 3: again, the “Jinyunshan” word has not been mentioned before and the columns´ titles need the reference
Lines 416-417: this sentence and the figure 8 are not possible to understand because the explanation is absent. The “some segmentation results” term is ambiguous. It is an essential point which need a clear description highlighting the differences among models
Lines 421-424: again, the “ablation experiments” have neither been mentioned in the objective nor in the methods
Figure 9: the graph is not proper because the data have not continuous values (different models). Please, change the line graph by column graph
Lines 452-454: this sentence repeats the lines 422-424: eliminate
Discussion
Figure 10: it corresponds to the results section. Moreover, this figure has not sense without description and references
Figure 11: again, it shows results
Lines 495-506: again, this paragraph and the figure 12 correspond to the results section
figure 12: line 508: “this location” term is ambiguous. Please, mention it
Lines 511-521: these comments need the literature reference
Conclusions
Lines 523-525: this paragraph is not proper (nor necessary). The conclusions must not repeat the MS abstract
Lines 526-533: these important comments must be mentioned in the results and justified in the discussion section, instead of the detailed informatic procedures (which comparison results are not commented in the conclusions).
Author Response
Comments 1: Figure 2: it has not sense: is it a result? when the imagens were taken? The “different times” term is ambiguous: eliminate.
Response 1: The significance of images obtained at different times in the same location is to illustrate the limitations of traditional vegetation indices. You are right, my expression here did not clearly explain the meaning of the images, and the annotations of the images were not accurate enough, which brought difficulties to readers' understanding. I will carefully consider and revise the expression of the entire paragraph here, and correct the annotations in the images to convey the correct meaning.
Comments 2:Table 3: again, the “Jinyunshan” word has not been mentioned before and the columns´ titles need the reference.
Response 2: The Jinyunshan mentioned here is actually Jinyun Mountain mentioned earlier. I'm sorry for my mistake. I colloquialized the name of the region without explaining it, which caused confusion before and after. I will unify these ambiguous parts before and after, and if they cannot be unified, I will provide detailed explanations.
Thank you very much for your careful reading and useful suggestions. I have spent a long time comparing, thinking, and revising each one, and explaining to you some of the low-level mistakes I have made.
Best wishes.
Reviewer 2 Report
Comments and Suggestions for AuthorsConclusion Revision:
The current conclusion lacks depth and clarity. It should be expanded to highlight the key findings of the study, their significance, and the broader implications. The conclusion should also suggest potential areas for future research, outline limitations, and reiterate the importance of the results within the field.
· Figure 1(a) & 1(b) Revisions:
Both parts of Figure 1 need to be revised in accordance with the template provided
· Table 1 – Right Margin:
The margin of Table 1 needs adjustment to maintain consistency and adhere to formatting rules.
· Figure 2 Corrections:
Figure 2 requires corrections. Cross-check it with the template for any discrepancies.
· Table 2 – Right Margin:
Similarly, the right margin of Table 2 so that it aligns properly within the document.
· Table 3 – Right Margin:
As with the previous tables, Table 3 must have its margin fixed.
· Figure 10 Description:
The description of Figure 10 must be updated to match the template suggestions. The description should be detailed enough to allow readers to understand the figure without needing to refer extensively to the main text.
Minor editing of English language required.
Author Response
Dear reviewer,
It is an honor to receive your advice. We will further revise and improve the manuscript based on your suggestions and templates to make the layout of the images more accurate. Thank you again for your valuable suggestion. We hope to have the opportunity to submit our manuscript to you again.
Best Wishes.
