Using Multi-Angular Hyperspectral Data to Estimate the Vertical Distribution of Leaf Chlorophyll Content in Wheat

Round 1

Reviewer 1 Report

Although the topic of the manuscript is of wide interest in remote sensing community, there are some issues the author may need to address. 

2.2. Data acquisition
Did you apply any filter for smoothing reflectance data?

2.3 Chlorophyll-sensitive spectral index selection
Why did you choose these indices? There are vast number of indices for detecting chlorophyll.

3) Model Calibration and Validation
Are all 67 samples collected in the experiment used to estimate the vertical distribution of leaf chlorophyll content? Is there sample data available to verify the accuracy and stability of the model?

Table 7.
Are these coefficients significant? Why didn't you use Akaike Information Criterion (AIC) for evaluating how well a model fits the data?

4. Discussion
You said that the TCARI index and MCARI/OSAVI are both chlorophyll sensitive indexes. Did you assess the influence of soil conditions? Could you offer any reasons?

Author Response

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Reviewer 2 Report

The submitted research paper aims to determine the effect of the vertical chlorophyll distribution on the multi-angular spectrum and to enhance the monitoring ability of the Leaf chlorophyll content. The authors suggested a good multi-angular observation strategy that gave substantially higher accuracy than the single-angle strategy, even when the optimal angle was used.

I saw the authors implemented all my comments and I found this revised version of the work very easy to read and perfectly written. The concepts and the ideas communicated in this work are at high level. The manuscript has a good structure with good and coherent language. Therefore, I see that this version of the manuscript can be accepted for publication.

Author Response

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Reviewer 3 Report

The research described in the article is generally well designed. The techniques described have been commonly used but their usage has a sufficient level of novelty in the literature. However, there are some minor comments on the article. Please, find the comments in the attached file.

Comments for author File: Comments.pdf

Author Response

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Round 2

Reviewer 1 Report

The results are now richer and there is some actual information that can be deduced. However, my comments have not been addressed, but rather ignored.

I asked whether the sample size was enough big to estimate the vertical distribution of leaf chlorophyll content. Could you clarify the reason why you thought it was enough?

5. Discussion
Could you offer the reason why OSAVI and MCARI/OSAVI had good responses in Discussion section?

Author Response

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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

Dear Authors,

The presented manuscript's main topic is leaf chlorophyll content determination at different vertical layers in winter wheat using remote sensing methods. This topic results interesting as a research question for this reviewer. However, the manuscript has many major mistakes that make really difficult to read it. It was not possible for me to understand the data acquisition method, the figure 1 is not explaining the image acquisition method. In general, the materials and methods section is really poor. In the results, how do you know that there is a redundancy between spectral indices at similar VZAs? Line 538 says that the largest coefficient of determination of the TCARI for the upper layer of leaf chlorophyll content was found at VZA30 to 40. However, it is not possible to see that in Figure 3. Line 588 highest R2 was 0.72 in the middle layer. However, in figure 3 the maximum value is around 0.30. In my point of view, section 3.4 is not possible to understand. How do you obtain the conclusion of lines 602, 603, and 604? Figure 4 is not cited in the text. In my point of view, it is not possible to understand the manuscript and the topic as it is presented is not novel. There are many minor mistakes that I will not comment on because my recommendation is to reject the manuscript in the present form.

Reviewer 2 Report

The submitted research aims to find the LCC of different vertical layers of the canopy of winter wheat using multi-angular remote sensing and spectral vegetation indices.  I found this paper very interesting where Several technical aspects were nicely implemented and explained sufficiently. Undoubtedly, authors invested huge amount of time and have made a great effort to produce this high-quality of research which is clearly structured and the language used is largely appropriate. I see that this manuscript in its form and level deserves to be accepted for publication in MDPI-RS but addressing below MINOR COMMENTS is recommended before the final approval of this excellent paper.

COMMENTS:

• The title of this paper looks good but can be improved.
• I found the abstract very well structured and contains a good overview about the undertaken work.
• Make sure to define ALL the acronyms form their first appearance in the paper.
• I suggest for the authors to update the list of references with the latest papers related to the topic of their work.
• All the references MUST BE CHECKED and formatted as required by MDPI-RS, also make sure that all the references have DOI number unless it is not available.

Author Response

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Reviewer 3 Report

Although the topic of the manuscript is of wide interest in hyperspectral remote sensing community, there are many major issues with the manuscript as the authors can find some of them in the following.

1. Introduction
Your literature review is not sufficient.
LL.56-57
Light stress changes the allocation of chlorophyll-a and b and then shading treatment is effective to increase chlorophyll content in the short term

LL.60-62
I agree with that various methods have been presented for estimating the canopy chlorophyll content using hyperspectral reflectance data. However, you should have cited some previous studies and described what kind of techniques have been used.
There are some approaches for quantifying chlorophyll content using hyperspectral remote sensing and one of them is through the application of hyperspectral indices, which you mentioned. Also, some radiative transfer models have been proposed and some previous studies reported the inversions of them were effective for estimating chlorophyll contents. Why did you ignore them?

L. 72
Reference is missing.

2.2. Data acquisition
FieldSpec has three detectors including visible and near-infrared (VNIR), Short Wave Infra-Red (SWIR) 1 and SWIR 2, and some inherent variation in detector sensitivities often causes differences in the spectral drifts at two wavelength locations (1000 and 1800 nm). Did you conduct any correction?

2.4 Data analysis
Did you divide the dataset into training data, which was used for generating regression models, and validation data, which was used for assessing generalization error? 

3.1 LCC distribution in the wheat canopy
LL.184-185
Did you find the significant differences?

Figure 2.
The caption and the axis labels should be modified.

LL.199-201
Were these correlations significant?

You can show the relationships between chlorophyll-a and b. 
Were the chlorophyll-a to b ratios approximately three?

3.4 Correlation analysis between LCC and vegetation indices
You said the VZA ranged from 0 to +60 degree at intervals of 10 degree.
The x axis of Figure 3 is wrong.

There is no discussion, with physical interpretation of the results, and with a comparison with existing results in the literature. This should be added in the paper.

Author Response

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Round 2

Reviewer 3 Report

Although the authors improved the manuscript, there are some issues the authors may need to address in the revision.

1. Introduction
LL.175-177
Reference is missing.

2.4 Data analysis
Did you repeat the random-sampling procedure? It should be better for more robust conclusions.

4. Discussion
L.725
Could you clarify 'many factors'?

LL.741-744
You should have given more details on the northern China standards.
What characterizes patterns compared with those of other regions?

LL.744-747
Could you clarify the stratification method in previous studies?
Reference is missing.