Tree Recognition and Crown Width Extraction Based on Novel Faster-RCNN in a Dense Loblolly Pine Environment

Round 1

Reviewer 1 Report

1. Tree crown segmentation in mature forest or dense forest is a difficult problem. It is of great significance to study tree crown width in dense forest. Introduction needs provide the review focusing on the hotspots, difficulties, limitation and trends in the field of tree crown measure.

2. Line79-87, It was not clear what the problems the authors want to explain though the several examples. I think the authors should write a conclusive statement.

3. Line 114，line 117，there were two different statements about the location of study area, the authors should check it.

4. line 299 to 304，the sentence “The total number of iterations was 20,000, and the model 303 was saved every 5000 times. The learning rate was set to 0.001, and the batch_size was set 304 to 256” was repeated, the authors should check similar errors carefully.

5.Line 365-368 and the table 2, the SDD model performed better than the target model FPN_Faster-RCNN_ResNet101. I don’t think it is helpful for supporting the conclusion. Moreover, the method 4 is more complicated than SDD, what is the significance of improving the model?

6. The authors combined Resnet101 and FPN as backbone to create FPN_ResNet101 structure, however, some studies also reported with similar structure. What’s the innovation of the method in this study, please clarify.

7. The authors selected mature loblolly pine plot as object. From figure 11 showed that the loblolly pine had a homogeneous structure, which led to obtain a good result. However, the effectiveness of the proposed algorithm in the original forest or broad-leaf forest maintained unclear. The authors should select 2-3 study plot represented different forest structure to explain the robustness of the algorithm.

 

Author Response

Dear Reviewer:

Please see the attachment.

Kind regards.

Author Response File: Author Response.docx

Reviewer 2 Report

Reviewer’s Report on the manuscript entitled:

Tree Recognition and Crown Width Extraction Based on Novel Faster-RCNN in Dense Forest Environment

 

The authors proposed a fast region-based CNN algorithm for tree crown identification and crown width extraction in an environment of a forest stand with a high crown density. They showed the performance of their algorithm in a region in Texas, USA. While the topic and results are important, the presentation and structure of the manuscript should be improved. Please see below my comments.

 

Lines 22 and 23. Please remove. Note that Abstract should not include citation.

Please replace “the author” with “Lou et al.”

Line 66. Here please also include the following articles about most recent applications of UAV and AI for crown identification and monitoring:

https://doi.org/10.3390/rs14051239

https://doi.org/10.3390/drones5030077

Line 88. Simply instead of “In 2021, the author published a paper on the application” say “Lou et al. showed an application…”

Line 90. Just say USA.

Lines 94-110. This is unclear. What is the objective of this research? Please avoid talking about the results of your method here rather highlight the main contributions of this paper using bullet points.

Figure 1. The map should have geographical latitude and longitudes and should have better quality. Also, a small continental map should be displayed where the region is highlighted in it.

Figures 5 and 7 should be improved. Please increase the font size and resolution.

Figures 6 and 9 the font size is better but please improve their resolution.

Line 320. Please insert a hyphen “F1-score”

Line 334. “data” is plural. Here it should be “The data come from…” Please check and correct this issue elsewhere.

Line 354. Say “…mentioned in Section 3.1.1 as the…”

Figure 12. Please increase the font size of the text and numbers in all the panels.

Line 414. Is method 4, FPN_ResNet101? This sentence is unclear. Please rephrase.

Line 420. Fastrt? There are many punctuations/typos’ issues in the manuscript. Please carefully proofread and correct them.

Please mention the limitations of the study and future work in the conclusion section.

Please follow the MDPI guideline for style and format of references.

Thank you!

Author Response

Dear Reviewer:

Please see the attachment.

Kind regards.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

I would like to thank the authors for addressing my comments and improving their manuscript. In my view, the manuscript can be accepted.

Regards,