Urban Morphology Influencing the Urban Heat Island in the High-Density City of Xi’an Based on the Local Climate Zone

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The issues brought in this paper are very contemporary, since UHI is a concern worldwide. The paper is well written and minor revisions are required.

*There are a lot of acronyms used in this paper. It would be interesting create a list.

*Why your research only considered six urban morphology factors?

*The quality of Figure 2 could be improved. As it is, it is not possible to read the captions of the map.

*How will you justify your model is better than the previous studies? What are the advantages offered?

*What were the main gaps/novelty your research covered?

 

Comments on the Quality of English Language

Small typos.

Author Response

*1. There are a lot of acronyms used in this paper. It would be interesting create a list.

Response: Thank you for your suggestion. In order to keep the writing concise, this article did use a lot of acronyms, which have been created the Abbreviations table in the Appendix section.

More detailed can be seen in Line 690

 

*2. Why your research only considered six urban morphology factors?

Response: We have added relevant explanations on the selection of urban morphology factors in the article.

Revised: General UHI intensity is determined by meteorological factors (e.g., relative humidity, solar radiation, and wind velocity) and urban morphology factors (e.g., sky view factor, building configuration, land cover type, and surface material albedo). The urban morphology factors include six major aspects: Urban Tissue Con-figuration, Street Network, Building-Plot Characteristics, Land Use, Natural Features, and Urban Growth. Urban morphology plays a crucial role in driving the UHI effect, as various studies have highlighted. Therefore, we selected the six major urban spatial morphology factors (BD, BH, FVC, ISF, SVF, FAR) that have appeared frequently in previous studies, and these factors have also been proven to have a correlation with LST. At the same time, in Xi'an, these factors are relatively simple to obtain and have high accuracy.

More detailed can be seen form line 67 to line 73 and line 84 to line 87.

 

*3.The quality of Figure 2 could be improved. As it is, it is not possible to read the captions of the map.

Response: Thank you for your suggestion. We have improved the LCZ identification flowchart

More detailed can be seen in Line 221

 

*4.How will you justify your model is better than the previous studies? What are the advantages offered?

Response: The main advantage of this research model over other models lies in the use of the Pearson model under scale optimization, which improves the transferability of the research conclusions.

Most previous studies started from the overall scale of the city and used the Pearson model to explore the linear relationship between UHI and related factors. However, there were few studies on the correlation between the two at the regional grid scale. Therefore, this paper introduces the local climate zone framework and divides large cities into several different LCZ regional grids, such as LCZ1 (compact high type) LCZ6 (open low type) and so on. From the regional grid scale, explore the correlation between UHI and urban spatial morphological factors. The results show that the correlation between UHI and urban spatial morphological factors is significantly different in different LCZs. And it is different from previous research results conducted at the overall urban scale. The research conclusions at the overall urban scale can only be used under the same urban environment. The research conclusions are not highly transferable, but the LCZ zoning used in this study can Conducted in various cities, in the same LCZ zone, the correlation between UHI and urban spatial morphological factors is the same, so the results of this study are highly transferable.

Therefore, the analysis results of the Pearson model under scale optimization are more conducive to guiding urban construction in different types of cities to alleviate the urban heat island effect and achieve sustainable urban development.

 

*5.What were the main gaps/novelty your research covered?

Response: We have strengthened the expression of innovation in the article.

Revised: As stated in the previous answer, The innovation of our study lies primarily in the utilization of Pearson correlation analysis to explore the correlation between various urban morphology factors and Land Surface Temperature within different Local Climate Zone partition. This addresses the shortcomings of previous research and enhances the transferability and scientific rigor of our study findings.

More detailed can be seen form line 115 to line 125.

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript (sustainability-2903292) tries to use Landsat 8 images to estimate Land Surface Temperature (LST) and employed Pearson correlation analysis to investigate the interplay between urban heat islands and six urban morphology factors: Building Density (BD), Floor Area Ratio (FAR), Building Height (BH), Fraction Vegetation Coverage (FVC), Sky View Factor (SVF), and Impervious Surface Fraction (ISF), within the framework of local climate zones. Since there exist a large number of problems, at least a Major Revision is necessary. Another severe issue is that some latest relevant research has been ignored. In particular, I have the following comments and concerns:

- 1. In the Abstract, the manuscript merely mentioned what the authors have done in this study area, and therefore I am missing the scientific questions.

