The Impact of Land Tenure Strength on Urban Green Space Morphology: A Global Multi-City Analysis Based on Landscape Metrics
, Mingwei Xie 1, Kaili Zhang 1,*,‡ and Xiangrong Wang 1,*,‡Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis study makes a significant attempt to empirically analyze the relationship between institutions and landscapes, making a significant academic contribution to urban environmental research. However, to further enhance the rigor of the research design and interpretation, the following specific comments are offered. Specifically, more clarification and discussion are needed regarding the definition of concepts, selection of indicators, and validity of the analysis.
Keyword: It is advisable to avoid repeating keywords already included in the title. Furthermore, supplementary keywords are needed to improve the efficiency of paper retrieval and categorization.
LL69–74: Defining urban green space types (parks, forests, green areas, etc.) is a key element in data construction. Given the diversity of the countries studied, a more universal yet rigorous definition is needed, referencing major national definitions and classification systems for urban green space.
LL124–127: In the case of Russia, there is insufficient explanation regarding the interpretation of property rights intensity and data application methods. It would be beneficial to clearly describe how Russia's unique institutional conditions and data accessibility impacted the analysis.
LL145–147: The basis for defining urban peripheries as "green space exceeding 50%" is unclear. A detailed explanation is needed to determine whether this criterion is based on prior research, legislation, or empirical criteria.
LL167–171: It is unclear whether this study analyzes the form and structure of urban green spaces from the perspective of land use or land cover. Land use should be based on the legal and administrative boundaries of land units, while land cover should be based on the physical boundaries of actual vegetation. This has a significant impact on the interpretation of the analysis results.
LL187–197: The theoretical basis for the selected five landscape indicators (FRAGSTATS) and their application in urban green space analysis were not sufficiently explained. A more detailed description of how each indicator relates to the structural complexity and connectivity of urban green spaces is required.
LL233–238: It is unclear how ownership of subsurface resources relates to the physical form of urban green spaces. This study, which analyzes the structure of the land surface from a landscape ecological perspective, should be supplemented with a context that discusses the issue of subsurface resource rights.
LL239–250: Even when private land ownership is transferred, the explanation is ambiguous as to whether the land is classified as private or public based on the continuation of the use right or the initial title. The relationship between legal title and actual use needs to be clarified.
Tables 3–5: The criteria for assigning scores to each item in the composite index scoring process may appear subjective, and it is difficult to ensure objectivity in quantitative judgments solely based on the descriptions in LL214–222. Additional explanation is needed regarding the scoring criteria and weighting method for each indicator.
A clearer explanation of how the results relate to existing theoretical and empirical research is needed. In particular, a discussion highlighting the differences or contributions of this study compared to previous studies using similar variable combinations or landscape indicators is needed.
Furthermore, although country-specific scoring is a key analytical variable, there is a lack of specific interpretations demonstrating the relationship between scores and green space structure using specific country-specific examples. Selecting a few representative countries and adding qualitative explanations would enhance the reliability of the research results.
In addition to the statistical significance of correlation coefficients, further discussion is needed on their practical interpretation and policy implications. In particular, even when the correlation strength is low, the implications for institutional design should be described.
Recognition of potential sources of uncertainty that could influence the results—e.g., differences in data collection methods across countries, subjectivity of scoring criteria, and sensitivity in interpreting landscape indicators—and a description of their limitations are essential.
These are important factors that should be considered to enhance the theoretical clarity and empirical validity of this study. Future improvements are expected to further enhance the completeness of the research.
Author Response
As there seems to be a temporary problem with my submission system, I was unable to highlight the revisions directly in the response text. To make it easier to read, I’ve attached a PDF version with the changes clearly marked. I apologize for any inconvenience this may cause and appreciate your understanding.
Comments 1: Keyword: It is advisable to avoid repeating keywords already included in the title. Furthermore, supplementary keywords are needed to improve the efficiency of paper retrieval and categorization.
Response 1: Thank you for this valuable suggestion. We agree with this comment. Therefore, the keywords have been revised to avoid duplication with the title and to improve the paper’s visibility in database indexing. Two new terms—Landscape governance and Institutional diversity—were added, while redundant terms were removed.
The revised keywords can be found on page 1, lines 8–10 of the manuscript.
Comments 2: LL69–74: Defining urban green space types (parks, forests, green areas, etc.) is a key element in data construction. Given the diversity of the countries studied, a more universal yet rigorous definition is needed, referencing major national definitions and classification systems for urban green space.
Response 2: Thank you for this insightful suggestion. We agree with this comment. To enhance the conceptual rigor and international comparability of the definition, we revised the paragraph to integrate key definitions of urban green space from the World Health Organization (WHO, 2016), the European Environment Agency (EEA, 2021), and the U.S. Environmental Protection Agency (US EPA, 2019).
The revised text now clarifies that this study adopts a composite and functionalized definition, covering all artificial and natural vegetation-covered public or semi-public spaces within and around urban built-up areas, excluding bodies of water.
The changes can be found on page 3, lines 69–74 of the revised manuscript.
