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Peer-Review Record

Identification of Dominant Species and Their Distributions on an Uninhabited Island Based on Unmanned Aerial Vehicles (UAVs) and Machine Learning Models

Remote Sens. 2024, 16(10), 1652; https://doi.org/10.3390/rs16101652
by Jinfeng Wu 1, Kesheng Huang 1, Youhao Luo 1, Xiaoze Long 1, Chuying Yu 1, Hong Xiong 2 and Jianhui Du 1,3,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Remote Sens. 2024, 16(10), 1652; https://doi.org/10.3390/rs16101652
Submission received: 5 February 2024 / Revised: 6 April 2024 / Accepted: 29 April 2024 / Published: 7 May 2024

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Specific comments referring to line numbers, tables, or figures.

P value must be written in italics, correct lines 424, 427, 431 and others.

Minor comments:

1.     Line 33: Delete , after the word species.

2.     Line 34 and 35: Arrange key words in alphabetical order.

3.     Line 47: Delete “so as”

4.     Line 51: Replace “in” the island with “on”

5.     Line 56: Replace “were” with “was”

6.     Line 63: Correct spelling for “challengable” to “challengeable”

7.     Line 65 Replace “in” the island with “on”

8.     Line 94: Replace “on the basis of” with “based on ….”.

9.     Lines 98: Change “assessing” to read as “assess”

10.  Line 99:  Change “determining” to read as "determine”

11.  Line 100: Change “exploring” to read as " explore”

12.  Line 116:  Delete space between “spray, and drought…”

13.  Line 125: Delete Sketch

14.  Line 142: Replace “unaccessible,” with inaccessible….

15.  Line 163: delete , after the word band

16.  Line 164: Add , after the word “brightness”

17.  Line 178: change heterogeneity to heterogeneities

18.  Line 188: Add s to calculation.

19.  Line 198: Make it read as correlations.

20.  Line 261: Change “accuracy” to accuracies.

21.  Line 277: Add space after the word “separately”

22.  Line 288: Delete the before the word " adding”

23.  Line 306: delete letter “s” from the word “reduces”

24.  Line 376: Add space between these 2 words “multiplespectral”

25.  Line 380: Correct grammar “…. in identify those …”

26.  Line 408: Add a , after the word “aspects”

27.  Line 421: Add space after the word “slope”

28.  Line 422: Add space after the word “slope”

29.  Line 437: Add space after coastline.

30.  Line 437: Add space after “Anyu Island”

31.  Line 449: Delete space after “adding”

32.  Line 457: Consider “decrease to decreased”

33.  Line 458: check “pixes”?

34.  Line 461: consider revising it to discrepancies.

35.  Line 474: Add s to sand.

36.  Line 482: Add a dash between “high water”

37.  Line 486: Check this “adequent”

38.  Line 492: Check this “adaptataions”

39.  Line 505 & 522: Consider replacing “more close” with “closer”

40.  Line 534: Add s on “ecosystem”

41.  Line 540: Add , after “factors”

Comments on the Quality of English Language

Moderate revision is required. See some of my suggestions to the authors above.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Some comments are included within the text. Here is a summary:

#The introduction needs improvement, especially in the state-of-the-art ML models in similar studies, i.e., natural vegetation analysis. So, hopefully, the arguments for these four particular models used in the experiment will be discussed.

#The features selected and used in the analysis must also be discussed more deeply, referring to the bibliography or your consideration. Here, one expects the species description regarding their distribution on the island, spatial characteristics, and habitat needs. Therefore, some parts of the Discussion should go to the Introduction to show the context and characterize the species.

#What was the reason for selecting particular features and their parameters? Again, please refer to other studies or enforce your consideration. What was the reason for establishing unique sets for each model? Have you tested some other solutions?

#How do you perform DEM from images? More details, especially accuracy, are needed.

#How do you select the samples for training and validation? More details and spatial distribution are required. 

#What are the recommendations for other studies on natural veg analysis? Do you think this study (i.e., this particular island) has a unique character, or can it be considered more universal? A more specific description of the region would be nice to read here.

#Does the title need "four" ML models? Please rethink and make it shorter without repetition, like UAV and multispectral images. Is the period of image acquisition relevant to the study and conclusions? 

#Some minor issues, like the linear function in Fig. 3b, or delta kappa =? Fig. 4 explanation is not clear enough. Fig. 1 - It's challenging for those unfamiliar with this world part to recognize it. More specific indications should work. Why this particular area? Is it something universal for testing, or is it something unique?

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript, titled "Identification of dominant species and their distributions in an uninhabited island based on Unmanned Aerial Vehicles (UAVs) multispectral images and four machine learning models," employs four machine learning models to identify and locate seven dominant species on Anyu Island. It also explores the impact of different feature combinations on the accuracy of identifying these dominant species. This study offers valuable insights into the identification and distribution of dominant species on uninhabited islands, thereby contributing to vegetation management and restoration efforts in such environments. The manuscript is well-structured and aligns with the scope of the Journal. While the accuracy of the results is satisfactory, there are some aspects that need further clarification before considering it for publication.

Comments:

1. The manuscript presents a case study focusing on a particular area, comparing various feature combinations and machine learning methods. However, it is essential to highlight the innovative aspects of this research. Is the novelty primarily in the methodology employed or the new discoveries made?

2. Can the findings, including the optimal model and feature combinations identified on Anyu Island, be extrapolated to other uninhabited islands? It would be beneficial to elaborate on the broader significance and potential applications of this study beyond the specific island setting.

3. How did the authors define and distinguish "dominant species" on Anyu Island? Clarification on the criteria used for this classification would enhance the understanding of the research methodology.

4. In Section 3.1, some dominant species exhibit significantly higher PA values compared to UA values. Providing explanations for these discrepancies would strengthen the interpretation of the results.

5. While a standard practice involves dividing samples into training and validation sets using an 80:20 ratio, the variability of machine learning results with different training data is acknowledged. Could the authors clarify whether a single set of training data was utilized or if multiple sets were employed, such as through k-fold cross-validation, to ensure robustness and reliability in the study's outcomes?

 

Comments on the Quality of English Language

Minor editing of English language required.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for including all the suggestions from my previous review. 

Reviewer 3 Report

Comments and Suggestions for Authors

All my concerns have been explained. The manuscript is ready for publication after minor editing.

Comments on the Quality of English Language

Minor editing

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