Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Feature Fusion of Airborne LiDAR Data and Aerial Images

Round 1

Reviewer 1 Report

I have highlighted some of the portions (typical ones) that has to be redrafted from the language perspective/ for better clarity. You may go through the entire draft and redraft appropriately.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

We deeply appreciate the effort and time that you have spent in reviewing our manuscript “Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images” (ID: sustainability-2091738). We have studied the comments carefully and have made revisions which we hope meet with your approval. The outline of the revisions is listed as follows:

• We have systematically revised the abstract to make it more prominent the significance and innovation of this paper.
• We have checked and corrected the language and terminologies of the whole paper.
• We have corrected the existing figures and tables and made reasonable adjustments to their layout. We have added tag information to the graph, and have modified some images to high resolution and colorful.
• We have added text explanation to the figures and tables that are difficult to understand, which will make it easier for readers to understand the content of the charts.
• We have systematically adjusted the discussion and conclusion sections, and have added a quantified biomass statistical result to the conclusion.
• We added a detailed introduction to the point cloud processing software (lidar360).

Comment #1

I have highlighted some of the portions (typical ones) that has to be redrafted from the language perspective/ for better clarity. You may go through the entire draft and redraft appropriately.

Response:

Thank you for helpful comment. We have made a detailed inspection and improvement on the problem part you marked. In addition, we have invited a college English teacher to help check the article for language problems. We hope our modification can be approved by you.

 

Comment #2

The question in section 3.6 of the annotated manuscript: Why single trees only in this case?

Response:

Thank you for your helpful comment. The ‘single tree scale’ is mainly reflected in our works of segmentation and biomass mapping. In the works of classification and biomass estimation, machine learning models are trained by using features of individual tree samples. Finally, these models were used to classify the species and estimate the biomass of each individual trees in the whole study area. That's why you might harder found the description of ‘single tree scale’ in other sections. We hope our explanation can be approved by you!

Author Response File: Author Response.docx

Reviewer 2 Report

In this study, author did a study on Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images.

1. authors should state the novelty of this work.

2. Statistical analysis should be done where ever possible like in table 9.

3. Some figures are difficult to read  like fig 8, 9, etc

4. Keywords should be minimum 5

Author Response

Dear Reviewer,

We deeply appreciate the effort and time that you have spent in reviewing our manuscript “Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images” (ID: sustainability-2091738). We have studied the comments carefully and have made revisions which we hope meet with your approval. The outline of the revisions is listed as follows:

• We have systematically revised the abstract to make it more prominent the significance and innovation of this paper.
• We have checked and corrected the language and terminologies of the whole paper.
• We have corrected the existing figures and tables and made reasonable adjustments to their layout. We have added tag information to the graph, and have modified some images to high resolution and colorful.
• We have added text explanation to the figures and tables that are difficult to understand, which will make it easier for readers to understand the content of the charts.
• We have systematically adjusted the discussion and conclusion sections, and have added a quantified biomass statistical result to the conclusion.
• We added a detailed introduction to the point cloud processing software (lidar360).

Comment #1

authors should state the novelty of this work.

Response:

Thank you for helpful comment. We have summarized the novelty of this work again. In addition, systematic correction has made to the abstract. Please refer to lines 13-29 on page 1. The major innovation of this paper is to identify the key features of biomass estimation among different tree species. Secondly, the difference of characteristic importance among different tree species is compared and discussed. Finally, the features of point cloud and image are integrated to achieve the accurate biomass mapping of single wood scale in the study area.

Comment #2

Statistical analysis should be done where ever possible like in table 9.

Response:

Thank you for the helpful comment. We have made statistics on the biomass estimation results in the study area by referring to table9. Please refer to table 20 on page 22.

 

Comment #3

Some figures are difficult to read like fig 8, 9, etc.

Response:

Thanks for your comment. We have changed this type of picture to high resolution. In addition, we have added more text explanations to these images. Please refer to figure 4 and 5 on page 13, figure 6 on page 14, figure 7 and 8 on page 15, and figure 9 on page 16. The introduction of figures please refer to lines 415-419 on page 12 and lines 465-468 on page 14.

 

Comment #4

Keywords should be minimum 5.

Response:

Thank you for this comment. We've added the keyword: ‘subtropical arboreal forest’. Please refer to lines 30-31 on page 1.

Reviewer 3 Report

In the paper entitled "Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images" by Yan et al., The idea of work and approach is good but the data representation and the inference are not clear. 

Tables are too crowded. Lot of information thrown in table without proper understanding to reader.

