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Peer-Review Record

Predicting Urban Trees’ Functional Trait Responses to Heat Using Reflectance Spectroscopy

Remote Sens. 2024, 16(13), 2291; https://doi.org/10.3390/rs16132291
by Thu Ya Kyaw 1,*, Michael Alonzo 1, Matthew E. Baker 2, Sasha W. Eisenman 3 and Joshua S. Caplan 3
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2024, 16(13), 2291; https://doi.org/10.3390/rs16132291
Submission received: 10 May 2024 / Revised: 14 June 2024 / Accepted: 17 June 2024 / Published: 23 June 2024
(This article belongs to the Section Ecological Remote Sensing)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript “Predicting urban tree functional trait responses to heat using reflectance spectroscopy” by Kyaw et al. has two fundamental objectives: to study whether known spectral indices can predict leaf trait responses and to analyze whether PLSR spectral models can quantify these leaf trait responses.

The work was carried out on 59 urban trees of 9 different species.

Numerous determinations have been made: measurement of air temperature, leaf water potential, specific leaf area, hyperspectral reflectance at leaf level. Additionally, several photosynthetic parameters were obtained at the leaf level by analyzing chlorophyll fluorescence.

A rich statistical analysis of the results was performed, including Pearson correlation analysis and the development of PLSR models.

The work is well written and the methodology used is well described.

However, I have concerns about the conclusions of the work and the discussion of the results.

The biggest problem I find in this work has to do with several of the results obtained, especially those shown in Figure 2, where the correlations between various measured values and those predicted by the PLSR model are explored. In my opinion, these correlations are shown in a misleading way, since a straight line, which is forced to pass through (0,0), is superimposed on the set of points. This fitting makes the data appear better correlated than they really are. If the least squares adjustment were performed without forcing the line to pass through (0,0), the slopes obtained would be completely different and much larger. In particular, in figures 2(C), 2(f) and 2(i), the shown fitting lines do not reflect the behavior of the data. Something similar also occurs in graph 2(h). The R2 coefficients are in general low for Figure 2. 

Before publication I suggest the authors to revise fittings in Figure 2 and to present and discuss correlations in a more realistic way.

 

Minor comment:

In table 2:… the fresh leaf reflectance (expressed as percentage).

Author Response

Dear Reviewer,

Thank you so much for providing review comments. Our responses to your reviews are provided in the attached. 

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Please find my comments in the attached document.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

Thank you so much for providing the review comments and suggestions. Our responses (blue texts) are provided in the attached.

Author Response File: Author Response.docx

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