A New Large-Scale Monitoring Index of Desertification Based on Kernel Normalized Difference Vegetation Index and Feature Space Model

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

    Based on the KNDVI-Albedo remote sensing monitoring model of point-line mode, the authors analyzed and revealed the spatiotemporal evolution pattern of desertification in Gulang County from 2013 to 2023. This is an important subject, and the research results could provide important decision support for the precise monitoring and governance of regional desertification.

    Some problems need to be modified. Major Comments and Suggestions for Authors are as follows:

1.         It is important to maintain a uniform style for all map scales, as demonstrated in Figures 1, 6, and 9.

2.         It is essential to recognize the distinction between an abstract and a conclusion. Merely copying one from the other is not sufficient, as they each have unique roles to play. The conclusion is not meant to be a repetition of the abstract. The conclusion encapsulates the core findings of the study, including the objectives and methods, summarizing the results, and concluding the discussion.

 

3.         The author repeatedly mentions the superiority of the monitoring index method based on the KNDVI-feature space model. However, is it truly flawless, or are there limitations or shortcomings in the overall study? Please add the corresponding content in the discussion section.

Comments on the Quality of English Language

Minor editing of English language required.

Author Response

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Author Response File: Author Response.doc

Reviewer 2 Report

Comments and Suggestions for Authors

A new large-scale monitoring index of desertification based on KNDVI and feature space model

(1) Title: Write KNDVI in full in the title.

(2) Research Background: Please change the section's title to Introduction.

(3) Lines 116 to 122: Please clearly write the research's objectives in this paragraph.

(4) Line 141, Figure 1: Reference the map.

(5) Line 254, Figure 3: Please prepare a colored legend for this figure.

Thank you to the respected authors, the current manuscript has a good level of science and innovation, please fix the announced flaws carefully.

RESPECT

Author Response

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Author Response File: Author Response.doc

Reviewer 3 Report

Comments and Suggestions for Authors

This paper introduces a novel approach for desertification monitoring utilizing the Kernel Normalized Difference Vegetation Index (KNDVI) and feature space models. The methodology is meticulously outlined, elucidating the data origins and processing procedures, and incorporates a confusion matrix for accuracy evaluation. Results showcase the efficacy of the proposed KNDVI-Albedo feature space model in detecting and tracing desertification patterns, boasting an impressive accuracy of 94.93%. Outperforming alternative models, including those employing NDVI and MSAVI, the KNDVI model is adept at mitigating saturation issues and minimizing atmospheric and soil influences. Insights gleaned from the study shed light on the spatiotemporal evolution of desertification in Gulang County, revealing an overall improving trend characterized by a "firstly aggravation and then alleviation" pattern. Analysis of desertification gravity center shift underscores the need for heightened attention to the northeastern region in future desertification mitigation endeavors. This research furnishes invaluable data for prospective land management and ecological restoration initiatives in Gulang County and analogous environmental contexts.

General Comments:

The paper makes a significant contribution to desertification monitoring by introducing the innovative use of KNDVI in feature space models. However, it could be strengthened by conducting a more comprehensive comparative analysis with other vegetation indices, exploring the underlying mechanisms of desertification changes, and discussing the model's applicability to different regions. Additionally, improving the visualization of figures would enhance clarity and readability.

Specific Comments:

Line 107-114: Consider providing a more detailed comparison between KNDVI, NDVI, and MSAVI by quantitatively analyzing their sensitivity to vegetation changes and discussing specific limitations addressed by KNDVI.

Line 156-205: Add references to original sources or key studies establishing relationships between feature parameters and desertification.

Line 239-240: Justify the selection of feature parameters for constructing the feature spaces and clarify any criteria or prior research guiding this selection.

Line 295-311: Expand the discussion of accuracy assessment by analyzing types of errors in the confusion matrix and exploring reasons for differences in accuracy between models.

Line 337: Discuss any discrepancies or nuances in findings compared to cited research on overall improvement trends.

Line 387-393: Strengthen the comparison between image classification and feature space models by providing specific examples of information captured uniquely by the feature space model.

Line 412-442: Explore the influence of specific human activities and climatic factors on desertification evolution in more detail.

Line 451-452: Reiterate specific advantages of KNDVI identified in the comparative analysis earlier in the paper.

Line 463-464: Provide examples of how research results could be utilized for precise desertification monitoring and governance.

Comments on the Quality of English Language

The language is understandable but requires moderate editing to improve clarity and flow.

Author Response

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Author Response File: Author Response.doc

Reviewer 4 Report

Comments and Suggestions for Authors

GENERAL COMMENTS

The manuscript studies the use of available satellite remote sensing based indices in evaluating desertification process. Results of the comparison of the methods seems to clarify selection process in the future applications.

Typographical inconsistency is seen in the manner references are marked, as in examples: et al.[7] constructed... et al [8]utilized... et al.[9] applied... et al[10] utilized.

On the other hand a general way of writing "had been" and "was used" instead of "has been" and "is used" may need rethinking. Even if the technology development rate is high, NDVI and KNDVI etc. may not be something belonging only to the history as "were used" seems to make one think.

COMMENTS ON DETAILS

1. Research background

a. Line 111: "it had reduce the influence"?

b. Expressions as "it was suitable" and "there had been no reports" I already mentioned in my general comments, you may need to do some smart changes in these expressions.

c. Lines 115-122: You state "The northern agro-pastoral transitional zone of Gulang County was a typical ecologically fragile area that had long been plagued by desertification". Do you mean that this is not the case anymore? On the other hand "methods such gravity center" seems to miss something.

2. Research methods and data sources

a. Lines 125-135: in the print "102km" etc. needs a space between the number and unit.

b. Line 143: in the print "OLI _ TIRS", in some articles the more common format is "OLI/TIRS".

c. Lines 151-153: "software was used to eliminate the water and building land of the three remote sensing images, and remove the water and buildings in the study area", may give a false impression that building were actually moved away, but what is the difference between images and study area if you do not mean this?

d. Line 177: "The surface albedo reflected", and some other reflections as well, you might use some other expression in these descriptions.

e. Line 189: "The size of the surface temperature" sounds strange, level may be more common, but "surface temperature" would already be enough. On the other hand continuing "was directly related to the soil moisture content" may refer to the remote sensing radiation temperature in this context? You may find relation to soil moisture content if the net radiation on similar surfaces would be equal... Perhaps you have a reference and more exact comment?

f. Table 1: Parameter "sigma" in KNDVI is left unexplained, and I do not think this is the well-known Stefan-Boltzmann coefficient, although very fundamental in remote sensing applications.

g. Lines 206-207: Temperature subscript not printed "Ta", and no vertical space before the beginning of the paragraph.

3. Results

a. Figure 6 and 7: It would be more reader friendly to write the comparison spaces to the figures directly instead of using letters and explain these in the figure text.

b. Lines 336-337: In a kind of natural environment improvement as in "desertification of Gulang County in 2023 showed a slight improvement trend", may need a human view point to be understood, you might express this in another way, perhaps.

4. Discussion

a. Line 441: "wasmore"?

 

 

Author Response

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Author Response File: Author Response.doc