Comments 3: LL124–127: In the case of Russia, there is insufficient explanation regarding the interpretation of property rights intensity and data application methods. It would be beneficial to clearly describe how Russia's unique institutional conditions and data accessibility impacted the analysis.
Response 3: Thank you for this important comment. We agree with this observation. In response, we have expanded the discussion to clarify the institutional background of Russia, emphasizing the complexity of its land system transition and the challenges in establishing consistent property-rights metrics.
Specifically, we explain that due to the variability of privatization processes and inconsistencies in data collection standards, Russia’s property-rights intensity was adjusted using World Governance Indicators (WGI) to ensure comparability with other national contexts.
Comments 4: LL145–147: The basis for defining urban peripheries as "green space exceeding 50%" is unclear. A detailed explanation is needed to determine whether this criterion is based on prior research, legislation, or empirical criteria.
Response 4: Thank you for this helpful comment. We agree with this concern. The previous version did not sufficiently clarify the source of the 50% threshold for defining urban fringe areas. We have now revised the paragraph to specify that this criterion is based on the Technical Guidelines for Territorial Spatial Planning of China (2021) and empirical studies on urban development boundaries (Long et al., 2020). The definition has also been verified and corrected through manual visual inspection using OSM data. This addition improves methodological transparency and ensures that the spatial delineation aligns with established national and academic practices.
The revised text appears on page 5, lines 145–147 of the manuscript.
Comments 5: LL167–171: It is unclear whether this study analyzes the form and structure of urban green spaces from the perspective of land use or land cover. Land use should be based on the legal and administrative boundaries of land units, while land cover should be based on the physical boundaries of actual vegetation. This has a significant impact on the interpretation of the analysis results.
Response 5: Thank you for this precise and valuable comment. We agree with this observation. The previous version did not explicitly clarify the analytical basis distinguishing land use from land cover. We have revised the corresponding paragraph to explicitly state that the study adopts a functionalized land-cover approach, integrating physical vegetation cover identification with land-use attribute screening. This approach allows for cross-scale comparability while reflecting both the spatial and institutional dimensions of urban green spaces.
The revised description can be found on page 5, lines 167–171 of the manuscript.
Comments 6: LL187–197: The theoretical basis for the selected five landscape indicators (FRAGSTATS) and their application in urban green space analysis was not sufficiently explained. A more detailed description of how each indicator relates to the structural complexity and connectivity of urban green spaces is required.
Response 6: Thank you for this very constructive comment. We agree with this suggestion. To strengthen the theoretical foundation of our indicator system, we have added a clear explanation that the selected landscape metrics—patch area (AREA), perimeter–area ratio (PARA), shape index (SHAPE), fractal dimension (FRAC), and perimeter–area fractal dimension (PAFRAC)—are derived from landscape ecology theory (Forman, 1995; McGarigal et al., 2012). The revision clarifies that these indices are widely used to quantify spatial fragmentation and geometric complexity of urban landscapes. Furthermore, we specify that this study focuses exclusively on the geometric dimension of these indicators without interpreting their ecological functions.
The revisions appear on page 6, lines 187–197 of the manuscript.
Comments 7: LL233–238: It is unclear how ownership of subsurface resources relates to the physical form of urban green spaces. This study, which analyzes the structure of the land surface from a landscape ecological perspective, should be supplemented with a context that discusses the issue of subsurface resource rights.
Response 7: Thank you for this thoughtful comment. We agree with this observation. To clarify the conceptual relevance of underground resource ownership, we have revised the section to explain that this indicator functions as a proxy measure of institutional completeness, representing the legal depth of property-rights coverage in each country rather than a direct physical determinant of green-space morphology. This addition strengthens the conceptual logic linking institutional variables to landscape form while avoiding overinterpretation of causality.
The revision can be found on page 7, lines 233–238 of the manuscript.
Comments 8: LL239–250: Even when private land ownership is transferred, the explanation is ambiguous as to whether the land is classified as private or public based on the continuation of the use right or the initial title. The relationship between legal title and actual use needs to be clarified.
Response 8: Thank you for highlighting this important conceptual issue. We agree with this comment. The previous version did not sufficiently clarify whether the classification of land ownership was based on initial ownership or transferable use rights. We have revised this section to specify that statutory ownership (de jure ownership) serves as the classification criterion across national contexts, regardless of short-term leases or transferable use rights. This revision ensures consistency in cross-country comparison and avoids potential ambiguity between legal and practical ownership.
The updated passage can be found on page 7, lines 239–250 of the manuscript.
Comments 9: Tables 3–5: The criteria for assigning scores to each item in the composite index scoring process may appear subjective, and it is difficult to ensure objectivity in quantitative judgments solely based on the descriptions in LL214–222. Additional explanation is needed regarding the scoring criteria and weighting method for each indicator.
Response 9: Thank you for this detailed and constructive suggestion. We agree with this comment. To address potential subjectivity in the scoring process, we have added an explicit description of how the weight coefficients were determined through a Delphi expert consultation involving five specialists in land institutions and landscape studies.
We further note that the weighting process can be validated through the Analytic Hierarchy Process (AHP) in future research.
An explanatory note has also been added beneath Table 3 for clarity.
The revision appears on page 7–8, lines 214–222, and below Table 3 of the manuscript.
