Spatial–Temporal Differences in Land Use Benefits and Obstacles Under Human–Land Contradictions: A Case Study of Henan Province, China

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study takes Henan Province as a case to analyze the spatiotemporal evolution and obstacles of land use benefits by integrating the entropy weight method, TOPSIS model, and obstacle degree model. The research topic is closely aligned with the practical needs of territorial space governance and sustainable development. By constructing a three-dimensional evaluation system of "economy-society-ecology", the study preliminarily reveals the evolution characteristics and key restrictive factors of land use benefits in Henan Province, providing certain references for the optimal land use in agriculture-dominated regions with human-land contradictions.

However, I have some basic questions/suggestions to be addressed before this may be accepted:

1. Why did you choose Henan Province as a case study, that is, why is this province suitable for the research topic?
2. Figure 2, give information about the line in the box.
3. Section 2.2, add references on the selection of evaluation indicators.
4. Line 344-346, “reliance on land finance consistently exceeded 60%”, but without comparing data from other provinces, it is difficult to highlight the particularity of Henan. It is recommended to supplement regional comparisons to strengthen the generality of the research conclusions.
5. The direct impact of land use policies (such as the red lines for cultivated land protection and ecological protection) on land use benefits is not considered in the paper. It is better to add a description of this limitation in the discussion.
6. Conclusions and Implications, the recommendations in this section can be adjusted to make them more focused on the findings of this study.

7. The innovation and research contribution of the paper should be more clearly described.

Author Response

Comments1. Why did you choose Henan Province as a case study, that is, why is this province suitable for the research topic?

Response 1: Thanks for the comment. We have added some sentences to give more description about the reasons. Please see L100-110.

As one of China’s top three provinces in arable land area, Henan faces unique pressure to balance the protection of its massive arable land (critical for national food security) with the development needs of its nearly 100 million people—boasting the highest population density among major arable land provinces. This duality epitomizes the most representative and structurally complex man-land conflicts in China, where in-tensive human-land interactions have given rise to three systemic challenges: (1) acute human-land conflict: With a population density of 595 persons/km²—four times the national average—Henan struggles with the paradox of being an arable land giant yet facing scarce per capita land resources, making high population density and land re-source constraints particularly pronounced;

 

Comments 2. Figure 2, give information about the line in the box.

Response 2: Done.

Figure 2. Land use benefits in Henan Province in 2011, 2015 and 2020. Black line within the box is the mean value. Numbers with different lowercase indicate significant difference among different years for an individual land use benefit (P < 0.05)

 

Comments 3. Section 2.2, add references on the selection of evaluation indicators. 

Response 3: Related references have been added. Please see section 2.3.

Wu, K.; Wang, D.; Lu, H.; Liu, G. Temporal and Spatial Heterogeneity of Land Use, Urbanization, and Ecosystem Service Value in China: A National-Scale Analysis. J. Clean. Prod. 2023, 418, 137911, doi:10.1016/j.jclepro.2023.137911.

Yang, X.; Wu, Y.; Dang, H. Urban Land Use Efficiency and Coordination in China. Sustain. 2017, 9, 1–12, doi:10.3390/su9030410.

Qian, L.; Yi, H.; Shen, M.; Wang, M. Coupling Coordination and Spatio-Temporal Evolution of Land-Use Benefits under the Dual Carbon Goal: A Case Study in Anhui, China. Sci. Total Environ. 2023, 903, 166123, doi:10.1016/j.scitotenv.2023.166123.

Li, Q.; Wei, J.; Gao, W. Spatial Differentiation and Influencing Factors of Land Eco-Efficiency Based on Low Carbon Perspective: A Case of 287 Prefecture-Level Cities in China. Environ. Challenges 2023, 10, 100681, doi:10.1016/j.envc.2023.100681.

He, W.; Yang, J.; Li, X.; Sang, X.; Xie, X. Research on the Interactive Relationship and the Optimal Adaptation Degree between Land Use Benefit and Industrial Structure Evolution: A Practical Analysis of Jiangsu Province. J. Clean. Prod. 2021, 303, 127016, doi:10.1016/j.jclepro.2021.127016.

