PONE-D-24-03115Spectral indexes with different spatial resolutions in recogniz-ing soybean phenologyPLOS ONE

Dear Dr. Silva,

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1. The goal of the study is not clear. What the key research questions that your work address?

2. The methodology is too shallow and no allow to identify the novelty or contribution of the work. It was difficult to connect flowchart in Figure 1 with the method description.

3. It was very difficult to see whether the work effectively addressed the aim of the study in the conclusion.

4. To include some statistical findings in your abstract.

5. Performing exploratory data analysis to understand the variability within vegetation indexes across different phenological stages could be beneficial.

6. Verify the assumptions underlying Anderson's discriminant analysis, such as multivariate normality and homogeneity of covariance matrices, through diagnostic tests or graphical methods.

7. Evaluate the efficiency of vegetation indexes, compare the performance of the discriminant analysis model with baseline classifiers such as logistic regression or support vector machines.

8. Conduct sensitivity analysis to examine the impact of different parameters or settings on the results of Anderson's discriminant analysis.

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Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Major concern

1. The goal of the study is not clear to mean, or have not been well articulated in the last paragraph of the introduction. In fact, what the key research questions that your work seek to address?

2. The methodology is too shallow and has no debt to allow readers identify the novelty or contribution of the work. So much effort was spent on describing the data used, even in the aspect that talked about “Conducting the experiment.” Readers are expecting to see a step-by-step description of how the experiment was conducted. It was difficult to connect flowchart in Figure 1 with the method description. Every aspect of the work is just mixed up with content that ought to be in different section. In this current form, the work lack is no logical coherence. For example, I see you have two figures with caption as Figure 1. Secondly, for the second Figure 1 (flowchart), how was the reprojection done for both satellite images? How was the field data corroborated with the satellite image using the Anderson Discriminant Analysis? Lastly, what do you mean by Conclusions? You flowchart is supposed to be a concise summary of the approach adopted. But here, you confuse readers with “Conclusions”. How are we supposed to understand that while reading your methodology? Please, streamline the methodology to allow for easy reproducibility.

3. While reading your conclusion, it was very difficult to tell if the work actually addressed the goal of the study. I suggest you overhaul the entire manuscript, and then, clearly state the goal or objectives of the study. Then, try to show us in the conclusion that the goal has been achieved.

Minor comment

1. Why did you hyphenate “recogniz-ing” in the title (line 2)?

2. The title of this manuscript can be improved. Think about it carefully.

3. What do you mean by “Search Location” in line 100? Note that "Search location" and "Study location" are not exactly the same.

4. It would be very nice to include some statistical findings in your abstract.

Reviewer #2: Title: Spectral indexes with different spatial resolutions in recogniz-ing soybean phenology.

The title is not correct. "Indices" is the plural form of "index" when used in the context of measurements or indicators. Secondly the use of the hyphen in ‘recogniz-ing’ is unnecessary in this context. Similar mistake is also repeated in the Abstract section too, like: ‘cul-tivation’, and ‘demon-strates’. Therefore, the accurate title for the paper would be: "Spectral Indices with Different Spatial Resolutions in Recognizing Soybean Phenology." This usage adheres to standard scientific terminology in the field of remote sensing and geographic information systems.

In the abstract section, the findings are verbally expressed without substantiating the same with data. This is not a standard practice. The authors should have briefly described with data (in the abstract section) how different indices are correlated in identifying phonological stages of the soybean crop.

The spatial resolution of Amazonia 1 and sentinel 2 for (NIR, RGB) are 60 m and 10 m respectively. For a better accuracy assessment, the efficiency of each spectral indices needs to be checked at the same spatial resolution for both Amazonia 1 and sentinel 2 imageries, using resampling technique. This can be done either by upscaling the 10 m to 60 m or downscaling the 60 m to 10 m resolution. The authors have ignored this fact.

The temporal resolution i.e. the revisit frequency of each single SENTINEL-2 satellite is 10 days while the combined constellation revisit time is 5 days. The authors seem to have confused the revisit time of Sentinel 2 constellation with the temporal variation of MSI sensor onboard Sentinel-2. This is a major correction and it will impact the findings of this study.

Reviewer #3: Dear Authors,

Thank you for choosing PLOS for your interesting study. However, here are my specific suggestions and comments:

1. Consideration of Additional Statistical Tests: While Anderson's discriminant analysis is valuable for assessing classification accuracy, incorporating additional statistical tests such as ANOVA or pairwise comparisons could provide further insights into the significance of differences between vegetation indexes and phenological stages. This would strengthen the statistical robustness of your findings.

2. Exploratory Data Analysis for Variability: Prior to conducting discriminant analysis, performing exploratory data analysis to understand the variability within vegetation indexes across different phenological stages could be beneficial. Box plots or histograms could help visualize the distribution of index values and identify any outliers or trends that may impact the analysis.

3. Assessment of Model Assumptions: Verify the assumptions underlying Anderson's discriminant analysis, such as multivariate normality and homogeneity of covariance matrices, through diagnostic tests or graphical methods. Addressing violations of these assumptions ensures the reliability of the classification results.

4. Validation Techniques for Model Performance: Consider employing cross-validation or bootstrap resampling techniques to validate the performance of the discriminant analysis model. This would assess the generalizability of the classification results and provide confidence in the effectiveness of the selected vegetation indexes for phenological stage identification.

5. Comparison with Baseline Models: In addition to evaluating the efficiency of vegetation indexes, compare the performance of the discriminant analysis model with baseline classifiers such as logistic regression or support vector machines. This comparative analysis would offer a broader perspective on the suitability of different statistical approaches for phenological stage classification.

6. Sensitivity Analysis for Model Parameters: Conduct sensitivity analysis to examine the impact of different parameters or settings on the results of Anderson's discriminant analysis. This analysis would help identify optimal parameter choices and enhance the reproducibility of the classification outcomes.

By incorporating these suggestions, you can enhance the rigor and validity of your statistical analysis, providing a more comprehensive assessment of the efficiency of vegetation indexes in distinguishing soybean phenological stages.

Thank you in advance for taking into consideration my commnts and suggestions.

Kind regards,

Reviewer

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Reviewer #1: No

Reviewer #2: Yes: Dr. A Salim Khan

Reviewer #3: No

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Spectral indices with different spatial resolutions in recognizing soybean phenology

PONE-D-24-03115R1

Dear Dr. Silva,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Claudionor Ribeiro da Silva

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: "Differentiation"?

In table 3 and other places, is it not better to just say, "Normalized Difference Vegetation Index"?

I think you should deal with this word: "Differentiation"

Reviewer #2: The comments have been addressed adequately. The manuscript now appears to be an actual contribution to science. I recommend that this manuscript may be accepted for publication.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Dr. A Salim Khan

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