Characterizing Spring Phenological Changes of the Land Surface across the Conterminous United States from 2001 to 2021
Round 1
Reviewer 1 Report
1. Given many similar studies have been reported, the novelty and contribution the study is not significant.
2. Why did you use EVI? How about other indexes?
3. The distribution of samples from USA-NPN, Harvard Forest data were not shown.
4. The correlation shown in Fig.,5 is not significant without the P. The differences between them and the quality of your results should be further analyzed.
5. The factors caused the SOS change should be analyzed.
6. In sum, the novelty, contribution, workload and analysis of the manuscript are not adequate for publishing in the journal
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Dear Authors, I have reviewed in detail the paper "Understanding the Spring Phenology in the Conterminous United States for 2001–2021 Based on the MODIS Data."
I have no significant objections to the paper. However, the paper has questionable value in the context of the elements of the novelty of the methodology and the significance of the obtained results regarding the journal in which it is sent. I simply can't see it. Namely, considering the input data specifications that were used, it is difficult to draw significant conclusions. Also, the methodology is generally known and easily implemented. Remote Sensing is a Q1 journal with an IF of 5,349. I believe that this kind of journal deserves a paper that will not only have a good structure but also have a satisfactory element of novelty regarding the methodological processing and thus the significance of the results. I suggest sending the paper to another MDPI journal, ranked somewhat lower in indexing.
All comments below are made with the aim of improving your paper:
Title: The title is appropriate for the content of the paper. However, format it according to the guidelines of the journal “Understanding the Spring Phenology in the Conterminous United States for 2001–2021 Based on the MODIS Data.”
Abstract: The summary should be shortened without violating its structure. The total number of words needs to be between 250 – 300. For example line 18 “(i.e., forest, grassland, cropland, and urban and built-up land)” is not necessary, line 21 “(including USA-NPN and Harvard Forest data)” is not necessary, line 27 “(either significantly advanced or delayed trends)”
Introduction: The introduction is very well written. The introduction to the research issue is written from general to specific. The authors have referred to a sufficient number of literature, however, in some places more can be added. All the problems that have been recognized in previous research are highlighted. The research task is clearly defined. These are my suggestions:
• line 42 – if it is “commonly used” add more papers.
• line 43 – add more papers to support that claim.
• line 44 – define what "regional scale" would represent in that context, what is the size of the study area? because in the rest of the text you mention the terms “continental” and “global” scale. Try to give some explanation…
• when writing “Zhang, et al. [32]” I believe that the comma (,) is not necessary here. Delete it. This is done on multiple occasions in the Introduction.
• line 91 – start with “Therefore”, satellite-derived phenological metrics…
Study Materials: I suggest renaming this paragraph to “Materials and Methods.”
• I suggest that you create a methodological scheme for the entire methodology process which consists of several steps.
Satellite data: I suggest renaming this paragraph to “Satellite Data Acquisition”
• line 113 “Figure 1” is more appropriate to be located behind line 122.
• line 123-124 - rewrite this sentence so that there is no link, that is, refer to it as a source [XX] and add it to your literature
• line 120 – 122 “We extracted the four categories of the forest, grassland, cropland, and urban and built-up land areas required for this study based on the International Geosphere Biosphere Programme (IGBP) classification scheme [45] in the product.” – Can you add this map, since you use this in your analysis?
In-situ: I suggest renaming this paragraph to “In-Situ Data Acquisition”
• line 129 can you give the map with the location of the flux tower observations which are used for ground-based phenology observation?
• line 131 can you give the map of the location of these sites?
Methods: I suggest renaming this paragraph to “Satellite Imagery Processing”
• line 143 "The performance of satellite-derived SOS was evaluated using USA-NPN and Harvard Forest data"- This is already repeated several times in the text.
Data pre-processing:
• line 147 “sensors specifications”
• line 148 “based on the quality control bands of the MOD09A1 product” Did you perform quality control or was it already performed? Explain in more detail.
Time series fitting: I have no complaints about this part-
Spring phenology extraction:
• line 175 if it is “widely accepted” add more papers.
• Figure 2. - can you put different color for EVI2, both EVI2 and reconstructed EVI2 are gray therefore it is difficult to distinguish them-
Assessment and analysis: I suggest renaming this paragraph to “Accuracy assessment and Correlation analysis”
Spatial distributions:
• line 198 can you define more precisely what the term represents “generally earlier”? Is there an exact number of days that describes that term?
• Line 201 this should be Figure 3 not Figure 2
• dimensions of Figure 4 can be smaller
Assessment:
• “significantly correlated” is mentioned for both r = 0.62 and r = 0.42, the difference in the description should still be highlighted.