Zhu, J.; Li, X.; Zeng, X.; Zhong, K.; Xu, Y. Cultivated Land-Use Benefit Evaluation and Obstacle Factor Identification: Empirical Evidence from Northern Hubei, China. Land 2022, 11, doi:10.3390/land11091386.

Zhang, L.; Zhang, L.; Xu, Y.; Zhou, P.; Yeh, C.H. Evaluating Urban Land Use Efficiency with Interacting Criteria: An Empirical Study of Cities in Jiangsu China. Land use policy 2020, 90, 104292, doi:10.1016/j.landusepol.2019.104292.

Song, Y.; Yeung, G.; Zhu, D.; Xu, Y.; Zhang, L. Efficiency of Urban Land Use in China’s Resource-Based Cities, 2000–2018. Land use policy 2022, 115, 106009, doi:10.1016/j.landusepol.2022.106009.

Zhuang, X.; Li, X.; Xu, Y. How Can Resource-Exhausted Cities Get Out of “The Valley of Death”? An Evaluation Index System and Obstacle Degree Analysis of Green Sustainable Development. Int. J. Environ. Res. Public Health 2022, 19, doi:10.3390/ijerph192416976.

Xu, X.; Zhang, Z.; Long, T.; Sun, S.; Gao, J. Mega-City Region Sustainability Assessment and Obstacles Identification with GIS–Entropy–TOPSIS Model: A Case in Yangtze River Delta Urban Agglomeration, China. J. Clean. Prod. 2021, 294, 126147, doi:10.1016/j.jclepro.2021.126147.

 

Comments 4. Line 344-346, “reliance on land finance consistently exceeded 60%”, but without comparing data from other provinces, it is difficult to highlight the particularity of Henan. It is recommended to supplement regional comparisons to strengthen the generality of the research conclusions.

Response 4: Thanks for the comment. We have added discussion on it in section 4.1 (L410-417).

Moreover, reliance on land finance consistently exceeded 60% (Henan Statistical Yearbook, 2021), a ratio notably higher than that of other central provinces with simi-lar development scales—for instance, Shandong and Shanxi reported average land fi-nance dependence of 38.7% and 33.4% respectively in 2020 (Ministry of Finance, 2021). This discrepancy highlights Henan’s stronger reliance on land-centered revenue models compared to its regional peers, partly stemming from its heavier burden of balancing agricultural protection (as a major grain-producing province) and urbanization funding gaps.

Comments 5. The direct impact of land use policies (such as the red lines for cultivated land protection and ecological protection) on land use benefits is not considered in the paper. It is better to add a description of this limitation in the discussion.

Response 5: Thanks for the comment. The limitation has been supplemented in Section 4.3 Comparisons with existing studies and research limitations. Please refer to it for details.

However, a notable limitation of this study is that it does not explicitly incorporate the direct impacts of key land use policies-particularly the cultivated land protection red line and ecological protection red line-into the analysis of land-use benefits. The cultivated land protection red line, established in 2006 as a legally binding target to safe-guard 1.8 billion mu of arable land [53], imposes stringent constraints on land conversion in Henan, a major grain producing province, potentially limiting the flexibility of land allocation for economic development. Similarly, the ecological protection red line, formally introduced in 2017 to demarcate critical ecological zones, further regulates land use within ecologically sensitive areas of the province [54]. These dual policy red lines undoubtedly shape the trade-offs between agricultural security, ecological preservation, and economic gains in land utilization. However, due to the complexity of quantifying their policy effects and data constraints regarding the intensity of regional policy implementation, this study has not fully unpacked how these red lines directly influence the observed patterns of comprehensive, social, ecological, and economic benefits of land use in Henan. Future research could integrate policy instruments (e.g., ecological compensation mechanisms) into the analytical framework to better disentangle the policy driven impacts on land use benefit.

Comments 6. Conclusions and Implications, the recommendations in this section can be adjusted to make them more focused on the findings of this study. 

Response 6: We have revised Conclusions and Implications to better align with the key findings of this study. Please refer to L552-574 for the updated content.

