A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization

Round 1

Reviewer 1 Report (New Reviewer)

This research paper provides a comprehensive description and analyses of remote sensing for crop characterization.

However, several issues remain:

1.     The manuscript did a comprehensive overview of the published articles related to remote sensing for crop characterization, however, the advantages and disadvantages of techniques for different crop characteristics need to be discussed in detail; the theories and principles of different platforms or methodologies weren’t well elaborated.

2.     The importance of food supply and crop yield are mentioned several times in the manuscript, however, the connection between crop characteristics and crop yield or how to apply remote sensing techniques to monitor crop yield weren’t discussed sufficiently.

3.     Table 1 summarized studies on crop parameter estimation through remote sensing techniques, while the selected articles are not that representative.

Author Response

Please see the attached file.

Author Response File: Author Response.docx

Reviewer 2 Report (New Reviewer)

This paper conducted a meta-analysis of 277 papers published in the last three decades and focused on retrieving crop biophysical parameters from remote sensing data. This study gathered research works in crop parameter estimation and provided a statistical analysis of trends in this field of research. The article is reasonable in structure and comprehensive in summary, but there are also some small problems:

1. Check the naming of all tables and figures, the format should be uniform, ‘Table ⁎)’ changed to ‘Table ⁎.’and ’Figure ⁎)’ read ‘Figure ⁎.’. In addition, check and standardize the format of all tables (three-line table) and formulas.

2. Figure 8 missed the title of the vertical axis.

3. The description of LIDAR in the introduction is irrelevant to the previous text and further explanation of its differences with other remote sensing techniques is suggested.

4. The line 487 “Except for barley, the median R2 was above 0.6 (Figure 6)”in the Figure 6 should be Figure 16.

5. The Section 4.3 is too long. Setting some subtitles is suggested as in Section 4.2

6. The conclusion section is weak. The contribution of this paper needs to be further emphasized.

Author Response

Please see the attached file.

Author Response File: Author Response.docx

Reviewer 3 Report (New Reviewer)

This manuscript provides a comprehensive and meaningful review on crop biophysical parameter estimation based on a meta-analysis of 277 papers published in the last three decades. It is well-prepared.

Lines 26-27, P1/56 & Figure 10: The sentence "In addition, the analyses confirmed that the Normalized Difference Vegetation Index (NDVI) had been the most widely used vegetation index to estimate crop parameters." is easily misleading. In many papers, NDVI was just tested together with other VIs, but it was not necessarily the selected best one.

You said "The selected studies were published from 1990 to 2020. " (Lines:188-189), so it is not surprising that "The first paper on remotely sensed data for crop parameter estimation was published 238 in 1990."(Line 238)

Line 917, P37/56: What's the unit of RMSE values?

Author Response

Please see the attached file.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report (New Reviewer)

No more questions.

Author Response

Thank you so much.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

I have read this paper which mainly presenting a meta-analysis of remote sensing technologies and methodologies for crop characterization. This is really an interesting review article which summarize past 30 years publications to identify trends in crop monitoring using remote sensing systems and imagery dataset. It documents the methods, challenges, and opportunities from the 180 scientific literature. There are always a lot of contribution of such work for world-wide remote sensing community. In the introduction the authors presented a very focused literature review. In my opinion, the overall paper is well written and individual section has been addressed fairly. The overall analysis provided in this paper are quite interesting, and the paper is technically correct with proper references.

Reviewer 2 Report

Major comments

 In this study, the authors reviewed the current studies about remote sensing applications from 277 papers. In my opinion, the number of papers is not enough to summarize the current progress of remote sensing applications in crop characterization. If the study mainly focused on crop yield, the title should be more specific. Or this review aims to discuss crop parameters. The authors should explain the specific parameters. From the abstract, the authors did not provide any bright ideas from the review, and the readers cannot find interesting or useful findings from the review. The abstract should be further improved. Besides, the introduction section was not organized well. Various datasets, methods, and such words were mentioned, but no specific methods were explained when the authors introduce previous publications. Any advantages or disadvantages of these methods were not discussed.

For the method section (3.2. Data processing), the author did not conduct data processing or introduce any method to analyze data from publications. For other sections in Methods, the authors only introduced the statistics generated from publications. And such statistics can not provide valuable information or comparison.

In addition, it cannot provide valuable information to compare the R2 in section 3.2.5. It is not useful to put all R2 values together for different crop parameters. It is better to compare for the same parameter estimation. And such a comparison can not provide information about the methods. The accuracy depends on the study scales, environmental factors, datasets, etc., not only determined by the approach.

This review provided a lot of data (such as R2), but no valuable information could be found from these datasets. The authors only simply described some common information, such as the 4.2 section. The readers can not see the interesting findings from reviewing hundreds of publications. 

 

 

 

I also have some other concerns with this article:

1.                  Abstract: “Several research studies”, May consider revising the expression.

2.                  Abstract: “to identify trends in crop monitoring research using remote sensing data and tools”. Here, what does the tool mean?   

3.                  Abstract: it makes the readers confused about the abstract. What is the major target of this study? Crop production estimation methods using remote sensing? Or crop features characterized by the remote sensing images? It is not clear to readers.

4.                  Introduction: Line 78-19: only NDVI was mentioned here. If the authors can review more about other vegetation indices?

5.                  Introduction, Line 87-92: if the authors can provide some references.

6.                  Line 199: do not address, revise to did not address

7.                  Lines 165-168: “authors with the most publications”, revise this sentence. Please rewrite this paragraph and make it clear to readers.

8.                  Figure 1: the authors can provide the meaning of some abbreviations. And explain the star marks’ meaning.

9.                  Line 192: explain the VOS.

10.              Figure 4 means “The number of studies per year”, but the numbers in this figure are percentages.

11.              Figure 5: Do the study sites mean study areas or the authors’ locations. Does it mean the site-level or regional studies?

12.              Lines 276-279: if the authors can provide some references?

13.              Lines 285-287: any references about the categories?

14.              Line 290: Platform, might be better to change Remote Sensing Platforms.

15.              Line 308: change sensor to Sensors

16.              Line 370-371: the application of MODIS in agriculture should be far more than 39 studies.

17.              Lines 382-383: Provide any references to classify these methods.

18.              Line 400: why put machine learning methods to non-parametric approaches? The machine learning model also needs to provide parameters.

19.              Line 411: this review paper mainly talked about the crop parameters: biomass and LAI? If other parameters were included?

20.              Line 423: “Thus, R2 could be negative” is that true?

21.              Figure 19: the comparison for different platforms should consider the crop parameters, methods, and evaluation datasets. Such comparison could not verify which sensor performs better.

22.              4.3 section: it might be better to add methods for the sub-title if this section is talking about methods

23.              Line 701: so what kind of advantages of ANN have on crop parameters estimation compared to other methods?

24.              Section 4.5: if the format was changed?

 

25.              The subtitles of the discussion section should be improved. 

Comments for author File: Comments.pdf

Reviewer 3 Report

See attached.

Comments for author File: Comments.pdf