• line 217 – 221 needs to be expanded with referencing and comparison with results from other studies that used similar methods for accuracy assessment.
Trends analysis:
• In figure 8 it is very hard to observe the trend distribution of SOS in four land cover types. Can you zoom in on the mentioned locations on the map?
• line 289 – 297 can this part of the discussion be expanded a little more? Add more about whether relatively poor input data in the context of spatial resolution and a smaller number of in-situ samples about the surface of the studied area can cause these results, which then resulted in this interpretation.
Conclusion:
• conclusions (1), (2), and (3) can be put in separate lines
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
The manuscript presents an interesting study related to the connection between the dynamics of spring phenology and climate change.
The manuscript needs to be improved, in particular with regard to a better description of the results.
Note to the manuscript:
· Software used is not presented in the Methods section.
· Two figures are labeled as figure 2 – the second figure must be figure 3.
· Figure 3(2) – the scale is from 1 to >200 Days of Year. At the same time, the data values presented in the figures range from 95 to 145. Why values outside the studied range of values are presented?
· Figure 4 – The caption of the figure should be clarified - there is no explanation of the light blue area.
· Figures 6 and 7 – DOY is indicated on the Y axes, but there is no explanation for such an abbreviation in the text. It's probably the day of the year.
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
The study described in the paper appears to be a good example of computational geography approach to land cover and climate change exploration. The text is well structured and sounds clear in whole.
Three significant drawbacks have to be pointed in result of reviewing:
1) The phrase "... results showed that there was a significant positive correlation between the timing of SOS and latitude" (rows 18-19) sounds slightly confusing in the abstract, as the general dependence between geographic (latitudinal) position of the location and growing season starting date at the location is well known and almost obvious. Probably, it is better to redesign/crystalize the idea that was thought to be presented by this sentence.
2) Implementation of phenology as the discipline that "studies the timing of recurring biological cycles and their connection to climate" (rows 36-37) is too discussible from two points of view. First, not only climate is discovered in phenological studies as a factor of biological cycles. Second, the agrometeorology is another one discipline that studies exactly weather impact onto (agricultural) crops. It is better to describe in details the body of phenology knowledge, or to introduce the body of described study as a part of phenological studies (bearing in mind that phenology domain is quite wider).
3) The study of growing season trends for urban and built-up lands (row 245) have to be commented in details, as these land types looks like have to be excluded when studying vegetation cover. Authors' point of view on this problem have to be presented in the text.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 5 Report
Dear authors,
Thank you so much for your relevant and essential investigation of the vegetation phenology in the conterminous United States for 2001–2021 based on the MODIS data.
Line 20 – Did you estimate the error of the delayed trend?
L. 24-26 – Did you estimate the error of the range of SOS interannual variation?
L. 32 – Authors can change the keyword "vegetation phenology".
L. 99 – Which coefficient of correlation did you use?
L. 112-125 – Please, add data about the accuracy of the estimation area of four categories of land areas.
L. 117 – Why did you analyze data from July 2000 to December 2021 if the article's title contains another period?
L. 192 – Please, separate out results and discussion.
L. 201 – Please, edit the number of figures.
L. 192-297 – Please, compare your results with another study (or studies).
L. 120-121 – Could you describe all four categories of land areas? The USA has extensive bar land, wetlands, and pastures. What did the criteria for separating forests and built-up areas for your study in the USA?
Figure 1 – Colors of legend for evergreen needleleaf forests, evergreen broadleaf forests, deciduous needleleaf forests are too similar. Please, improve it.
L. 299-315 – Please, improve the conclusions.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The manuscript has been well revised. However, I still think the contribution of the paper is not significant. This should be further improved.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 2 Report
Dear authors, you have taken into account all the comments I mentioned. However, they are given with the intention of improving the paper and sending it to another lower-ranking journal. Due to the reasons stated in the text below, I still believe this paper cannot be published in Remote Sensing.
I still believe that the paper has questionable value in the context of the elements of the novelty of the methodology and the significance of the obtained results. I still simply can't see it. Namely, considering the input data specifications that were used, it is difficult to draw significant conclusions. Also, the methodology is generally known and easily implemented. Remote Sensing is a Q1 journal with an IF of 5,349. I believe that this kind of journal deserves a paper that will not only have a good structure but also have a satisfactory element of novelty regarding the methodological processing and thus the significance of the results. I suggest sending the paper to another MDPI journal, ranked somewhat lower in indexing.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 5 Report
Dear authors,
thank you for your efforts and improving the manuscript.
Author Response
Thank you for your careful and responsible review.