The study's findings suggest several policy implications. First, given that economic factors dominate the obstacles to land use benefits, targeted measures are required: Strengthen the agglomeration of high value-added industries (e.g., advanced manufacturing, digital economy) in Zhengzhou to leverage its "single core" radiation effect, thereby improving land based economic indicators. For peripheral regions such as the eastern and western areas, compensate for insufficient fixed asset investment per unit land by developing infrastructure linked industrial clusters, aiming to narrow the "center periphery" gap. Explore financing models suitable for an agricultural province to reduce reliance on land finance and enhance government fiscal revenue per unit land.

Second, utilizing the characteristics of leading social benefits and growing ecological benefits: Integrate high quality social services (e.g., healthcare, education) in southern Henan with agricultural modernization, such as upgrading agricultural product logistics, to increase total retail sales of social consumer goods per unit land. Promote ecological practices including pollution control and green space construction, and establish ecological compensation mechanisms in sensitive areas to reward low pollution and high output industries, achieving coordinated improvement of ecological and economic benefits.

Third, in response to the "single-city dominance" and regional imbalance: Implement a "core-periphery linkage" strategy to promote the transfer of land intensive industries from Zhengzhou to surrounding areas, improving fixed asset investment per unit land in peripheral regions. Based on regional characteristics, advance industrial upgrading in northern Henan to raise GDP per unit land, develop high efficiency agriculture in southern Henan, and leverage resources in eastern and western Henan to develop low land consumption tourism, thereby alleviating economic obstacles in a targeted manner.

Comments 7. The innovation and research contribution of the paper should be more clearly described.

Response 7: We have revised the relevant parts in the abstract. Please see L22-27.

Policy implications focus on strengthening regional differentiated development by leveraging Zhengzhou's core role to boost land-based economic benefits, integrating social-ecological strengths with agricultural modernization, and promoting "core-periphery linkage" to narrow gaps through targeted industrial and infrastructure strategies. This study could provide region-specific insights for sustainable land management in agricultural provinces amid rapid urbanization.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The attached comments could be used in improving the manuscript

Comments for author File: Comments.pdf

Author Response

Comments 1. Need to acknowledge source (attribution) in section 2.1 (line 125-145)
Response 1: We have supplemented the source attribution in the section 2.1 by adding a description of the data source. Specifically, Data were primarily sourced from the Henan Statistical Yearbook of 2020 (https://oss.henan.gov.cn/sbgt-wztipt/attachment/hntjj/hntj/lib/tjnj/2021nj/zk/indexch.htm).

Comments 2. There should be some background information (probably in the introduction section) for the conclusion made in line 439-450 to be valid. 

Response 2: We greatly appreciate your valuable suggestion. Regarding the content in lines 439-450 of the "Conclusions and Implications" section, we acknowledge that there was a lack of corresponding background context in the preceding sections. Concurrently, another reviewer commented on lines 439-450 that "the recommendations in this section can be adjusted to make them more focused on the findings of this study".​

In response to both comments, we have rewritten the implications section. The revised content is more closely targeted at the specific man-land contradiction issues in Henan's land use as mentioned in the introduction, as well as the specific economic, social, and ecological obstacle factors identified in the results section. Please refer to lines 552-574 for details.

The study's findings suggest several policy implications. First, given that economic factors dominate the obstacles to land use benefits, targeted measures are required: Strengthen the agglomeration of high value-added industries (e.g., advanced manufacturing, digital economy) in Zhengzhou to leverage its "single core" radiation effect, thereby improving land based economic indicators. For peripheral regions such as the eastern and western areas, compensate for insufficient fixed asset investment per unit land by developing infrastructure linked industrial clusters, aiming to narrow the "center periphery" gap. Explore financing models suitable for an agricultural province to reduce reliance on land finance and enhance government fiscal revenue per unit land.

Second, utilizing the characteristics of leading social benefits and growing ecological benefits: Integrate high quality social services (e.g., healthcare, education) in southern Henan with agricultural modernization, such as upgrading agricultural product logistics, to increase total retail sales of social consumer goods per unit land. Promote ecological practices including pollution control and green space construction, and establish ecological compensation mechanisms in sensitive areas to reward low pollution and high output industries, achieving coordinated improvement of ecological and economic benefits.