Comments 10: A clearer explanation of how the results relate to existing theoretical and empirical research is needed. In particular, a discussion highlighting the differences or contributions of this study compared to previous studies using similar variable combinations or landscape indicators is needed.
Response 10: Thank you for this valuable and constructive suggestion. We fully agree with this comment. In response, we have added a new subsection — 4.5 Comparison with Previous Studies — in the Discussion section.
This addition explicitly compares our results with existing studies, including Zhang & Li (2023) and Whiting (2022), highlighting that the key innovation of this paper lies in its cross-national analytical scale and the incorporation of institutional dimensions into landscape morphology research.
The revision can be found on page 13–14, Section 4.5 (lines 480–512) of the manuscript.
Comments 11: Furthermore, although country-specific scoring is a key analytical variable, there is a lack of specific interpretations demonstrating the relationship between scores and green space structure using specific country-specific examples. Selecting a few representative countries and adding qualitative explanations would enhance the reliability of the research results.
Response 11: Thank you for this insightful suggestion. We agree with this comment. To enhance the interpretability and credibility of our results, we have supplemented the Results section with brief qualitative descriptions of representative countries.
Specifically, we now illustrate how different property-rights intensity levels correspond to variations in green-space morphology:
Countries with high property-rights intensity (e.g., the United States, Germany, Japan) tend to exhibit smaller and more fragmented patches due to market-driven land allocation.
Countries with low property-rights intensity (e.g., China, India, Brazil) show larger and more contiguous green patches, reflecting greater state coordination in land acquisition and planning.
The added content can be found on page 11, lines 364–385 of the revised manuscript.
Comments 12: In addition to the statistical significance of correlation coefficients, further discussion is needed on their practical interpretation and policy implications. In particular, even when the correlation strength is low, the implications for institutional design should be described.
Response 12: Thank you for this thoughtful and valuable suggestion. We agree with this comment. To strengthen the interpretation of results, we have expanded the discussion to address both the practical significance of the correlations and their policy implications for institutional design.
Specifically, we clarify that even where statistical correlations are moderate or weak, the directionality of the results provides insight into how property-rights structures influence urban green-space formation through transaction costs and governance capacity. We have also summarized policy recommendations that align institutional flexibility with spatial connectivity goals.
These revisions appear in page 14–15, lines 520–548 of the revised manuscript.
Comments 13: Recognition of potential sources of uncertainty that could influence the results—e.g., differences in data collection methods across countries, subjectivity of scoring criteria, and sensitivity in interpreting landscape indicators—and a description of their limitations are essential.
Response 13: Thank you for this crucial and constructive comment. We fully agree with this observation. To address it, we have added a new subsection — 4.5 Limitations of the Study — to explicitly discuss the sources of uncertainty and potential limitations affecting the robustness of our results.
The revision identifies four main uncertainty factors:
(1) cross-country inconsistencies in data acquisition and reporting;
(2) expert-based scoring subjectivity in the composite index;
(3) scale dependence of landscape metrics; and
(4) the absence of multivariate modeling to explore interaction effects.
We emphasize that these limitations may influence the strength of correlations and the generalizability of findings, and we suggest directions for future research to address them through higher-resolution data and multiscale analytical frameworks.
The revision can be found on page 15–16, Section 4.6 (lines 550–580) of the manuscript.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsComments and Suggestions for Authors
Thank you to the journal for the invitation and to the authors for submitting this manuscript on the relationship between land tenure strength and urban green space morphology. In my view, the paper presents a relatively novel topic, exploring the influence of institutional factors on urban green space patterns at a cross-national, multi-city scale. This carries a certain degree of academic and practical significance. Moreover, the research design is relatively comprehensive, the methods are described in detail, and the results provide meaningful policy implications. However, there are still several aspects of the manuscript that require improvement and clarification:
Background and References: The introduction provides background on land tenure strength and urban green space morphology, citing studies on rural land tenure economics as well as several works on urban green space planning. Overall, the background is adequate, covering the concept of tenure strength, its role in both agricultural and urban contexts, and the importance of urban green space. Recent studies are also cited, reflecting some degree of frontier relevance. However, the following issues remain:
(a) Some cited references appear to have only limited direct relevance to land institutions or green space. I suggest the authors carefully check the appropriateness of the references to ensure that each one directly supports the argument of the paper.
(b) The introduction could more explicitly clarify how land tenure strength may affect green space morphology specifically in the urban context, and how this differs from rural situations, in order to highlight the motivation for the study.
Research Design: The study adopts a cross-national, multi-city comparative approach to analyze the effect of land tenure strength on urban green space morphology. This design is both reasonable and innovative. The selection of cities with different land tenure systems and levels of development enhances the representativeness and generalizability of the findings. Moreover, focusing on capital or major cities helps to reduce confounding effects arising from city size or hierarchy differences. The definition of study areas based on urban sprawl and green space distribution, rather than administrative boundaries, is also commendable as it better captures metropolitan realities and improves comparability. Nevertheless, several points require attention:
(a) The discussion section may be somewhat insufficient. Although the authors note that they carefully selected cities to minimize the interference of differing natural conditions, the sample spans multiple climate zones and regions. Factors such as climate, vegetation type, population density, and planning traditions may also influence green space patterns and interact with tenure systems. I suggest the authors explicitly acknowledge these potential confounders in the discussion, and explain how the study addresses them, or recommend their inclusion in future analyses.
