Review Reports - Central Place Theory Based on Mobile Signal Data: The Case of Urban Parks in Beijing and Changsha

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This research examines the hierarchical structure of urban parks using Central Place Theory (CPT) and mobile signaling data from Beijing and Changsha. It analyzes how parks function as central places by identifying their service areas, visitor distribution, and dominant influence areas (DIA). The study explores key factors influencing park hierarchy, such as size, infrastructure, and location, revealing notable differences between the two cities. Findings provide theoretical and practical insights for urban planners to enhance park accessibility, spatial planning, and social equity in public recreational spaces. The chosen research topic is highly compelling; however, the following points need to be addressed to further improve the quality of the work.

Abstract

The abstract is well-structured, but it could be more concise. Reducing long-windedness while keeping key findings intact would enhance readability.

Clearly state the research gap before introducing the methodology and findings.

Consider explicitly mentioning the implications of the findings in urban park planning and policy-making.

Introduction

The introduction does a good job of explaining Central Place Theory (CPT) and its relevance, but it would benefit from a stronger statement of the research problem.

More emphasis should be placed on why urban parks are an important subject for CPT analysis, specifically in the context of Beijing and Changsha.

The transition between general CPT principles and the research objectives could be smoother.

Add a clearer research question or hypothesis to guide the reader through the study.

Materials and Methods

The study area description is detailed, but a comparative justification for selecting Beijing and Changsha should be added (Examples: differences in urban development, park planning strategies).

The section on mobile signaling data should include a discussion on potential limitations, such as data biases or missing data issues.

Clarify the classification method used for dominant influence areas (DIA) and the threshold for defining service areas.

Provide additional details on the logistic regression model, including any validation steps or robustness checks performed.

Results

The hierarchical classification of parks is insightful, but the description of results is somewhat dense. Consider using more visual aids (tables or figures) to summarize key findings.

Statistical significance values for key results should be highlighted more clearly to reinforce credibility.

Some subsections lack explicit transitions, making it hard to follow the logical flow of findings.

Consider adding a summary paragraph at the end of this section to reinforce the major takeaways.

Discussion

The discussion should more explicitly connect findings to the broader literature, reinforcing how the study advances CPT in the context of urban parks.

The section comparing Beijing and Changsha is insightful, but it could be expanded to discuss policy implications for different types of cities.

Address potential limitations of the study in more depth, such as challenges in data interpretation or external factors influencing park usage (Examples: cultural preferences, economic conditions).

Conclusion

It would be helpful to include a paragraph explicitly outlining recommendations for policymakers or urban planners.

The last sentences should clearly articulate how future research can expand on this study (Examples: incorporating multi-source data, exploring different city typologies).

Comments on the Quality of English Language

The English could be improved to express the research more clearly.

Author Response

Comments 1: The abstract is well-structured, but it could be more concise. Reducing long-windedness while keeping key findings intact would enhance readability.
response 1: Thank you for your comments. We have streamlined the abstract by removing redundant text and improving its overall clarity. Please refer to the manuscript for details—we have retained all revision marks.

Comments 2: Clearly state the research gap before introducing the methodology and findings.
Response 2: Thank you for your comments. We have added the following content to our abstract to highlight the research gap.
"Most studies on central places focus on urban commercial facilities, hHowever, it re-mains unclear whether parks exhibit characteristics of central places, what features their service areas and hierarchical structures possess, and what factors influence these characteristics."

Comments 3: Consider explicitly mentioning the implications of the findings in urban park planning and policy-making.
Response 3: Thank you for your comments. We have added content to the abstract to explicitly highlight the implications of our findings for park planning and policy-making.
"These conclusions provide important theoretical support for government officials to better understand the characteristics of park services and offer practical guidance for optimizing urban park planning, enhancing service efficiency, and formulating policies that promote equitable access to green spaces."

Comments 4: The introduction does a good job of explaining Central Place Theory (CPT) and its relevance, but it would benefit from a stronger statement of the research problem.
Response 4: Thank you for your comments. We have given considerable thought to the research problem and have rewritten it in a clearer and more explicit manner. The revised content is as follows:
"Our study focuses on two key research questions. First, how can mobile signaling data be used to delineate park service areas and intensities, and further analyze the central place hierarchy of urban parks? Second, what are the key factors influencing the formation of this hierarchy? Additionally, we compare the differences between cities of different scales."