Third, in response to the "single-city dominance" and regional imbalance: Implement a "core-periphery linkage" strategy to promote the transfer of land intensive industries from Zhengzhou to surrounding areas, improving fixed asset investment per unit land in peripheral regions. Based on regional characteristics, advance industrial upgrading in northern Henan to raise GDP per unit land, develop high efficiency agriculture in southern Henan, and leverage resources in eastern and western Henan to develop low land consumption tourism, thereby alleviating economic obstacles in a targeted manner.

Comments 3. Inclusion of SOME THEORETICAL ASPECTS section INFORMING THE STUDY in the introduction AND/ OR CONCEPTUAL model in materials and methods could GREATELY IMPROVE THE MANUSCRIPT. This could also improve the discussion and conclusion section. 

Response 3: Thanks for the valuable comment. The theories of sustainable land use, man-land relationship coordination, regional development differentiation, and obstacle factor diagnosis serve as the theoretical underpinnings for this study on land use benefit evaluation.   We have supplemented relevant descriptions in the introduction (L72-75) and added a dedicated section 2.2 "Theoretical Foundation" (L158-186) to elaborate on these theoretical aspects. These additions are intended to strengthen the theoretical framework of the manuscript, thereby enhancing the robustness of the discussion and conclusions.

L72-75: The theories of sustainable land use, man-land relationship coordination, regional development differentiation, and obstacle factor diagnosis, as proposed by scholars both domestically and internationally, have laid a solid theoretical foundation for the evaluation of land use benefits.

 

2.2. Theoretical foundation

(1) Sustainable land use theory

The concept of "sustainable development" was proposed in Our Common Future in 1987[39], which was further reinforced at the United Nations Conference on Environment and Development in 1992. As the ultimate goal of land use benefit research, this theory emphasizes meeting the needs of the present without compromising the ability of future generations to meet their own needs, and pursues the coordinated unification of economic, social, and ecological benefits [40].

(2) Man-land relationship coordination theory

Derived from the "possibilism" put forward by French geographer P. Vidal de la Blache and J. Brunhes, this theory holds that humans can selectively utilize resources and interact with nature. Focusing on the balance between human activities and land resources, it serves as a core support for addressing man-land contradictions, with key concerns including alleviating man-land conflicts, rational land utilization, and im-proving land use efficiency [41].

(3) Regional development differentiation theory

Originating from Western regional economics, such as the growth pole theory proposed by F. Perroux in 1950, this theory posits that regions exhibit unbalanced development due to differences in resources, location, and other factors. It provides a theoretical basis for analyzing the spatial differentiation of land use benefits, understanding the root causes of imbalance, and formulating differentiated improvement strategies [33].

(4) Obstacle factor diagnosis theory

Derived from the law of limiting factors proposed by Blackman in 1905 (stating that limiting factors determine the rate or intensity of biological physiological processes), this theory offers a methodological basis for identifying key limiting factors in a system. It locates "shortboards" by quantifying and analyzing the degree of obstacles. In the evaluation of land use benefits, it can identify key bottlenecks restricting the improvement of comprehensive benefits (e.g., specific indicators in economic, social, or ecological dimensions), providing a scientific basis for targeted policy-making [38]

Comments 4. Font size in Fig 2 need to be improved. 

Response 4: Done.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Authors,

The manuscript presents a comprehensive evaluation of land use benefits and obstacles in Henan Province, China, using a robust methodological framework. While the study is well-structured and addresses an important research gap, several areas could be improved to enhance its clarity and scientific rigor. Below are specific comments for improvement:

1. I recommend expanding the explanation of the entropy weight method and TOPSIS model, particularly the rationale behind indicator weight determination. A sensitivity analysis of the weighting scheme would further validate the methodological robustness.

2. The reliance on statistical yearbooks warrants explicit acknowledgment of potential data inconsistencies. A brief discussion of imputation methods for missing data and their implications would strengthen transparency.

3. While the spatial analysis is thorough, Figures 3–6 would benefit from standard cartographic elements (scale bars, north arrows) to align with conventional mapping practices.

4. The 2011–2020 period captures key trends, but I suggest addressing whether this timeframe adequately reflects long-term dynamics, particularly given China’s rapid urbanization.

