Monitoring Grassland Variation in a Typical Area of the Qinghai Lake Basin Using 30 m Annual Maximum NDVI Data

Round 1

Reviewer 1 Report

The research is innovative and has technical-scientific merit that qualifies it for publication. Only a few points should be further clarified for reader understanding. Regarding image fusion, it is suggested to detail the procedure in a little more detail in the text. Another point refers to the use of images from only two or three dates per year. Justify why only these dates are used. Wouldn't it be more interesting to use more images throughout the same year to generate the adjustment curve?

Author Response

We appreciate your time and thanks for your comments concerning our manuscript entitled “Monitoring grassland variation in a typical area of the Qinghai Lake Basin using 30 m annual maximum NDVI data” (Manuscript ID: remotesensing-2852804). These comments are all valuable and very helpful for revising and improving our paper, as well as providing important guiding significance to our future research. We have gone through the manuscript and made corrections carefully according to the comments. Please see the attachment for a detailed response and the corresponding revisions/corrections highlighted in track changes in the resubmitted files.

Author Response File: Author Response.pdf

Reviewer 2 Report

The manuscript focuses on monitoring grassland variations in the Qinghai Lake Basin utilizing annual maximum NDVI data derived from 30 m spatial resolution imagery. The study proposes a novel methodology combining Landsat and MODIS NDVI data through the ESTARFM model and a logistic curve fitting to obtain accurate annual maximum NDVI values. This approach aims to overcome limitations related to spatial resolution and temporal coverage, providing a more detailed analysis of vegetation changes over time. The findings indicate significant spatial distribution characteristics and a slight increasing trend in vegetation cover from 2001 to 2022, highlighting areas of degradation and suggesting environmental factors contributing to these patterns.

General Comments:

- The study presents an innovative approach to enhancing the spatial and temporal resolution of NDVI data for monitoring grassland variations, which is crucial for understanding environmental changes in the Qinghai Lake Basin.

- The methodology appears robust, combining satellite data with advanced modeling techniques to improve upon existing NDVI datasets. However, the high plagiarism rate (36%) raises concerns about the originality of the content, which needs addressing.

- The manuscript could benefit from a deeper discussion on the implications of grassland variations for ecological conservation and land management strategies in the Qinghai Lake Basin.

Specific Comments:

- The abstract and introduction effectively set the stage for the study's significance and objectives. However, further clarification on the novelty of the methodology compared to existing approaches would strengthen the manuscript.

- The methodology section is detailed, providing clear insight into the data processing and analysis steps. It would be helpful to include more information on the validation of the model's accuracy and the potential limitations of the approach.

- The results section presents comprehensive findings on spatial and temporal vegetation patterns. Including additional analysis on the environmental and anthropogenic factors influencing these patterns could enrich the discussion.

- The discussion section effectively synthesizes the study's findings, linking them to broader ecological and management implications. Expanding on strategies for mitigating grassland degradation could further enhance the manuscript's contribution to the field.

To address the plagiarism issue, revising the manuscript to ensure all sources are properly cited and that the text provides a unique contribution to the literature is essential. Additionally, further elaboration on the study's implications for grassland management and conservation in the Qinghai Lake Basin would make a valuable addition to the discussion.

The English language quality of the manuscript is generally good, with clear expression of ideas and technical descriptions. However, to further enhance readability and ensure precision in communication, consider the following improvements:

- Review the manuscript for consistency in terminology, especially technical terms related to remote sensing and vegetation analysis, to ensure they are used consistently throughout.

- Simplify complex sentences to make them more accessible to readers not specialized in this specific field, which could involve breaking down longer sentences into shorter, more straightforward ones.

- Pay attention to the use of passive and active voice. Using active voice can make sentences clearer and more direct.

- Ensure that all figures, tables, and references are correctly cited in the text and that their relevance is explicitly stated in the manuscript's narrative.

- Consider having a native English speaker or a professional scientific editing service review the manuscript to catch subtle grammatical errors and suggest improvements in phrasing that might not be evident to non-native speakers.

Improving the English language quality will make the manuscript more accessible and engaging to a broader audience, potentially increasing its impact.

Author Response

We appreciate your time and thanks for your comments concerning our manuscript entitled “Monitoring grassland variation in a typical area of the Qinghai Lake Basin using 30 m annual maximum NDVI data” (Manuscript ID: remotesensing-2852804). These comments are all valuable and very helpful for revising and improving our paper, as well as providing important guiding significance to our future research. We have gone through the manuscript and made corrections carefully according to the comments. Please see the attachment for a detailed response and the corresponding revisions/corrections highlighted in track changes in the resubmitted files.

Author Response File: Author Response.pdf

Reviewer 3 Report

This study reconstructed the NDVI dataset with enhanced temporal and spatial resolution through data fusion, addressing the critical issue of low resolution in NDVI time series data. It enabled precise monitoring of diverse vegetation cover and fragmented landscapes at a fine scale. Furthermore, the study explored the spatiotemporal patterns and interannual variations of grasslands. The research methodology had a certain innovation, and the results substantiated the research conclusions effectively. However, the following issues require further refinement before publication, as detailed below.

1.       The main issue with this manuscript is the excessively high repetition rate. Many journals do not accept repetition rates exceeding 30% (even 20%). It is recommended to reduce the repetition rate.

2.       In this study, the total area of the study region is only 2300 km², which is less than 1/10 of a Landsat image. Using the vegetation type map at a scale of 1:1 million as the basis for vegetation classification in such a small area, the error caused by scale difference may be greater than the error reduced by model improvement.

3.       Is the study area representative as it is only part of a basin located in a basin? Can the NDVI reconstruction method developed in this area be well extended to the entire Qinghai Lake basin or even larger regions?

4.       Please modify the citation format in Line 137 to match the rest of the document..

5.       In Section 3.3, all variables should be Italics, including i^th and n.

6.       The citation of Figure 5 in the text is incorrect. Please modify it.

7.       It is recommended to add the units of DEM in Figure 5a and Figure 6.

8.       Why does the NDVI show a significant decrease in the areas on both sides of the Buha River in Figure 7, while it shows extremely stable in the CV map? Why does the significantly stable area still exhibit a remarkable decrease?

Author Response

We appreciate your time and thanks for your comments concerning our manuscript entitled “Monitoring grassland variation in a typical area of the Qinghai Lake Basin using 30 m annual maximum NDVI data” (Manuscript ID: remotesensing-2852804). These comments are all valuable and very helpful for revising and improving our paper, as well as providing important guiding significance to our future research. We have gone through the manuscript and made corrections carefully according to the comments. Please see the attachment for a detailed response and the corresponding revisions/corrections highlighted in track changes in the resubmitted files.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

The author revised the manuscript according to the reviewers' comments, and the quality of the article has been greatly improved. It is recommended to accept it for publication.

The following points are suggested for the author to consider:

1.       In order to reduce the repetition rate, the substitution words and expressions in some places affect sentence fluency. Please pay attention to coordination.

2.       In Figure 6, DEM legend does not need to add m after the number, just add (m) after the topmost DEM.