(b) The assignment of the same national-level tenure strength value to all cities within a country simplifies the analysis, but the authors should consider whether intra-country variations in local land policies could play a role. For instance, China’s centralized land policies differ considerably from federal systems such as the United States, where land policy may vary across states. It would be advisable to mention this limitation in the discussion.
Methods: The methods are generally described in detail and with transparency. The authors clearly explain data sources and processing steps: extracting green space data from OSM, classifying 11 categories with ArcGIS, rasterizing and merging them, and calculating landscape metrics with FRAGSTATS. Furthermore, they construct a four-dimensional land tenure strength evaluation system. This framework is well grounded, with references and expert consultation providing objectivity. However, several details require clarification:
(a) The paper states that indicators are scored on a five-point scale and aggregated into an absolute score S, which is then ranked into a relative score R. Please clarify how indicator weights were determined—equal weighting or based on expert judgment? Please clarify it.
(b) There are some editing issues with tables and figures. For example, Table 1 still contains template text (“Table 1. This is a table...”), and its content appears incomplete. Such oversights should not occur. Please carefully revise the title and ensure completeness.
Results: The results are generally clear, and the main findings are sufficiently described: higher tenure strength is associated with smaller patch sizes and more complex, irregular boundaries, while overall green space coverage/connectivity shows no significant correlation. These conclusions are further explained in the discussion. Nevertheless, the results section could be improved in the following ways:
(a) The interpretation of correlation signs is somewhat confusing. For example, the authors state that the shape index (SHAPE) is negatively correlated with tenure strength, and that lower tenure strength yields larger shape index values, implying simpler shapes. However, typically higher SHAPE values indicate more complex and irregular forms. This point requires clarification to ensure consistency with theoretical expectations.
(b) The text should clearly indicate which correlations are statistically significant. At present, many results are described as trends, but significant results should be explicitly highlighted to distinguish them from non-significant tendencies.
Conclusions: The conclusions are consistent with the results and provide some practical value. The main issue, however, is the repeated use of phrases such as “validated the mechanism.” Since the study relies on correlation analysis, it does not provide strong evidence for causal mechanisms. I recommend adjusting the wording to emphasize “observed significant associations supporting the hypothesis” rather than suggesting causal proof.
Figures and Tables: Figures and tables are generally clear, but minor issues remain. For example, figure captions should not refer to figures as “tables,” and Table 1 should be revised to remove template text.
English Language Quality: The English writing is fluent, with appropriate use of technical terminology, and the overall expression is clear and coherent. It is evident that the manuscript has been carefully polished. Most sentences are correct and precise, but a few are overly long or could be phrased more concisely. Additionally, certain expressions (e.g., “the higher the property rights strength...”) appear to contain typographical errors and should be corrected.
In summary, the manuscript has a solid research foundation and is generally well written. I recommend that the authors address the above issues to strengthen the paper prior to publication.
Comments for author File: Comments.pdf
Author Response
As there seems to be a temporary problem with my submission system, I was unable to highlight the revisions directly in the response text. To make it easier to read, I’ve attached a PDF version with the changes clearly marked. I apologize for any inconvenience this may cause and appreciate your understanding.
Comments 1: Background and References: (a) Some cited references appear to have only limited direct relevance to land institutions or green space. I suggest the authors carefully check the appropriateness of the references to ensure that each one directly supports the argument of the paper.
Response 1: Thank you for this helpful and specific comment. We agree with this observation. Following the reviewer’s suggestion, we have carefully re-evaluated all references cited in the Introduction. Several references unrelated to land-tenure institutions or urban green-space studies have been removed, and all retained citations now directly support the conceptual framework and research hypotheses.
Additionally, we have replaced a few less relevant sources with recent publications (2020–2024) addressing institutional determinants of urban form, governance, and ecological planning, to strengthen the theoretical linkage between land ownership and spatial morphology.
The revisions are located on page 2–3, lines 40–74 of the manuscript.
Comments 2: Background and References: (b) The introduction could more explicitly clarify how land tenure strength may affect green space morphology specifically in the urban context, and how this differs from rural situations, in order to highlight the motivation for the study.
Response 2: Thank you for this insightful and constructive comment. We agree with this suggestion. To address it, we have strengthened the discussion of how property-rights strength specifically influences green-space morphology within urban contexts, distinguishing it from rural mechanisms.
The revised text clarifies that in cities, stronger property-rights intensity increases transaction costs and affects the configuration of green spaces through land acquisition difficulty and ownership fragmentation. In contrast, rural systems primarily affect investment incentives and agricultural productivity.
We have also emphasized the innovation of this study—quantifying the coupling relationship between institutional strength and urban green-space morphology across multiple countries, filling a research gap in the integration of institutional variables within urban form studies.
The revised text can be found on page 3, lines 80–110 of the manuscript.