- 2. From Line 74 to Line 76: the authors mentioned that "However, many existing studies have focused solely on individual urban spatial morphology factors, neglecting the combined effects of these factors on LST". However, these statements are incorrect because many studies have already done so.

- 3. The last parts of the Introduction Section should be moved to the study area section.

- 4. This paper mainly focuses on the impact of the urban form of Xi'an's four central urban areas on the urban heat island effect, which makes the results of the study possibly not fully representative of the entire city or larger region. At the same time, focusing only on four specific urban areas may ignore the different influencing factors that may exist in other areas.

- 5. Why only one year of data sets has been used in this study? And why only one scene of remote sensing images has been used?

- 6. What are the accuracies of the building height data of the open street map in China and in Xi'an?

- 7. Lack of specificity in strategic recommendations: Although the paper proposes strategic recommendations for mitigating the urban heat island effect, these recommendations are relatively general and lack specific implementation plans or specific measures. For example, how to control building density and proportion of impervious surfaces? How to appropriately increase building height and vegetation coverage? These require more specific guidance and advice.

- 8. Pearson correlation analysis is not the present state of the art techniques for analyzing the complex relationships. Non-linear methods such as the random forest models should be utilized in future studies (please refer to below research).

Exploring the connection between morphological characteristic of built-up areas and surface heat islands based on MSPA. 2024, 53: 101764

How Do the Dynamics of Urbanization Affect the Thermal Environment? A Case from an Urban Agglomeration in Lower Gangetic Plain (India). Sustainability. 2024; 16:1147

- 9. Lack of in-depth discussion: Although the paper mentioned the impact of urban form on the UHI effect, it did not delve into its internal mechanism. For example, how different urban form elements (such as building density, green space coverage, etc.) specifically affect the UHI effect.

- 10. In future research, I suggest the important influences of the morphological characteristic of built-up areas should also be taken into account, please see the above.

- 11. This study mainly focuses on urban areas. How applicable is it to other types of areas (such as rural, mountainous, etc.)?

- 12. The percent match revealed by the iThenticate report is too high (38%).

Comments on the Quality of English Language

Moderate editing of English language required.

Author Response

 Reviewer #2

*1. In the Abstract, the manuscript merely mentioned what the authors have done in this study area, and therefore I am missing the scientific questions.

Response: We have added a description of scientific issues in the abstract.

Revised: However, the influence of various urban forms on surface temperature, as viewed through the lens of regional networks, remains not fully understood.

More detailed can be seen form line 10 to line 11.

 

*2. From Line 74 to Line 76: the authors mentioned that "However, many existing studies have focused solely on individual urban spatial morphology factors, neglecting the combined effects of these factors on LST". However, these statements are incorrect because many studies have already done so.

Response: Our expression is indeed not rigorous, and we have made modifications in the introduction.

Revised: There are still shortcomings in the current research on the impact of multi factor coupling mechanisms on the UHI effect. These shortcomings limit our ability to fully understand the comprehensive impact of various urban spatial factors on surface temperature changes.

More detailed can be seen form line 80 to line 84.

 

*3. The last parts of the Introduction Section should be moved to the study area section.

Response: We have changed the article accordingly to your suggestions.

More detailed can be seen form line 153 to line 160.

 

 

*4. This paper mainly focuses on the impact of the urban form of Xi'an's four central urban areas on the urban heat island effect, which makes the results of the study possibly not fully representative of the entire city or larger region. At the same time, focusing only on four specific urban areas may ignore the different influencing factors that may exist in other areas.

Response: Our study focuses on high-density built-up areas. Therefore, the four selected areas are all relatively mature high-density built-up areas in Xi'an, with relatively stable construction conditions and more representative of high-density cities. The data is easy to obtain and the analysis results are more accurate. It is important to note that this research may not fully represent the entirety of the urban or rural areas. We acknowledge this limitation and plan to address it in future studies. Thank you for your valuable feedback.

 

*5. Why only one year of data sets has been used in this study? And why only one scene of remote sensing images has been used?