5. The recommendations could be sharpened by specifying how obstacle factors (e.g., budget revenue per unit area) might translate into targeted policy interventions. Concrete examples would enhance applicability.

6. Comparing Henan’s results with analogous regions in China or globally would help situate the findings within broader land-use efficiency discourse.

7. The study would benefit from quantifying uncertainties, such as confidence intervals for obstacle degrees, to reinforce the reliability of conclusions.

8. Figure 7’s heatmap could be improved with more distinct labeling and a refined color scheme to better communicate temporal and spatial variations.

I am available for any clarification.

Kind regards.

Author Response

Comments 1. I recommend expanding the explanation of the entropy weight method and TOPSIS model, particularly the rationale behind indicator weight determination. A sensitivity analysis of the weighting scheme would further validate the methodological robustness.

Response 1: Thanks for your suggestion. We have added some sentences to give more description about the entropy weight method and TOPSIS model. Please see L239-242 and L261-265.

L239-242: The entropy weight method is an objective weighting method. The core principle is that the determination of the weight of the indicator is entirely based on the discrete degree of the indicator data itself. The greater the dispersion of the index, the smaller the entropy value, and the larger the information utility value, the greater its weight.

L261-265: TOPSIS is a classic multi-attribute decision analysis method. The core idea is that the optimal solution should be as close as possible to the "ideal point" and as far away from the "anti-ideal point" as possible. The basic principle is based on the geometric distance, and the relative proximity of the calculation scheme to the ideal optimal solution and the ideal worst solution is ranked.

Comments 2. The reliance on statistical yearbooks warrants explicit acknowledgment of potential data inconsistencies. A brief discussion of imputation methods for missing data and their implications would strengthen transparency.

Response 2: Thanks for your suggestion. We have rewritten and improved this part. Please see L222-233.

In order to solve the problem of missing data in some indicators in the study, this study comprehensively used Trend Extrapolation and Mean Imputation to fill in the problem based on the data distribution characteristics and available auxiliary information. For continuous variables with significant temporal trends or serial correlations, the linear or nonlinear regression model for historical data is used to predict missing values (trend extrapolation). For indicators with relatively stable distribution, the mean value of the index in the complete sample is used as the substitute value (mean imputation method). For example, 2020 fixed asset investment data for Henan’s cities were estimated using 2019 values and a five-year (2015-2019) average growth rate, while sulfur dioxide emissions in Jiyuan City were imputed using the provincial average. These methods may ignore external shocks and structural changes, affecting the overall statistics. However, because the amount of missing data is small, the overall impact is manageable.

Comments 3. While the spatial analysis is thorough, Figures 3–6 would benefit from standard cartographic elements (scale bars, north arrows) to align with conventional mapping practices.

Response 3: Thanks for the suggestion. We have revised and standardized these figures.

 

Comments 4. The 2011–2020 period captures key trends, but I suggest addressing whether this timeframe adequately reflects long-term dynamics, particularly given China’s rapid urbanization.

Response 4: Thanks for your suggestion. We have added a dedicated paragraph to address the question. Please see L210-219.

This period covers the key stage of China's urbanization transformation from "speed expansion" to "quality improvement", which has a unique historical significance. 2011 was the first year of China's 12th Five-Year Plan, marking the first time that "intensive land use" was included in the core goal at the national level, and a binding target of a 30% reduction in construction land per unit of GDP was proposed. 2020 is not only the final year of the 13th Five-Year Plan, but also the turning point of the convergence of poverty alleviation and rural revitalization strategies. Therefore, this timeframe can adequately reflect the long-term dynamics, and the changes in land use benefits in this time period have strong representative and practical enlightenment.  

Comments 5. The recommendations could be sharpened by specifying how obstacle factors (e.g., budget revenue per unit area) might translate into targeted policy interventions. Concrete examples would enhance applicability.

Response 5: Thanks for your suggestion. We have rewritten this part. Please see L552-574.

