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Peer-Review Record

Discovering Tree Architecture: A Comparison of the Performance of 3D Digitizing and Close-Range Photogrammetry

Remote Sens. 2025, 17(2), 202; https://doi.org/10.3390/rs17020202
by Kristýna Šleglová *, Marek Hrdina and Peter Surový
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2025, 17(2), 202; https://doi.org/10.3390/rs17020202
Submission received: 22 November 2024 / Revised: 16 December 2024 / Accepted: 1 January 2025 / Published: 8 January 2025
(This article belongs to the Section Forest Remote Sensing)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Please see comments in the PDF file. This work compares two technologies that measure tree components. The two technologies are very different, and results show mixed results. The limitation of the study is that small trees are used for testing, but nevertheless the results are interesting and provide insights to accuracy of measuring complex structures like trees.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Meaningful work with some commence are as follows:

Close-Range Photogrammetry is not an optimal strategy for constructing complex tree models. This is because, when trees possess high leaf area density and numerous twigs or branches, occlusion effects can occur, resulting in deficiencies in various parts. Therefore, comparing the results with terrestrial LiDAR data serves as a viable method for assessing their accuracy. Additionally, to demonstrate the effectiveness of the proposed methodologies, more mature and intricate tree models should be provided.

Tree movement due to wind poses significant challenges for photogrammetric 3D reconstruction. A highly relevant paper titled "A framework for phenotyping rubber trees under intense wind stress using laser scanning and digital twin technology" (with the focus on tree modeling under wind stress) could be referenced in the introduction, potentially offering beneficial insights for improving the current work.

The study utilized TreeQSM software for automated dimension estimations, yet manual measurements were still necessary for validation. To facilitate improvement, some quantitative comparisons should be provided.

Furthermore, other tree modeling algorithms could be listed for comparison with the existing method.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

I appreciate authors’ significant and valuable contributions during this round of revisions. The efforts have significantly enhanced the quality and clarity of the paper, making it more aligned with the journal's standards. Consequently, I have no remaining reservations and am fully in agreement to accept this revised submission.

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