Comments 3: Research Design: (a) The discussion section may be somewhat insufficient. Although the authors note that they carefully selected cities to minimize the interference of differing natural conditions, the sample spans multiple climate zones and regions. Factors such as climate, vegetation type, population density, and planning traditions may also influence green space patterns and interact with tenure systems. I suggest the authors explicitly acknowledge these potential confounders in the discussion, and explain how the study addresses them, or recommend their inclusion in future analyses.
Response 3: Thank you for this careful and valuable comment. We fully agree with this observation. We have revised the Discussion section to explicitly acknowledge and elaborate on potential confounding variables that may influence the observed relationships between property-rights intensity and green-space morphology.
Specifically, we now discuss the effects of climate zones, vegetation types, population density, and planning traditions as interacting factors that could shape urban green-space configuration. Although the study design focused on capital and major cities to minimize variability, we acknowledge that these contextual differences remain an inherent source of uncertainty.
We also suggest that future studies incorporate these factors through stratified sampling or multilevel modeling to better disentangle institutional effects from environmental and socio-demographic influences.
The revisions appear on page 13, lines 460–480 of the manuscript.
Comments 4: Research Design: (b) The assignment of the same national-level tenure strength value to all cities within a country simplifies the analysis, but the authors should consider whether intra-country variations in local land policies could play a role. For instance, China’s centralized land policies differ considerably from federal systems such as the United States, where land policy may vary across states. It would be advisable to mention this limitation in the discussion.
Response 4: Thank you for this thoughtful and important observation. We agree with this comment. To address this, we have revised the Discussion section to explicitly acknowledge the limitation of assigning a single national-level property-rights intensity value to all cities within a country.
We now note that local institutional variations—especially in large or decentralized nations such as the United States, India, and Brazil—mayas lead to intra-country differences in land governance capacity and green-space planning practices. In contrast, in more centralized systems such as China, national policy frameworks tend to dominate local land allocation mechanisms.
This clarification ensures transparency in the study’s comparative approach and suggests that future research should develop multi-scalar indicators to capture subnational diversity in property-rights systems.
The revision appears on page 13, lines 440–460 of the manuscript.
Comments 5: Methods: (a) The paper states that indicators are scored on a five-point scale and aggregated into an absolute score S, which is then ranked into a relative score R. Please clarify how indicator weights were determined—equal weighting or based on expert judgment? Please clarify it.
Response 5: Thank you for this specific and valuable question. We agree with this comment. To clarify the weighting process and strengthens the credibility of the composite index construction., we have revised the Methods section to explicitly state how the indicator weights were determined.
The revised text explains that the weight coefficients were derived through a Delphi expert consultation involving five experts in land systems and landscape ecology, rather than being equally weighted.
We have also noted that this approach reduces subjectivity by aggregating multiple rounds of expert consensus and that future research may validate these weights using the Analytic Hierarchy Process (AHP) for comparison.
The revised text can be found on page 7, lines 214–222 of the manuscript.
Comments 6: Methods: (b) There are some editing issues with tables and figures. For example, Table 1 still contains template text (“Table 1. This is a table...”), and its content appears incomplete. Such oversights should not occur. Please carefully revise the title and ensure completeness.
Response 6: Thank you for catching this oversight. We acknowledge and have corrected this issue. In the revised manuscript, all residual template text—such as This is a table and placeholder captions—has been removed.
Table 1 has been fully reformatted to align with Land journal style guidelines, with complete captions, consistent numbering, and clear variable descriptions.
We have also verified the consistency of all subsequent tables (Tables 2–5) to ensure accuracy in layout, font, and labeling.
The updated Table 1 appears on page 6, and corresponding corrections for Tables 2–5 appear on pages 8–10.
Comments 7: Results: (a) The interpretation of correlation signs is somewhat confusing. For example, the authors state that the shape index (SHAPE) is negatively correlated with tenure strength, and that lower tenure strength yields larger shape index values, implying simpler shapes. However, typically higher SHAPE values indicate more complex and irregular forms. This point requires clarification to ensure consistency with theoretical expectations.
Response 7: Thank you for this insightful comment. We acknowledge the inconsistency you identified and have revised the explanation accordingly.
In the initial draft, a transcription error occurred when the variable r (representing normalized rank for property-rights intensity) was mistakenly written as s. This caused the interpretation of the correlation sign between SHAPE and property-rights strength to appear reversed.
In the revised version, we have corrected this issue and provided a clearer explanation: the SHAPE index increases as geometries become more irregular, and the negative correlation observed indicates that stronger property-rights intensity (smaller r values) corresponds to smaller, more irregular green-space patches.
The revision appears on page 11, lines 320–345 of the manuscript.
Comments 8: Results: (b) The text should clearly indicate which correlations are statistically significant. At present, many results are described as trends, but significant results should be explicitly highlighted to distinguish them from non-significant tendencies.
Response 8: Thank you for highlighting this important point. We fully agree with this comment.
In the revised manuscript, we have explicitly stated the statistical significance threshold used in the correlation analysis and clarified which results meet or fall below this criterion. Specifically, only results with p < 0.05 are considered statistically significant, while those with p ≥ 0.05 are treated as indicative trends rather than confirmed effects.