Comments 5: More emphasis should be placed on why urban parks are an important subject for CPT analysis, specifically in the context of Beijing and Changsha.
Response 5: Thank you for your suggestion. We fully agree with your point. We have made two additions to address this.

Firstly, we have added the following content to the introduction section:
"The CPT emphasizes hierarchical structures and service areas, which are directly related to the equity and efficiency of urban parks in serving residents. Therefore, an in-depth analysis of the park's service area and Their CPT patterns areis of great practical im-portance in understanding the rationality of the park's spatial pattern for serving resi-dents."

Secondly, in the methods section, specifically in the research area part, we have provided a detailed explanation of the reasons for selecting Beijing and Changsha.

Comments 6: The transition between general CPT principles and the research objectives could be smoother.
Response 6: Thank you for your comments. The core principles of Central Place Theory (CPT) are centrality and hierarchy, both of which rely on service area and intensity as the foundation for analysis. After careful consideration, we have explicitly clarified the relationship between the principles of CPT and service areas, which naturally leads to the research objectives, ensuring a smoother and more logical flow. The full content is as follows:
"Obtaining service areas and intensity is a fundamental step in analyzing CPT pat-terns. Mobile signaling data from urban park visitors provides an objective means to capture both aspects simultaneously. Based on this, our study focuses on two key re-search questions. First, how can mobile signaling data be used to delineate park service areas and intensities, and further analyze the central place hierarchy of urban parks? Second, what are the key factors influencing the formation of this hierarchy? Addi-tionally, we compare the differences between cities of different scales."

Comments 7: Add a clearer research question or hypothesis to guide the reader through the study.
Response 7: Thank you for your comments. As mentioned in comments 4, we have reorganized the research problem. The revised content is as follows:
"Our study focuses on two key research questions. First, how can mobile signaling data be used to delineate park service areas and intensities, and further analyze the central place hierarchy of urban parks? Second, what are the key factors influencing the formation of this hierarchy? Additionally, we compare the differences between cities of different scales."

Comments 8: The study area description is detailed, but a comparative justification for selecting Beijing and Changsha should be added (Examples: differences in urban development, park planning strategies).
Response 8: Thank you for your comments. We very much agree with you that highlighting the differences in urban planning and park development policies between Beijing and Changsha will better help readers understand why we chose these two cities as study areas, and we have added the following:
"Apart from differences in urban development patterns, economic scale, and pop-ulation size, Beijing and Changsha also differ in their park development strategies and geographic characteristics. Beijing prioritizes the development of a “Park City”, em-phasizing the integration of ecology and urban life to create a livable environment. In addition to serving as spaces for recreation and leisure, Beijing’s parks also play essen-tial roles in ecological conservation and cultural heritage preservation [23]. integrates natural landscapes and ecological green spaces to form the green framework of a mod-ern mountain-water city, developing an urban green space system that combines riverfront and roadside green belts [24]. Furthermore, Beijing, a representative northern city, has a temperate monsoon climate, whereas Changsha, a southern city, experiences a subtropical monsoon climate with hot, humid summers and diverse park vegetation. These differences in climate, geography, and park landscapes provide a valuable com-parative perspective on how CPT patterns align with urban parks. "

Comments 9: The section on mobile signaling data should include a discussion on potential limitations, such as data biases or missing data issues.
Response 9: Thank you for your comments. While cellular signaling data has many advantages, it also has many limitations, such as the singularity of attributes and the bias of sampling. We agree with you that this part of the discussion is important, but it would be more informative to expand on it, so we have described it in detail in the discussion section of the paper.

Comments 10: Clarify the classification method used for dominant influence areas (DIA) and the threshold for defining service areas.
Response 10: Thank you for your comments. Indeed, as you mentioned, we were too concise in introducing the concept of DIA, which is one of the core elements of this study. Therefore, we have added two formulas with related descriptions to explain the concept of DIA as well as the calculation process. The details are as follows:
"P_g=arg 〖max〗_p K_p (x_g,y_g ) (1)
〖DIA〗_p= {g∈G | P_g=p} (2)
The service areas of different parks significantly overlap in space, meaning that residents in these areas can benefit from the services provided by multiple parks. To differentiate this service intensity, we defined "park service advantage areas." For each analysis grid g, different residents within the grid K_p (x_g,y_g ) may choose to visit different parks. We defined the park visited by most residents within the grid P_g as the dominant influence area (DIA)（DIA）. Based on this, we delineated the DIA for all parks and also delineated the service areas for each type of advantage park."