The study's findings suggest several policy implications. First, given that economic factors dominate the obstacles to land use benefits, targeted measures are required: Strengthen the agglomeration of high value-added industries (e.g., advanced manufacturing, digital economy) in Zhengzhou to leverage its "single core" radiation effect, thereby improving land based economic indicators. For peripheral regions such as the eastern and western areas, compensate for insufficient fixed asset investment per unit land by developing infrastructure linked industrial clusters, aiming to narrow the "center periphery" gap. Explore financing models suitable for an agricultural province to reduce reliance on land finance and enhance government fiscal revenue per unit land.

Second, utilizing the characteristics of leading social benefits and growing ecolog-ical benefits: Integrate high quality social services (e.g., healthcare, education) in southern Henan with agricultural modernization, such as upgrading agricultural product logistics, to increase total retail sales of social consumer goods per unit land. Promote ecological practices including pollution control and green space construction, and establish ecological compensation mechanisms in sensitive areas to reward low pollution and high output industries, achieving coordinated improvement of ecological and economic benefits.

Third, in response to the "single-city dominance" and regional imbalance: Implement a "core-periphery linkage" strategy to promote the transfer of land intensive industries from Zhengzhou to surrounding areas, improving fixed asset investment per unit land in peripheral regions. Based on regional characteristics, advance industrial upgrading in northern Henan to raise GDP per unit land, develop high efficiency agriculture in southern Henan, and leverage resources in eastern and western Henan to develop low land consumption tourism, thereby alleviating economic obstacles in a targeted manner.

Comments 6. : Comparing Henan’s results with analogous regions in China or globally would help situate the findings within broader land-use efficiency discourse.

Response 6: Thanks for your suggestion. To address the point raised, we have added a dedicated section (Section 4.3) titled " Comparisons with Existing Studies and Research Limitations" in the Discussion. In this section, we have supplemented: (1) a brief assessment of the applicability of the entropy weight method, TOPSIS model, and obstacle degree model to the study of land use benefits in Henan, along with a comparison with similar studies to clarify the rationale for method selection; (2) a contrast between our research results and relevant studies from other parts of the world (e.g., the Ruhr region in Germany and the Cerrado agricultural region in Brazil) to enhance the international relevance and robustness of the findings. These additions aim to make the methodological framework more rigorous and the research conclusions more contextually grounded.

Section 4.3:

In this study, we employed the entropy weight method and TOPSIS model to evaluate the land use benefits of cities in Henan Province from 2011 to 2020, and constructed an obstacle degree model to identify the primary limiting factors affecting efficient land use. Approved by similar evaluation study, the selection of these methods is justified by their wide application in land use benefit assessment due to their objectivity in weight determination (i.e., entropy weight method) and effectiveness in multi-criteria decision-making (i.e., TOPSIS model) [36,38] Combined with the use of official statistical data (e.g., Henan Statistical Yearbook), the methodological rigor and data reliability enhance the scientific credibility of the results.

Although our findings indicate a steady improvement in Henan’s land use benefit over the past decade, there remains substantial room for enhancement when compared with developed regions in China. For instance, Zhejiang Province has adopted an evaluation system centered on the input-output efficiency of construction land, leveraging market-oriented mechanisms to significantly boost industrial land performance—its industrial land tax revenue per unit area is 2.6 times that of Henan[49]. Similarly, Jiangsu Province has promoted mixed industrial land use policies, raising the plot ratio to 4.0, whereas comparable pilot projects in Zhengzhou (Henan) have only achieved a plot ratio of 2.5[50].

From an international perspective, the Ruhr region in Germany offers a notable example of transforming industrial wastelands into multifunctional landscape parks through ecological restoration and cultural integration. This strategy not only rehabilitates degraded ecosystems but also integrates design, cultural, and tourism functions, fostering mixed-use industrial land development and substantially improving land use benefit [46]. In contrast, Henan’s industrial wastelands remain underutilized, with limited functional diversification. For agricultural land, the Brazilian Cerrado - a rain-fed agricultural region analogous to Henan - has effectively enhanced agricultural land efficiency through reduced tillage frequency and legume-based nitrogen fixation [47]. Drawing parallels, Henan’s agricultural land currently faces challenges of soil compaction and declining ecological benefits, suggesting potential for adopting Brazil’s model of conservation tillage combined with precision fertilization.

