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Article
Peer-Review Record

Tree Species Classification and Health Status Assessment for a Mixed Broadleaf-Conifer Forest with UAS Multispectral Imaging

Remote Sens. 2020, 12(22), 3722; https://doi.org/10.3390/rs12223722
by Azadeh Abdollahnejad * and Dimitrios Panagiotidis
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2020, 12(22), 3722; https://doi.org/10.3390/rs12223722
Submission received: 10 October 2020 / Revised: 31 October 2020 / Accepted: 10 November 2020 / Published: 12 November 2020
(This article belongs to the Section Forest Remote Sensing)

Round 1

Reviewer 1 Report

The authors present the novel approach of tree species and tree health classification method based on UAS data. The methodology is described in detail, the statistical evaluation of data is complex, and results are fully documented and well presented.

The paper fits well to the scope of the journal and is very interesting for readers.

Some corrections of the used terminology and figures are needed. Comments and recommendations are included in the attached file.

Let me recommend to extend the discussion of the results in the paper.

I would also recommend to rewrite and extend conclusions. The conclusions section just summarizes results. It should be more focused on the importance and impact of the research, the scientific contribution of the presented approach, and its usage in practice.

 

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

The manuscript titled “Tree species classification and health status assessment for a mixed broadleaf-conifer forest with UAS multispectral imaging” represents very interesting scientific research. The idea of the study is interesting and presents enough novelty. The manuscript title is accurate and correct. In the entire manuscript, authors use standard technical and scientific terminology. After a well-written Introduction, the authors explained in detail used Materials and Methods. Results were conducted according to the scientifically correct approach. The conclusions are logical and based on the results of the research. The manuscript topics fit in the Remote Sensing aims and scope. I recommended this research to be accepted after major revisions.

Comments for authors:

  1. Although the manuscript topic is interesting, the real research application of the findings and conclusions must be better explained in detail. I suggest adding a paragraph(s) to emphasize more the real applicability of the research finding in the future.
  2. Please, extend the discussion and split it into a separate section.
  3. Suggest adding more information about photogrammetric procedures and the production of the digital orthophoto map. The camera calibration is one of the most important stages in photogrammetry. Is it used fixed precalibrated interior parameters in the entire process or not? Please explain that. Further, add more information about UAV and UAV equipment. Did the UAV use the gimbal? What kind of? Also, please add more state-of-the-art references in topic of camera calibration and other UAV-based photogrammetry in the manuscript. These newly added paragraphs with the explanation of the processes mentioned above, as well as, camera calibration parameters, could significantly improve the manuscript. Proposed papers that can help authors to improve manuscript in the field of camera calibration: “Low cost surveying using an unmanned aerial vehicle”; “Gimbal influence on the stability of exterior orientation parameters of UAV acquired images”; “Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance”; etc.
  4. Suggest adding more information about tree species classification. Also, please provide the final tree species classification map or add vector symbols to figure 10. In the introduction and the entire manuscript can be added more actual references. A lot of references are older than ten years and more. Please add more references in the topic of “Automatic/semiautomatic/machine learning method for mapping based on UAV imagery”. This topic is very popular in the last years, and a lot of quality research is available.
  5. Please use a single letter as a variable instead of words (e.g., overall accuracy, commission error, producer’s accuracy, etc.). The variable names must have the same font style and size in equations, on figures, tables, and in the manuscript text. Please describe/introduce all variables used in equations or on figures in the manuscript text.
  6. All equations must be adequately cited in the entire manuscript.
  7. Use GNSS instead of GPS (page 5, line 190).
  8. Please, double-check all references and reference style.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The authors have addressed almost all reviewers' comments, and the manuscript in its current version is improved compared to the original.

I have no further comments, and the revised manuscript can be accepted.

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