This distinction has been added to the Results section to prevent potential misinterpretation of the correlation outcomes.
Additionally, we verified the corresponding figure and table captions (Figure 6, Tables 9–10) to ensure consistent notation of significance levels.
These clarifications are found on page 12, lines 360–378 of the revised manuscript.
Comments 9: Conclusions: The conclusions are consistent with the results and provide some practical value. The main issue, however, is the repeated use of phrases such as “validated the mechanism.” Since the study relies on correlation analysis, it does not provide strong evidence for causal mechanisms. I recommend adjusting the wording to emphasize “observed significant associations supporting the hypothesis” rather than suggesting causal proof.
Response 9: We appreciate the reviewer’s critical and precise observation. We fully acknowledge that the present study is based on correlation analysis and does not constitute a causal test of the proposed mechanism. Accordingly, all expressions implying mechanism validation have been revised to emphasize observed correlations supporting the hypothesis rather than causal confirmation.
Specifically, the phrase validated the mechanism has been replaced with supported the hypothesized relationship throughout the Discussion and Conclusion sections. Furthermore, a clarifying sentence has been added to state explicitly that this study identifies statistically significant associations rather than causal mechanisms.
These revisions are reflected on page 17, lines 512–525 of the revised manuscript.
Comments 10: Figures and Tables: Figures and tables are generally clear, but minor issues remain. For example, figure captions should not refer to figures as “tables,” and Table 1 should be revised to remove template text.
Response 10: Thank you for drawing attention to this issue. We have carefully reviewed and corrected all figure and table captions throughout the manuscript. Specifically, instances where “Table” was mistakenly used in figure titles have been corrected to “Figure,” and all remaining template text in Table 1 has been removed and replaced with the finalized descriptive content.
These corrections appear in Section 2 (Materials and Methods) and are reflected on pages 6–8, lines 150–210 of the revised manuscript.
Comments 11: English Language Quality: The English writing is fluent, with appropriate use of technical terminology, and the overall expression is clear and coherent. It is evident that the manuscript has been carefully polished. Most sentences are correct and precise, but a few are overly long or could be phrased more concisely. Additionally, certain expressions (e.g., “the higher the property rights strength...”) appear to contain typographical errors and should be corrected.
Response 11: We appreciate the reviewer’s positive evaluation and helpful advice regarding linguistic precision. We have conducted a final language check to further improve readability and consistency.
Overly long sentences were divided for clarity, while technical expressions were simplified where appropriate. The phrase “the higher the property rights strength...” has been corrected to “higher property-rights intensity” to ensure grammatical accuracy and conceptual consistency.
These language refinements have been implemented across the entire text, particularly in pages 4–5 (Introduction) and pages 15–17 (Discussion).
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThis article is a high-quality academic research with both theoretical value and practical significance. It stands out in terms of the perspective of the topic, research design, and the innovativeness of the conclusions. Using 36 cities worldwide as empirical samples, it explores the impact of land property rights intensity on urban green space morphology, providing important empirical support and decision-making references for urban green space planning and governance. However, there are some suggestions as follows:
1 Introduction, adding the related research on the other influencing factors of urban green space morphology, and the land tenure strength on urban green space morphology.
2 Table 9, Table 10. Please carefully review and make corrections.
3 Results, it is suggested to add secondary headings and supplement the relevant content,such as the impact of each land tenure strength indicator.
4 Discussion, It is suggested to make up for the deficiencies, such as the methods ...
5 Mechanism analysis can be further deepened: Although the moderating effect of macro factors such as planning policies and natural baselines on the intensity of property rights is mentioned, the degree of interference of these factors has not been quantified. Multivariate regression or hierarchical models can be used to further isolate the interaction between the intensity of property rights and other variables.
6 Research scale can be refined and extended: The current research takes the country as the evaluation unit for the intensity of property rights and fails to capture the internal property rights differences within a country (such as among different cities). High-resolution data can be combined to conduct analysis at micro scales such as communities and plots, thereby enhancing the precision of the conclusions.
Author Response
As there seems to be a temporary problem with my submission system, I was unable to highlight the revisions directly in the response text. To make it easier to read, I’ve attached a PDF version with the changes clearly marked. I apologize for any inconvenience this may cause and appreciate your understanding.
Comments 1: Introduction, adding the related research on the other influencing factors of urban green space morphology, and the land tenure strength on urban green space morphology.
Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have expanded the Introduction to synthesize additional determinants of UGS morphology (e.g., climate zones, vegetation types, population density, planning traditions) and to more clearly situate prior research on property-rights strength and urban spatial form, including recent international studies.
The change can be found on page 3, paragraph 3, lines 90–110 of the revised manuscript; related cross-references are provided in the Discussion on page 13, paragraph 2, lines 460–480.
Comments 2: Table 9, Table 10. Please carefully review and make corrections.
Response 2: Thank you for pointing this out. We agree with this comment. Therefore, we have rechecked Tables 9 and 10 for labeling, significance notation, and variable consistency. Significance thresholds are now clearly indicated (p < 0.05), and footnotes specify that p ≥ 0.05 results are interpreted as trends.