Response: We found that most relevant studies relied solely on data from only one scene of remote sensing images. (e.g., Spatial Association Rules and Thermal Environment Differentiation Evaluation of Local Climate Zone and Urban Functional Zone. Using OpenStreetMap (OSM) to enhance the classification of local climate zones in the framework of WUDAPT).Given the accelerated urbanization process in recent years in Xi'an, significant changes have occurred in urban building morphology. As our building footprint outlines and height data are from 2021, aligning urban spatial morphology with land surface temperature and considering factors such as cloud cover in remote sensing imagery and the typicality of the urban heat island effect were crucial. Therefore, Landsat 8 satellite imagery data captured on June 30, 2021, at 3:19 am was chosen for analysis.

 

*6. What are the accuracies of the building height data of the open street map in China and in Xi'an?

Response: Based on Open Street Map (OSM) data, we supplemented building outlines using 2021 Google Earth satellite imagery and utilized web scraping tools to gather information on building heights, enriching our dataset. After field validation of building heights in certain areas, the final data accuracy reached over 90%. Additionally, similar studies that utilized OSM data (Effects of Sky View Factor on Thermal Environment in Different Local Climate Zoning Building Scenarios—A Case Study of Beijing, China) provide some degree of validation for the reliability of our data. A comparison between building vector boundaries and current imagery is shown below:

 

 

 

 

*7. Lack of specificity in strategic recommendations: Although the paper proposes strategic recommendations for mitigating the urban heat island effect, these recommendations are relatively general and lack specific implementation plans or specific measures. For example, how to control building density and proportion of impervious surfaces? How to appropriately increase building height and vegetation coverage? These require more specific guidance and advice.

Response: In the mitigation strategy section, we made supplementary additions to enhance the implement ability of the strategies.

Revised: Through urban master planning, regulatory detailed planning, design guidelines, and more specific measures, we can regulate urban spatial morphology factors to make them more conducive to alleviating the urban heat island effect and maintaining urban sustainable development.

More detailed can be seen form line 601 to line 606 and line 619 to line 623.

 

*8. Pearson correlation analysis is not the present state of the art techniques for analyzing the complex relationships. Non-linear methods such as the random forest models should be utilized in future studies (please refer to below research).

Exploring the connection between morphological characteristic of built-up areas and surface heat islands based on MSPA. 2024, 53: 101764

How Do the Dynamics of Urbanization Affect the Thermal Environment? A Case from an Urban Agglomeration in Lower Gangetic Plain (India). Sustainability. 2024; 16:1147

Response: In the Conclusions section, we briefly introduced the application of linear regression and nonlinear regression in related studies, acknowledging the limitations of our research.

Revised: In the latest research, the utilization of the Random Forest model has been employed to investigate the nonlinear relationship between urban spatial morphology factors and Land Surface Temperature, confirming their nonlinear association. However, some studies still indicate a linear relationship between them. In future research, we will promptly update our research models and compare the credibility of nonlinear models (such as Random Forest) with linear models.

More detailed can be seen form line 625 to line 646.

 

*9. Lack of in-depth discussion: Although the paper mentioned the impact of urban form on the UHI effect, it did not delve into its internal mechanism. For example, how different urban form elements (such as building density, green space coverage, etc.) specifically affect the UHI effect.

Response: The paper briefly discusses the impact mechanism of urban morphology on the urban heat island effect, but the main focus is on comparing the differences in the correlation between urban spatial morphology factors and LST across different LCZs. In this revision, we have endeavored to provide a more in-depth discussion. However, further exploration of the underlying mechanisms may require the utilization of environmental simulation software such as Envi-met. We plan to conduct more comprehensive simulation studies in future research. We appreciate your valuable suggestions.

More detailed can be seen form line 491 to line 496, line 517 to line 524, line 546 to 554 and line 577 to line 591.

 

*10. In future research, I suggest the important influences of the morphological characteristic of built-up areas should also be taken into account, please see the above.

Response: In the Discussion section, we acknowledge the limitations of our study regarding the selection of characteristic factors.

Revised: The spatial factors influencing the urban heat island effect are numerous. In this study, we only selected six spatial morphology factors, which may limit the interpretation of the heat island effect. Therefore, in future research, we will endeavor to consider a wider range of characteristic factors.

More detailed can be seen form line 625 to line 646.

 

*11. This study mainly focuses on urban areas. How applicable is it to other types of areas (such as rural, mountainous, etc.)?

Response: Due to the focus of this study on high-density built-up areas, its applicability to rural and mountainous areas remains to be further investigated.