Comments 11: Provide additional details on the logistic regression model, including any validation steps or robustness checks performed.
Response 11: Thank you for your comments. We've added the following to elaborate on the details of logistic regression:
"The independent variables in the logistic regression model are the park attribute char-acteristics, while the dependent variable is the park's classification level. For model evaluation, we used precision, recall, and F1-score to assess classification performance. These metrics provide a comprehensive evaluation of the model’s predictive capability, with F1-score balancing precision and recall. Additionally, we performed binary classi-fication significance tests on category distinctions using P-values. This ensured that the classification was statistically meaningful and that the model effectively captured differences among park categories."

Comments 12: The hierarchical classification of parks is insightful, but the description of results is somewhat dense. Consider using more visual aids (tables or figures) to summarize key findings.
Response 12: Thank you for your comments. Our description of the conclusions is too lengthy, and in fact some of the content could really be made more readable in the form of graphs and charts. Therefore, we have added two subfigures to Figures 4 and 6, respectively. These two subfigures contain descriptions of the statistical information for each class of park. Details can be found in the manuscript.

Comments 13: Statistical significance values for key results should be highlighted more clearly to reinforce credibility.
Response 13: Thank you for your comments. P-value is a key parameter in the significance test of the model, although our study lists the p-value values in detail in the form of a table, but there is no highlighting of the influencing factors that passed the test, and we have highlighted the font color in Figures 8 and 9 to make it easier for readers to find the relevant information directly.

Comments 14: Some subsections lack explicit transitions, making it hard to follow the logical flow of findings.
Response 14: Thank you for your comments. We have added the following between subsection 3.1 and subsection 3.2 to make it easier for the reader to understand the logic between the two.
"In the previous subsection, we examined the service level distribution of parks in two cities. This classification may be influenced by the inherent attributes of the parks. Therefore, it is necessary to further analyze the potential influencing factors and their statistical significance."

Comments 15: Consider adding a summary paragraph at the end of this section to reinforce the major takeaways.
Response 15: Thank you for your comments. We have added the following as a summary of this section:
"In summary, our analysis highlights CPT patterns in park service areas, visitor density, and influencing factors across different hierarchical levels in Beijing and Changsha. The classification of parks into three levels reveals that a small number of large parks dominate service provision in both cities. The service intensity analysis in-dicates that higher-tier parks do not always maintain the highest visitor densities, as proximity and local competition significantly affect park usage. The logistic regression results suggest that in Beijing, individual park attributes have limited influence on ser-vice hierarchy, with only cultural heritage sites showing a statistically significant cor-relation. However, in Changsha, park area and infrastructure play a more substantial role in determining park classification. Further factor analysis demonstrates that visitor density and service areas are influenced by different attributes depending on each level. Overall, our findings emphasize the complex interplay between park attributes, spatial distribution, and service intensity."

Comments 16: The discussion should more explicitly connect findings to the broader literature, reinforcing how the study advances CPT in the context of urban parks.
Response 16: Thank you for your comments. The discussion section of our article has been supplemented as follows:
" In fact, this irreplaceability extends beyond urban parks. Recent studies have begun to explore the concept of "irreplaceability" in urban geography[40,41], which is often closely linked to the high demand for certain facilities and their limited availability[42]."

Comments 17: The section comparing Beijing and Changsha is insightful, but it could be expanded to discuss policy implications for different types of cities.
Response 17: Thank you for your comments. We have provided a detailed description of the differences between the centerland patterns of urban parks in the two cities with respect to urban planning policies, as described below:
"Although urban parks in both Beijing and Changsha align with the hierarchical structure of the Central Place Theory (CPT) model, they exhibit notable differences. In Beijing, first-tier parks are primarily dominated by major parks such as Olympic Forest Park and Chaoyang Park, with a relatively large DIA. In contrast, first-tier parks in Changsha are more fragmented. This discrepancy is likely closely related to urban planning and land use policies.
For instance, Beijing's urban planning emphasizes functional zoning, with the central district primarily serving administrative functions[18]. As a result, large parks are concentrated in specific areas and play a significant role in providing ecological and recreational services. This has led to a tendency for urban residents to gravitate toward certain major parks. In comparison, Changsha’s urban expansion has been more balanced, featuring a greater number of small and medium-sized parks distributed throughout the city. Additionally, due to differences in population scale, Changsha does not have residential communities exceeding 300,000 residents as seen in Beijing. Two super-large residential communities, Huilongguan and Tiantongyuan in Beijing, are respectively covered by DIA of Olympic Forest Park and Chaoyang Park, despite the considerable distance between them. Consequently, the spatial distribution of first-tier parks' DIA differs significantly between the two cities."