Figures need to be more clear with legible fonts

The graph are too messy the limits or ranges can be set as such the text of axis units and labels are clear to reader

Some places English language review is required. 

The paper need major revision 

Author Response

Dear Reviewer,

We deeply appreciate the effort and time that you have spent in reviewing our manuscript “Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images” (ID: sustainability-2091738). We have studied the comments carefully and have made revisions which we hope meet with your approval. The outline of the revisions is listed as follows:

• We have systematically revised the abstract to make it more prominent the significance and innovation of this paper.
• We have checked and corrected the language and terminologies of the whole paper.
• We have corrected the existing figures and tables and made reasonable adjustments to their layout. We have added tag information to the graph, and have modified some images to high resolution and colorful.
• We have added text explanation to the figures and tables that are difficult to understand, which will make it easier for readers to understand the content of the charts.
• We have systematically adjusted the discussion and conclusion sections, and have added a quantified biomass statistical result to the conclusion.
• We added a detailed introduction to the point cloud processing software (lidar360).

Comment #1

Tables are too crowded. Lot of information thrown in table without proper understanding to reader.

Response:

Thank you for helpful comment. We have split the crowded table 7 into three tables. They are used to represent the height correlation features, intensity correlation features, density correlation features and other variables of point cloud, respectively. Please refer to table 7-9 on page 7-9.

 

 

Comment #2

Figures need to be more clear with legible fonts.

Response:

Thank you for the helpful comment. We have replaced the unsharp pictures with high resolution images. However, there are too many variables in the correlation analysis map shown in Figure 4-6. The marked variable names have small fonts, which need to be enlarged to make them clear. If it is acceptable for you and editors to reduce some of variables to make the picture clearer, please contact me for modification. Please refer to figure 4-6 on page 13 and page 14.

 

Comment #3

The graph are too messy the limits or ranges can be set as such the text of axis units and labels are clear to reader.

Response:

Thanks for your comment. We have reformatted the graph and added the labels of axes for the missing label images. Please refer to figure 4-6 on page 13 and page 14, figure 10 on page 17-18, Table7-9 on page 7-9, and table 10 on page 9.

 

Comment #4

Some places English language review is required.

Response:

Thanks for your comment. We have re-checked and corrected the grammars and terminologies of the full text. And we hope our modification can get your approval.

 

Comment #5

The paper need major revision.

Response:

Thank you for this comment. We have made careful revisions according to your and other experts' opinions. A large number of issues such as layouts and grammars have been checked and revised. We hope our revised article can get your approval.

Author Response File: Author Response.docx

Reviewer 4 Report

The article “Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images” has been written well and covers a major topic for today. The in-depth research article may help to assess the biomass availability to harness energy and chemicals for the development of modern biorefinery. However, the MS requires certain minor revisions prior to consideration for publication as below.

·       The authors have mentioned that “R-Square coefficient of determination of 26 Cupressus Lusitanica (CL), Pinus Yunnanensis (PY) and Deciduous Broad-leaved Forest (DBF) were 27 0.7356, 0.8578, and 0.6823, respectively”. Is this only the novelty of the research?

·       In conclusion, the random forest biomass estimation model based on the fusion of integrated multi-source features in this paper has shown high estimation accuracy, which is positively significant for accurate forest biomass or carbon storage survey and mapping. This text should be simplified.

·       Table 2. allometric equations should be rechecked. Please change R2 with R².

·       Section 2.3 uAV or UAV? Please define correctly through the MS. Besides, there is no need to mention the data acquisition time.

·       Lidar-360 software: The author should provide some information about the software in detail.

·       Table 8, the author should recheck the variable notation and should not italicize them.

·       Result and discussion: In overall the results and discussion has been written well however, there are some phrases where the author needs to revise them properly.

·       For instance, Figure 4-7 needs to be explained further. The author should avoid the use of I, we or us in the manuscript.

·       The conclusion should be further revised with the inclusion of a novel statement with quantified results.

Author Response

亲爱的审稿人:

We deeply appreciate the effort and time that you have spent in reviewing our manuscript “Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images” (ID: sustainability-2091738). We have studied the comments carefully and have made revisions which we hope meet with your approval. The outline of the revisions is listed as follows:

• We have systematically revised the abstract to make it more prominent the significance and innovation of this paper.
• We have checked and corrected the language and terminologies of the whole paper.
• We have corrected the existing figures and tables and made reasonable adjustments to their layout. We have added tag information to the graph, and have modified some images to high resolution and colorful.
• We have added text explanation to the figures and tables that are difficult to understand, which will make it easier for readers to understand the content of the charts.
• We have systematically adjusted the discussion and conclusion sections, and have added a quantified biomass statistical result to the conclusion.
• We added a detailed introduction to the point cloud processing software (lidar360).