Revised: This study mainly focuses on the UHI problem in high-density built-up areas, and whether the relevant conclusions are applicable in rural and suburban areas remains to be confirmed.

More detailed can be seen form line 625 to line 646.

 

*12. The percent match revealed by the iThenticate report is too high (38%).

Response: We can assure that there is no plagiarism in this study, and we have also conducted content reduction to ensure originality.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript "Urban Morphology influencing Urban Heat Island in the High Density City of Xi'an based on the local climate zone" is an interesting take on investigating UHI and its impacts. Please find some specific comments below:

The title should not end in a period.

The introduction is lengthy and should be improved to be more succinct. Literature is good and quality of writing is good, but should be shorter.

I think suggesting strategies is a great aspect of the paper.

The discussion is likewise long and should be more succinct.

A

To answer a few questions, The references were appropriate and methodology was adequately considered. The manuscript was focused on a novel way of integrating urban form with LST to create a wholistic approach to identify impacts and causes of LAI. The paper addresses a significant need to contextualize what we can map with remote sensing through data fusion.

Comments on the Quality of English Language

English is good.

Author Response

Reviewer #3

*1. The title should not end in a period.

Response: Thank you for your suggestion. We have made the necessary modifications in the text.

More detailed can be seen form line 2.

 

*2. The introduction is lengthy and should be improved to be more succinct. Literature is good and quality of writing is good, but should be shorter.

Response: Based on your feedback, we have made some deletions to the repetitive content.

 

*2. I think suggesting strategies is a great aspect of the paper.

Response: We agree with your point of view. We have strengthened the strategy section. For an academic paper, studying scientific issues is one aspect, and more importantly, it is the mission of every researcher to explain scientific problems, solve practical problems, and achieve sustainable development of society.

*3. The discussion is likewise long and should be more succinct.

Response: Thank you for your suggestion. We have tried our best to revise the discussion section.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Although this is a revised manuscript and the authors claimed that they have improved the contents, a large number of major issues remain unsolved. In addition, this study has limited international significance. More specifically, the reviewer has the following comments and suggestions:

- . The authors claimed that: "the influence of various urban forms on surface temperature, as viewed through the lens of regional networks, remains not fully understood", which is absolutely wrong. This is because a large number of previous studies have done so. Please carefully see the comments in the first round, and many more other similar studies.

- . There are still shortcomings in the current research on the impact of multi factor coupling mechanisms on the UHI effect. What shortcomings? I cannot find the novelty in this manuscript.

- . The author only discusses the problems pointed out by the reviewers as research deficiencies without solving the problems at all. Focusing only on four specific urban areas may ignore the different influencing factors that may exist in other areas.

- . Some immature studies only use one scene of remote sensing image, which does not mean that this approach is reasonable or accurate. More scenes of remote sensing images should be used.

- . The study did not fully explore other potential influencing factors, such as wind speed, humidity, solar radiation, etc. These factors also play an important role in the formation of the urban heat island effect. Therefore, failure to fully consider these factors renders the study results incomplete and accurate.

- . Not just saying: "the final data accuracy reached over 90%". What exactly the accuracies? How to evaluate?

- . You can regulate urban spatial morphology factors to make them more conducive to alleviating the urban heat island effect and maintaining urban sustainable development. But how to do exactly?

- . The interpretation and discussion sections of the findings need further strengthening. The study did not provide in-depth analysis and explanation of these correlations. For example, why is building height positively correlated with surface temperature in some land use types and negatively correlated in others? The reasons and mechanisms behind this difference require in-depth exploration and explanation by the authors.

- . Non-linear methods such as the random forest models should be utilized.

- . The manuscript also has some problems in terms of language expression and formatting specifications. There are some paragraphs where the sentences are not smooth and the expression is not clear. The MDPI language service should be used.

- . The authors claimed that: "We can assure that there is no plagiarism in this study". This is not a negotiation. It is science!

Comments on the Quality of English Language

The manuscript also has some problems in terms of language expression and formatting specifications. There are some paragraphs where the sentences are not smooth and the expression is not clear. 

Author Response

1. The authors claimed that: "the influence of various urban forms on surface temperature, as viewed through the lens of regional networks, remains not fully understood", which is absolutely wrong. This is because a large number of previous studies have done so. Please carefully see the comments in the first round, and many more other similar studies.