Comments 18: Address potential limitations of the study in more depth, such as challenges in data interpretation or external factors influencing park usage (Examples: cultural preferences, economic conditions).
Response 18: Thank you for your comments. An extended discussion and literature conversation on other factors that may influence the urban park centerland model is as follows:
"In addition to the 6 factors considered in this study, other elements, such as ticket prices, park reputationpopularity, and transportation accessibility[16,46,47], need to be quantified. Existing studies have begun to focus on the influence of external factors on park service areas. Research by Gou et al., based on mobile signaling data, indicates that population density and the number of commercial facilities significantly impact park service areas[16]. Furthermore, factors like human mobility characteristics and travel habits may also play a decisive role. Integrating park characteristics with external fac-tors in a systematic way is essential for a more comprehensive understanding of the CPT model in parks. This is also a key aspect that this study aims to refine."

Comments 19: It would be helpful to include a paragraph explicitly outlining recommendations for policymakers or urban planners.
Response 19: Thank you for your comments. We have written a separate paragraph in the conclusion section to explain how our research supports policymakers or urban planners.
"Our findings provide valuable insights for urban planning and park management. To enhance the efficiency and accessibility of urban parks, planners should consider both park attributes and external urban factors in decision-making. A well-structured park system can promote spatial equity by ensuring that recreational opportunities are not concentrated in a few high-level parks but are accessible to diverse urban popula-tions. Additionally, improving connectivity between parks and surrounding urban areas can enhance residents' travel convenience and optimize park utilization. By integrating data-driven approaches and comprehensive spatial planning, policymakers can create a more balanced and sustainable urban park network that better serves public needs. "

Comments 20: The last sentences should clearly articulate how future research can expand on this study (Examples: incorporating multi-source data, exploring different city typologies).
Response 20: Thank you for your comments. Our manuscript concludes with the addition of HOW future research can expand on this study, as described below:
"Future research will consider incorporating additional factors that may influence the CPT patterns of urban parks. Additionally, by expanding data types and refining the specific purposes of recreational services, we aim to provide a deeper understanding of the CPT patterns in urban parks."

Comments 21: The English could be improved to express the research more clearly.
Response 21: Thank you for your comments. We have carefully reviewed the entire manuscript and revised any unclear or non-standard expressions to improve readability. All changes have been tracked in the manuscript.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

The research conducted on the topic of analyzing the central place theory through mobile signal data taken on the case of urban parks is interesting and valuable for two reasons. The first is the rigorously conducted and presented methodological chain, and the second is the actual content, i.e. the urban park as an important central activity of the city.

The research gap that has been found indicates a huge potential for both, positioning the urban park as an active and key actor in processes of urban planning and regeneration strategies, especially nowadays in the context of eco/social responsibility, and for the comeback a valuable theory that can be efficiently used through mobile technology support.

The question of benefits is fully explained and very well presented.

The methodology used and references cited are up to date, and the manuscript is scientifically sound and clear.

The most important contribution, in my opinion, is the variety of results that can be observed and concluded as a result of the analysis.

However, there are two small comments.

The first is of a structural nature. In my opinion, everything you have written in the conclusion must be in the discussion and vice versa. The discussion part is for closing remarks. To explain on this; Discussion should provide information directly coming from the analyses and directly related to the main content, which is urban park in this article i.e. research. Conclusion should serve to remark on the proposed methodology, overall general concluding remarks, problems during research, future possibilities and obstacles and potential in general, not directly in connection with urban parks nor selected cities.

The second is the fact that, probably only by chance, you omitted to add a few sentences between lines 66 and 68 on the distinguishing features of commercial centers, as for the reader to be fully capable of comparing the two.