The change can be found on page 12, paragraph 1, lines 360–378; see Table 9 and Table 10 on pages 12–13.
Comments 3: Results, it is suggested to add secondary headings and supplement the relevant content,such as the impact of each land tenure strength indicator.
Response 3: Thank you for pointing this out. We agree with this comment. Therefore, we introduced four subsections in the Results—3.1 Correlation Analysis Results; 3.2 Patch-Scale Interpretation; 3.3 Country-Level Pattern Differences; 3.4 Summary of Relationships—and added concise paragraphs discussing how each component (ownership ratio, tenure duration, acquisition compensation, governance capacity) relates to UGS metrics.
The change can be found on page 10–12, paragraph 1–4, lines 300–378.
Comments 4: Discussion, It is suggested to make up for the deficiencies, such as the methods ...
Response 4: Thank you for pointing this out. We agree with this comment. Therefore, we expanded the Discussion to reflect on methodological choices and their implications, including (i) potential confounding factors, (ii) within-country heterogeneity, and (iii) scale-dependence of landscape metrics. We also clarified the rationale for using a normalized rank (r) for rights-intensity and explained significance interpretation (p < 0.05).
The change can be found on page 13–14, paragraph 1–3, lines 440–512.
Comments 5: Mechanism analysis can be further deepened: Although the moderating effect of macro factors such as planning policies and natural baselines on the intensity of property rights is mentioned, the degree of interference of these factors has not been quantified. Multivariate regression or hierarchical models can be used to further isolate the interaction between the intensity of property rights and other variables.
Response 5: Thank you for pointing this out. We agree with this comment. Therefore, we have acknowledged this analytical extension as an important next step and added a clear plan in the Limitations and Future Work section to adopt multivariate and hierarchical models to test interaction effects among institutional, environmental, and socio-demographic variables.
The change can be found on page 15–16, paragraph 1–2, lines 550–580.
Comments 6: Research scale can be refined and extended: The current research takes the country as the evaluation unit for the intensity of property rights and fails to capture the internal property rights differences within a country (such as among different cities). High-resolution data can be combined to conduct analysis at micro scales such as communities and plots, thereby enhancing the precision of the conclusions.
Response 6: Thank you for pointing this out. We agree with this comment. Therefore, we have clarified the limitation of using national-level scoring and added a forward-looking plan to extend the analysis to subnational units using high-resolution datasets at parcel/community scales, coupled with multiscale indicators of property-rights intensity.
The change can be found on page 13, paragraph 1, lines 440–460 (limitation statement) and page 16, paragraph 1, lines 565–580 (future work).
Author Response File: Author Response.pdf
Reviewer 4 Report
Comments and Suggestions for AuthorsGeneral comments:
The use of AI for document introduction is not recommended. Furthermore, what is introduced into the AI ​​may become public domain.
There are losts of double spaces along the entire manuscript.
It is recommended to insert a citation in each statement. Also, try to keep the statements to 28 words for easier reading.
Discussion section did not follows scientific style. There are no reference in that sections.
Conclusion is longer than discussion.
There is an abstract of methodology in introduction and it is not necessary.
minor concerns
L. 35-37: Words in the title should not be included in the keywords section.
L. 64 Author did not add a legal statement where they support that green spaces are surroundes by human settlements.
L.65 Authors indicated that UGS concept vary according to country but, they only state a Chinese concept.
L. 75-87: This is a very long paragraph to have only two citations. Try adding a citation before each point.
L. 88-101: In these paragraphs, you describe used methods. Move it to the summary or delete it from this section and expand it into methodology.
Figure 1: Move it to the statistical analysis section.
L. 128-131: The statement is very long. Divide it. It should not exceed 28 words before period.
Dear editor,
I am very worried bout the translation of this manuscript since authors stated in methodology that they used ChatGPT to performed it.
Author Response
As there seems to be a temporary problem with my submission system, I was unable to highlight the revisions directly in the response text. To make it easier to read, I’ve attached a PDF version with the changes clearly marked. I apologize for any inconvenience this may cause and appreciate your understanding.
Comments 1: The use of AI for document introduction is not recommended. Furthermore, what is introduced into the AI ​​may become public domain.
Response 1: We fully understand and respect the reviewer’s concern. We confirm that no part of the Introduction or any other conceptual section was generated by AI. ChatGPT 5.0 Plus (OpenAI, 2025) was used solely for language polishing under author supervision, without altering scientific content. All conceptual, analytical, and interpretative content was written and verified by the authors. Sensitive or unpublished data were never uploaded to external platforms. The revised AI statement (page 7, lines 177–180) explicitly clarifies this manuscript.
Comments 2: Table 9, Table 10. Please carefully review and make corrections.
Response 2: Thank you for pointing this out. We conducted a full-format consistency check in MS Word using “Find and Replace” for double spaces, extra paragraph marks, and irregular line spacing. The revised manuscript is now fully consistent in spacing and layout, following the MDPI Land template guidelines.
Comments 3: It is recommended to insert a citation in each statement. Also, try to keep the statements to 28 words for easier reading.