Response: We carefully reviewed the comments from the first round, as well as additional similar studies, and realized that our previous viewpoint was incorrect. Many studies have indeed investigated the relationship between urban morphological factors and LST at the regional network scale. We have supplemented the explanation of this aspect in the introduction section and made corresponding modifications to the relevant parts of the text.

More detailed can be seen form line 9 to line 10 and line 92 to line 95.

 

2. There are still shortcomings in the current research on the impact of multi factor coupling mechanisms on the UHI effect. What shortcomings? I cannot find the novelty in this manuscript.

Response: We acknowledge that in the previous revision, we did not explain the "shortcomings" mentioned. In this revision, we have added a discussion on this point. The shortcomings lies in the fact that most current studies use simple or multiple linear regression models to analyze the combined effects of multiple factors on LST, which are simple and quick. However, linear models demonstrate lower accuracy and are not conducive to illustrating the complex relationships between multiple factors and LST.

[1] Diem Phan Kieu, et al." Remote sensing for urban heat island research: Progress, current issues, and perspectives." 33. (2024).

[2] Kaveh Deilami, Md. Kamruzzaman, and Yan Liu."Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures." 67.(2018):30-42.

More detailed can be seen form line 66 to line 68 and line 105 to line 108.

 

3. The author only discusses the problems pointed out by the reviewers as research deficiencies without solving the problems at all. Focusing only on four specific urban areas may ignore the different influencing factors that may exist in other areas.

Response: Thank you for your suggestion. We acknowledge that focusing solely on four specific urban areas may overlook different influencing factors that could exist in other areas. The primary aim of this study is to explore the characteristics of the urban heat island and its driving factors in high-density urban built-up areas. Therefore, we selected the four districts in Xi'an with the highest construction density and the most mature and stable construction situation. Additionally, due to limited data availability that matches the precision of our study, we ultimately chose these four areas. In future research, we will endeavor to include studies on other regions.

 

4. Some immature studies only use one scene of remote sensing image, which does not mean that this approach is reasonable or accurate. More scenes of remote sensing images should be used.

Response: We followed your suggestion and incorporated remote sensing images from August 2, 2021, in addition to those from June 30, 2021. We then performed LST retrieval on both dates and calculated the average of the two inversion results using the raster calculator tool in ArcGIS as the final LST.

More detailed can be seen form line 148 to line 149, and line 179 to line 180.

 

5. The study did not fully explore other potential influencing factors, such as wind speed, humidity, solar radiation, etc. These factors also play an important role in the formation of the urban heat island effect. Therefore, failure to fully consider these factors renders the study results incomplete and accurate.

Response: We acknowledge that changes in factors such as wind speed, humidity, and solar radiation indeed influence the urban heat island effect. We believe that urban morphological factors may also impact the heat island effect. Meanwhile, studying the influence of urban morphological factors on the heat island effect is beneficial for providing strategic recommendations for urban development. Therefore, we chose to focus on studying the correlation between urban design factors and LST. In future research, we will endeavor to expand our investigation into the impact of these factors on LST. We appreciate your valuable suggestions.

 

6. Not just saying: "the final data accuracy reached over 90%". What exactly the accuracies? How to evaluate?

Response: In terms of building quantity, we randomly generated 35 grids of 1000m × 1000m within the study area. We manually interpreted the building data within randomly generated grids using Google Earth imagery and compared the actual number of buildings with the number of buildings in the research data. The error between manual interpretation results and data sources is not significant, with an accuracy of over 90%. 

7. You can regulate urban spatial morphology factors to make them more conducive to alleviating the urban heat island effect and maintaining urban sustainable development. But how to do exactly?

Response：We referred to more relevant research and strengthened the article's specific measures to mitigate the urban heat island effect and maintain sustainable urban development, and summarized them in the following six points:

1. Green Infrastructure: Policies promoting green infrastructure, such as rain gardens, urban trees, and permeable pavement, should be encouraged to increase permeable surfaces and reduce impervious surfaces.
2. FAR Management: In densely built areas, maintaining FAR above 1.5 by managing the relationship between building footprint and height can help alleviate the urban heat island effect.
3. Compact LCZs: Planners can use "O" or "C" layouts in compact LCZs to reduce SVF, thus decreasing solar radiation received by the ground and improving microclimate comfort.
4. Open LCZs: For open LCZs, buildings should adopt "L" or "I" configurations to maximize SVF and promote vertical heat turbulence exchange, effectively decreasing LST.
5. BH Regulation: There's no fixed relationship between BH and LST for each LCZ type, suggesting the need for a reasonable range of building heights. Government regulations should incrementally raise building heights within designated limits to ensure cooling efficiency, while keeping it below 66m.
6. Regulatory Measures: Urban master planning and detailed control planning should be utilized to implement these strategies effectively.