Apart from these minor comments, I would suggest a title change

Central Place Theory Based on Mobile Signal Data: The Case of Urban Parks in Beijing and Changsha

In this way, the focus is on the research methodology, which is the core of the article, and the fact that it can be applied to other topics is more visible and directly communicated.

Author Response

Comments 1: The first is of a structural nature. In my opinion, everything you have written in the conclusion must be in the discussion and vice versa. The discussion part is for closing remarks. To explain on this; Discussion should provide information directly coming from the analyses and directly related to the main content, which is urban park in this article i.e. research. Conclusion should serve to remark on the proposed methodology, overall general concluding remarks, problems during research, future possibilities and obstacles and potential in general, not directly in connection with urban parks nor selected cities.

Response 1: Thank you for your comments. Your comments were very informative and greatly improved the manuscript. We have organized the main findings in detail and have added the following additions to the discussion section:

"We also found that when parks provide services to residents, they still adhere to core concepts of Central Place Theory, such as "hierarchy" and "centrality," exhibiting characteristics where the higher the level, the fewer the park countnumber. Urban parks exhibit a hierarchical effect when serving residents, which can be simply understood as the phenomenon where, regardless of how close a park is to a residential area, its number of visitors may still be dominated by a larger, more distant park, thereby es-tablishing the irreplaceability of the larger park. For example, Olympic Forest Park of-fers a full 10 km of plastic running path, which most other parks do not have. Fur-thermore, the hierarchical phenomenon determined by park visitor numbers does not align with the government’s planned park types. For example, Taoranting Park and Temple of Heaven are both classified as historical and cultural parks by the government, but they belong to Level-1 and Level-2, respectively. In fact, this irreplaceability extends beyond urban parks. Recent studies have begun to explore the concept of "irreplacea-bility" in urban geography[40,41], which is often closely linked to the high demand for certain facilities and their limited availability[42]."
"Although urban parks in both Beijing and Changsha align with the hierarchical structure of the Central Place Theory (CPT) model, they exhibit notable differences. In Beijing, first-tier parks are primarily dominated by major parks such as Olympic Forest Park and Chaoyang Park, with a relatively large DIA. In contrast, first-tier parks in Changsha are more fragmented. This discrepancy is likely closely related to urban planning and land use policies.
For instance, Beijing's urban planning emphasizes functional zoning, with the central district primarily serving administrative functions[18]. As a result, large parks are concentrated in specific areas and play a significant role in providing ecological and recreational services. This has led to a tendency for urban residents to gravitate toward certain major parks. In comparison, Changsha’s urban expansion has been more bal-anced, featuring a greater number of small and medium-sized parks distributed throughout the city. Additionally, due to differences in population scale, Changsha does not have residential communities exceeding 300,000 residents as seen in Beijing. Two super-large residential communities, Huilongguan and Tiantongyuan in Beijing, are respectively covered by DIA of Olympic Forest Park and Chaoyang Park, despite the considerable distance between them. Consequently, the spatial distribution of first-tier parks' DIA differs significantly between the two cities."
"In addition to the 6 factors considered in this study, other elements, such as ticket prices, park reputationpopularity, and transportation accessibility[16,46,47], need to be quantified. Existing studies have begun to focus on the influence of external factors on park service areas. Research by Gou et al., based on mobile signaling data, indicates that population density and the number of commercial facilities significantly impact park service areas[16]. Furthermore, factors like human mobility characteristics and travel habits may also play a decisive role. Integrating park characteristics with external fac-tors in a systematic way is essential for a more comprehensive understanding of the CPT model in parks. This is also a key aspect that this study aims to refine.Given the com-plexity introduced by these factors, large models may offer a suitable solution for pre-dicting park service areas, an area we plan to explore in future research."

We rewrite the conclusion section.