Response 3: We agree with the reviewer’s valuable suggestion. All declarative statements in the Introduction and Discussion have been verified for source citations. Missing references were added (e.g., Haase et al., 2017; Kabisch, 2019; Andersson, 2019). Additionally, sentences exceeding 28 words were revised for clarity and concision throughout the manuscript (notably pages 3–5 and 13–14).
Comments 4: Discussion section did not follows scientific style. There are no reference in that sections.
Response 4: We appreciate this observation. The Discussion section has been reorganized to follow a conventional IMRDC-style structure (4.1 Interpretation of Findings, 4.2 Comparison with Previous Studies, 4.3 Limitations and Future Work). Supporting literature has been added throughout (e.g., Zhang & Li, 2023; Whiting, 2022; Ma et al., 2024). These modifications appear on pages 13–15.
Comments 5: Conclusion is longer than discussion.
Response 5: Thank you for the constructive suggestion. The Conclusion has been condensed by approximately 35%, focusing on supported findings and avoiding repetition from the Discussion. Redundant policy examples were removed, while the main findings and implications remain clear and concise. The revised version now occupies 220–235 words (page 17, lines 600–630).
Comments 6: There is an abstract of methodology in introduction and it is not necessary.
Response 6: We agree with the reviewer’s valuable suggestion. The methodological paragraph formerly in the Introduction (lines 88–101) has been relocated to Section 2 (Materials and Methods) for improved logical flow. The Introduction now ends with a concise transition sentence directing readers to the methods section.
Comments 7: L. 35-37: Words in the title should not be included in the keywords section.
Response 7: Thank you for pointing this out. We agree with this comment. Therefore, duplicated keywords appearing in both the title and the keywords section have been removed. To improve indexing and retrieval efficiency, new terms such as Landscape governance and Institutional diversity were added.
The revision can be found on page 2, lines 35–37 of the manuscript.
Comments 8: L. 64 Author did not add a legal statement where they support that green spaces are surroundes by human settlements.
Response 8: We appreciate this comment. We have added supporting references from urban planning standards and international organizations. Specifically, we now cite the Urban Green Space and Health report (WHO, 2016) and the Urban Green Infrastructure framework (EEA, 2021), both of which define urban green spaces as natural or semi-natural areas embedded within or surrounded by built-up environments.
The revision appears on page 3, line 64.
Comments 9: L. 65 Authors indicated that UGS concept vary according to country but, they only state a Chinese concept.
Response 9: Thank you for highlighting this gap. We have expanded the definition of UGS to include comparative perspectives from international agencies such as WHO, EEA, and the US EPA (2019). This addition emphasizes the conceptual diversity across governance systems and improves cross-national comparability.
The revised text is on page 3, lines 65–75.
Comments 10: L. 75-87: This is a very long paragraph to have only two citations. Try adding a citation before each point.
Response 10: We appreciate this suggestion. Additional references have been incorporated to support each major statement within this paragraph. New citations include Haase et al. (2017), Kabisch (2019), and Andersson (2019), strengthening the theoretical linkage between governance and UGS morphology.
The revision can be found on page 4, lines 75–87.
Comments 11: L. 88-101: In these paragraphs, you describe used methods. Move it to the summary or delete it from this section and expand it into methodology.
Response 11: Thank you for pointing this out. We have relocated the methodological summary from the Introduction to Section 2 (Materials and Methods) and slightly expanded it for clarity. The Introduction now ends with a transitional sentence directing readers to the methodological framework.
The relocation appears between page 4, lines 88–101 (deleted from Introduction) and page 6, Section 2.1 (added).
Comments 12: Figure 1: Move it to the statistical analysis section.
Response 12: We agree with this comment. Figure 1 has been moved from the Introduction to Section 2.2 (“Statistical Analysis”) for better logical consistency. The figure caption has also been revised to describe the statistical framework rather than general methodology.
The updated figure appears on page 7, Section 2.2.
Comments 13: L. 128-131: The statement is very long. Divide it. It should not exceed 28 words before period.
Response 13: Thank you for the careful reading. The long sentence in lines 128–131 has been divided into two concise sentences of 22 and 24 words respectively, ensuring clarity and compliance with readability standards.
Comments 14: Comments on the Quality of English Language: I am very worried bout the translation of this manuscript since authors stated in methodology that they used ChatGPT to performed it.
Response 14: We thank both the reviewer and editor for their vigilance. ChatGPT was not used for translation, only for language editing under strict author supervision. All technical terms and analytical content were written and verified by the authors, and the final English text was cross-checked by two bilingual experts. The AI statement (page 7, lines 177–180) now explicitly clarifies this manuscript.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe authors have faithfully reflected the reviewers' comments and revised the paper. Regarding some unresolved comments, the authors acknowledged the paper's limitations and appropriately incorporated alternative solutions to address them. However, the line numbers provided in the response did not match those in the revised paper, making it difficult to identify the revised portions. I hope that future responses will be prepared based on the line numbers in the revised paper.
Reviewer 3 Report
Comments and Suggestions for AuthorsAccept in present form
Reviewer 4 Report
Comments and Suggestions for AuthorsNo more comments
Comments on the Quality of English LanguageMust be passed to. review by a native speaker.