Comment #1

The authors have mentioned that “R-Square coefficient of determination of 26 Cupressus Lusitanica (CL), Pinus Yunnanensis (PY) and Deciduous Broad-leaved Forest (DBF) were 27 0.7356, 0.8578, and 0.6823, respectively”. Is this only the novelty of the research?

Response:

Thank you for helpful comment. This statement has showed the optimal accuracy of the sample biomass estimation experiment in this paper, but could not represent the all novelties of this paper. We have summarized the novelty of this work again. And the systematic correction has made for the abstract. Please refer to lines 13-29 on page 1. The major innovation of this paper is to identify the key features of biomass estimation among different tree species. Secondly, the difference of characteristic importance among different tree species is compared and discussed. Finally, the features of point cloud and image are integrated to achieve the accurate biomass mapping of single wood scale in the study area.

 

Comment #2

In conclusion, the random forest biomass estimation model based on the fusion of integrated multi-source features in this paper has shown high estimation accuracy, which is positively significant for accurate forest biomass or carbon storage survey and mapping. This text should be simplified.

Response:

Thank you for the helpful comment. We have made comprehensive revisions to the abstract. Please refer to lines 13-29 on page 1. We hope our modification can be approved by you.

 

Comment #3

Table 2. allometric equations should be rechecked. Please change R2 with R2.

Response:

Thanks for your comment. We are sorry for this problem. We have revised the problem accordingly. Please refer to table 2 on page 4.

 

Comment #4

Section 2.3 uAV or UAV? Please define correctly through the MS. Besides, there is no need to mention the data acquisition time.

Response:

Thank you for your comment. Sorry for the similar problem, we have corrected it. Please refer to lines 176-179 on page 4.

 

Comment #5

Lidar-360 software: The author should provide some information about the software in detail.

Response:

Thank you for this comment. We have added a detailed introduction to the software. Please refer to lines 196-200 on page 5.

 

Comment #6

Table 8, the author should recheck the variable notation and should not italicize them.

Response:

Thanks for your helpful comment. We have changed the italics of all the variables in this paper. Please refer to table 6-10 on page 7-9.

 

Comment #7

Result and discussion: In overall the results and discussion has been written well however, there are some phrases where the author needs to revise them properly.

Response:

Thanks for your comment. We have checked and corrected the academic phrases in the results and discussion. Please refer the page 11-23. We hope our modifications can get your approval.

 

Comment #8

For instance, Figure 4-7 needs to be explained further. The author should avoid the use of I, we or us in the manuscript.

Response:

Thank you for this helpful comment. We have added some explanatory text to these figures, and have changed all the use of I, we or us in the full text. Please refer to lines 416-420 on page 12 and lines 689-690 on page 23.

 

Comment #9

The conclusion should be further revised with the inclusion of a novel statement with quantified results.

Response:

Thanks for your comment. We have added the quantitative statistical results of biomass in the study area to the conclusion. In addition, we have made necessary modifications to other problems existing in the conclusion. Please refer to lines 684-690 on page 23 and lines 696-705 on page 23.

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Yes as response to comment 2, some of variable may be kept silent keeping important variable for figure fonts to be legible

Author Response

亲爱的审稿人:

We deeply appreciate the effort and time that you have spent in reviewing our manuscript “Biomass Estimation of Subtropical Arboreal Forest at Single Tree Scale Based on Features Fusion of Airborne LiDAR Data and Aerial Images” (ID: sustainability-2091738). We have studied the comments carefully and have made revisions which we hope meet with your approval. The outline of the revisions is listed as follows:

• We have modified figure 4-6 on page 12-13 to facilitate the labels of variable names and global figures for readers to better observe. At the same time, we have added relevant text explanations.

Comment #1

Yes as response to comment 2, some of variable may be kept silent keeping important variable for figure fonts to be legible.

Response:

Thank you for helpful comment. We have amplified the heat maps of feature correlation of the three species in different regions. All variable names of figure fonts can be clearly observed in the three enlarged images. At the same time, the global graphs can help readers to understand the correlation values of the whole graph. The revised figures please refer to figure 4-6 on page 12-13. The literal interpretations please refer to lines 479-481 on page 12. We hope the modification can get your approval.

Author Response File: Author Response.docx