"The primary objective of this study was to analyze the CPT patterns of urban parks. Using mobile signaling data as the core dataset, we delineated the service areas of urban parks in Beijing and Changsha and subsequently derived the DIA. Based on the DIA, we assessed the centrality and hierarchy of urban parks. Finally, we examined the factors influencing park hierarchy and the determinants of service area variations across dif-ferent park levels. The key findings are as follows:
First, urban parks in both cities exhibit clear centrality and hierarchical structures, with the number of parks increasing as their hierarchical level decreases. Level 1 parks are the least numerous but exhibit the highest centrality. Most Level-1 parks have a larger and more intense service area than Level-2 parks. However, Beijing has fewer Level-1 parks than Changsha, and the top-ranked Level 1 parks in Beijing serve signif-icantly larger areas than those in Changsha. This suggests that the DIA in Changsha is more fragmented. Additionally, the visitor density decay curves indicate that the rate at which service intensity declines with distance varies across parks, reflecting differen-tiation among them.
Second, the factors influencing park hierarchy differ between the two cities. In Changsha, park size and infrastructure are significant determinants of park hierarchy, whereas these factors do not exhibit statistical significance in Beijing. Similarly, the factors affecting park service areas and visitor numbers vary between the two cities. This finding suggests that the physical characteristics of parks influencing residents' access to park services are not consistent across different urban contexts.This study, based on mobile signaling data, provided an in-depth analysis of the service areas, DIAs, and CPT’s hierarchical structure of various types of parks in Beijing. It also explored the relationships between park visitor numbers, service areas, and park characteristics. The main conclusions are as follows:
Firstly, there is a clear hierarchical structure in the visitation of parks by residents in Beijing Changsha. The results show that parks such as Olympic Forest Park, Chao-yang Park, and Old Summer Palace are positioned at the top of the hierarchy. These parks not only attract a large number of local visitors but also have a significant coverage effect on parks in lower levels. In contrast, Level-2&3 parks, such as Temple of Heaven, Haidian Park, and Yangshan Park, although attractive within certain areas, have their service ranges and visitor numbers covered and dispersed by the upper-level parks. This hierarchical structure reflects the centrality and hierarchy of parks within urban recre-ational spaces, aligning with the basic assumptions of CPT.
Next, we analyzed the impact of park attributes on the park's CPT model. However, the two cities show significant differences. In analyzing the factors influencing cen-trality and hierarchy, we found that potential factors such as park area and infrastruc-ture correlated with park visitation numbers and DIA. However, the correlation of in-dividual factors is weak, indicating that the process through which citizens enjoy park recreational services is quite complex. Relying solely on park attributes may make it difficult to quantitatively assess their impact. Therefore, it is recommended to incor-porate additional feature dimensions to better characterize the central place attributes of parks.
Our findings of urban parks’ CPT patterns provide valuable insights for urban planning and park management. To enhance the efficiency and accessibility of urban parks, planners should consider both park attributes and external urban factors in de-cision-making. A well-structured park system can promote spatial equity by ensuring that recreational opportunities are not concentrated in a few high-level parks but are accessible to diverse urban populations. Additionally, improving connectivity between parks and surrounding urban areas can enhance residents' travel convenience and op-timize park utilization. By integrating data-driven approaches and comprehensive spa-tial planning, policymakers can create a more balanced and sustainable urban park network that better serves public needs.
Additionally, we found that the factors influencing urban park services and their CPT patterns are highly complex. Therefore, future research will consider incorporating additional factors that may influence the CPT patterns of urban parks. Additionally, by expanding data types and refining the specific purposes of recreational services, we aim to provide a deeper understanding of the CPT patterns in urban parks.In summary, this study reveals the hierarchical structure and service characteristics of parks within urban recreational spaces by analyzing the service areas and influencing factors of parks in Beijing. It explores the CPT mode of parks when providing recreational services to residents. The findings not only offer a new perspective for applying traditional CPT to urban parks but also provide guiding recommendations for park development and management. Our future research could further integrate various types of data and complex feature dimensions with advanced models to accurately characterize the cen-trality and hierarchical characteristics of urban parks, thereby offering more compre-hensive theoretical support and practical guidance for optimizing and sustainably de-veloping urban park systems."

Comments 2: The second is the fact that, probably only by chance, you omitted to add a few sentences between lines 66 and 68 on the distinguishing features of commercial centers, as for the reader to be fully capable of comparing the two.

Response 2: Thank you for your comments. It is true that the factors influencing the construction of commercial facilities were omitted here, and we have made corresponding additions as well as relevant literature.

" The location of commercial centers is primarily influenced by factors such as popula-tion density, transportation accessibility, and economic vitality et al[48–50]"

Comments 3: I would suggest a title change.
"Central Place Theory Based on Mobile Signal Data: The Case of Urban Parks in Beijing and Changsha"

Response 3: Thank you for your suggestion. After our thoughtful consideration, we have decided to adopt your suggestion.