Assessing Long-Term Land-Cover Dynamics Along the Presnogorkovskaya–Zhanaesil Railway Corridor (1985–2024), Kazakhstan: A Landsat NDVI Buffer-Gradient Approach for Sustainable Rail Infrastructure

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

For Lines 79–81, further clarification regarding the process of selecting the control line is needed. In particular, it should be specified to what extent the climatic conditions are comparable, with supporting data provided. A comparison of the original vegetation conditions before railway construction should also be included.

Given that multiple global databases now provide high-resolution NDVI data, the significance of the work presented in the earlier part of the paper appears limited.

After calculating the land area by category (km²) for both the control zone and the railway buffer zone, appropriate significance testing methods should be applied to determine whether the observed differences are statistically meaningful.

Regarding Lines 255–256, the analysis was conducted in Microsoft Excel with data preparation mainly carried out in ArcGIS 10.4, which is a version released more than a decade ago. Furthermore, the evaluation of annual NDVI variation under different climatic conditions relied only on relatively basic regression analysis, which weakens the overall significance and contribution of the study.

Author Response

Dear reviewer, thank you very much for your comments, please see attached our answers.

Best regards,

IMP

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1. The research topic is well motivated, and the article exploits open data to extract trends due to infrastructure.
2. Some quantitative information in the abstract would give an idea of the extent of the degradation in the proximity of the rail infrastructure.
3. How does the method support research that disentangles infrastructure’s influence from the one caused by climatic and landscape trends? This issue needs further explanations within the article.
4. The structure of the article follows the steps of the method very well.
5. Why are there n categories in Table 2? From the previous sections one understands that there is a clearly defined number of categories.
6. What do X1, X2, X3 from equation 3 represent for this particular study?
7. In figure 5 the dense vegetation areas are hard or almost not visible, which may be a problem, considering that the main difference in the evolution concerns this category.
8. In section 3.2, an example or more information regarding land cover area matrices would be useful.
9. The results include data for the control and railway areas, but the discussion from section 3.2 offers no quantitative comparison between them; therefore, the method proposed in 3.3 is welcome. I only wonder if this does not belong to the method description rather than to the interpretation of the results.
10. The resolution of Figure 7 should be improved.
11. The analysis from 3.3. covers four vegetation categories; it would be necessary to explain the reason why they were selected from all the other categories.
12. A discussion / analysis of how an area goes into a different category during time should be included.
13. A more detailed interpretation of the numerical values from Figure 7 would clarify the findings and strengthen the quantitative comparison.
14. In general, more quantitative information is necessary within comparative analysis, some important values should be extracted from the tables and figures into the text, otherwise the text only provides qualitative findings.

Author Response

Dear reviewer, please see attached our answers. Thank you for your support and help by improving our work, 

BR

IMP

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Accept in present form.

Reviewer 2 Report

Comments and Suggestions for Authors

I agree with the publication of the article in this form. My previous concerns have been properly considered.