More detailed can be seen form line 457 to line 470.

 

8. The interpretation and discussion sections of the findings need further strengthening. The study did not provide in-depth analysis and explanation of these correlations. For example, why is building height positively correlated with surface temperature in some land use types and negatively correlated in others? The reasons and mechanisms behind this difference require in-depth exploration and explanation by the authors.

Response：We utilized nonlinear analysis to reassess the correlation between LST and its driving factors. Additionally, we expanded the discussion on the correlation between LST and its driving factors in greater depth. It can be simply summarized as the following six points.

1. This study confirms negative correlation between LST and FVC, attributing it to urban vegetation's role in mitigating the UHI effect through shading and transpiration, particularly in densely populated park areas, thus enhancing cooling effects.
2. ISF and LST show a positive correlation, attributed to impermeable surfaces such as concrete and asphalt replacing soil and vegetation in urban areas, altering the urban canopy structure and reducing latent heat flux. This change increases sensible and radiation heat flux from impermeable surfaces, resulting in higher LST.
3. BD shows a positive correlation with LST, with the rate of LST increase being highest between 0.2 and 0.4 BD, stabilizing beyond 0.4. Increasing BD affects impervious surface coverage and urban wind patterns, leading to the formation of urban canyons that trap heat during the day and hinder heat release at night. However, there is a threshold effect; beyond 0.4 BD, the warming effect diminishes.
4. The relationship between FAR and LST forms an inverted U-shaped curve, peaking at an FAR of 1.5. This nonlinear relationship is attributed to the increasing heat storage volume of urban canyons and the shading effect on solar radiation as FAR increases. Below an FAR of 1.5, the heat storage effect dominates, resulting in a positive correlation, while beyond 1.5, the shading effect becomes predominant, leading to a negative correlation.
5. LST rapidly decreases within the range of 0-40m of BH, with relatively little variation observed between 40-60m. However, beyond 60m, LST shows a slight increase. This negative correlation is attributed to the shading effect of buildings, reducing solar radiation, and altering wind patterns to facilitate heat transfer. However, beyond 60 m, excessively tall buildings may disrupt wind patterns, weaken cooling effects, and potentially lead to warming due to the thermal insulation effect of urban canyons.
6. The correlation between SVF and LST: positive in compact (LCZ2-3) and open low (LCZ6) classes, and a U-shaped relationship in Open mid-rise (LCZ5) with the inflection point at 0.75-0.85. SVF represents both solar radiation reception and urban canyon cooling capacity, thus as SVF increases, more solar radiation is received, enhancing heat dissipation. The balance between these effects determines surface temperature. In LCZ2, 3, and 6, increasing SVF initially reduces LST, but beyond 0.8, increased solar radiation outweighs cooling, leading to warming. In LCZ5, high human activity areas, weak cooling at low SVF leads to higher LST, but as SVF increases, cooling strengthens, resulting in a negative correlation. Yet, beyond 0.8, substantial solar radiation and artificial heat lead to a positive correlation, with LST surpassing other LCZs with similar SVF.

More detailed can be seen form line 383 to line 385, line 393 to line 406, line 410 to line 420, and line 432 to line 448.

 

9. Non-linear methods such as the random forest models should be utilized.

Response: Following your suggestion, we utilized a random forest model to study the nonlinear relationships between LST and its driving factors. Comparing with previous Pearson analysis, there are some overlapping conclusions. However, nonlinear analysis can exhibit more complex nonlinear relationships. Therefore, we modified the research methodology to nonlinear analysis methods.

More detailed can be seen form line 105 to line 121, and line 240 to line 251.

 

10. The authors claimed that: "We can assure that there is no plagiarism in this study". This is not a negotiation. It is science!

Response: We have revised the article to reduce redundancy.

 

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

I have no other comments except for the language.

Comments on the Quality of English Language

Moderate editing of English language required.

Author Response

We had modified the English language.