Overall, optimizing land use benefits in Henan requires integrating domestic best practices and international experiences, while aligning with its dual positioning as a major grain-producing area and an emerging industrial hub. However, a notable limitation of this study is that it does not explicitly incorporate the direct impacts of key land use policies—particularly the cultivated land protection red line and ecological protection red line—into the analysis of land-use benefits. The cultivated land protection red line, established in 2006 as a legally binding target to safeguard 1.8 billion mu of arable land, imposes stringent constraints on land conversion in Henan, a major grain producing province, potentially limiting the flexibility of land allocation for economic development. Similarly, the ecological protection red line, formally introduced in 2017 to demarcate critical ecological zones, further regulates land use within ecologically sensitive areas of the province. These dual policy red lines undoubtedly shape the trade-offs between agricultural security, ecological preservation, and economic gains in land utilization. However, due to the complexity of quantifying their policy effects and data constraints regarding the intensity of regional policy implementation, this study has not fully unpacked how these red lines directly influence the observed patterns of comprehensive, social, ecological, and economic benefits of land use in Henan. Future research could integrate policy instruments (e.g., ecological compensation mechanisms) into the analytical framework to better disentangle the policy driven impacts on land use benefit.

Comments 7. The study would benefit from quantifying uncertainties, such as confidence intervals for obstacle degrees, to reinforce the reliability of conclusions.
Response 7: Thanks for your suggestion. To enhance the reliability of the obstacle factor determination results, we have supplemented the analysis by setting confidence intervals for the obstacle degrees. Please refer to Lines 370-371 for the revised content.

Confidence intervals were set for 0.18-0.2, 0.16-0.18, 0.14-0.16, 0.12-0.14, and 0.1-0.12, and the top five main obstacle factors were determined.

 

Comments 8. Figure 7’s heatmap could be improved with more distinct labeling and a refined color scheme to better communicate temporal and spatial variations.

Response 8: We have revised and improved the figure with more distinct labeling and a refined color scheme.

 

Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

The reviewed article addresses the issue of a comprehensive analysis of land-use benefits in one of China's most important provinces, Henan Province, from 2011 to 2020, using an integrated methodological approach combining quantitative methods: entropy, TOPSIS and the obstacle degree model.The aim of the paper is to identify the obstacles inhibiting the growth of land-use efficiency and to point out spatial and functional differences within the province.

The strengths of the article are its logical and clear structure. The article has a logical and clear structure. The authors clearly define the research objectives, present the methodology and results, and formulate conclusions and recommendations.

Some shortcomings of the paper are the lack of evaluation of the application of this type of methods to the issue under study and comparison with other similar methods (1) and the lack of reference to other studies of this type from other parts of the world (2). In this context, firstly, the article should have been supplemented by a brief assessment of the methodology and research procedure used. Secondly, the held results of the research should be contrasted with other results of similar research from other parts of the world.

In conclusion, the peer-reviewed article is an original and valuable contribution to the study of space management in developing regions. With minor revisions, it is suitable for publication.

Author Response

Comments 1. Some shortcomings of the paper are the lack of evaluation of the application of this type of methods to the issue under study and comparison with other similar methods (1) and the lack of reference to other studies of this type from other parts of the world (2). In this context, firstly, the article should have been supplemented by a brief assessment of the methodology and research procedure used. Secondly, the held results of the research should be contrasted with other results of similar research from other parts of the world.

Response 1: We appreciate this insightful comment. To address the two points raised, we have added a dedicated section (Section 4.3) titled " Comparisons with Existing Studies and Research Limitations" in the Discussion. In this section, we have supplemented: (1) a brief assessment of the applicability of the entropy weight method, TOPSIS model, and obstacle degree model to the study of land use benefits in Henan, along with a comparison with similar studies to clarify the rationale for method selection; (2) a contrast between our research results and relevant studies from other parts of the world (e.g., the Ruhr region in Germany and the Cerrado agricultural region in Brazil) to enhance the international relevance and robustness of the findings. These additions aim to make the methodological framework more rigorous and the research conclusions more contextually grounded.

 

Section 4.3:

In this study, we employed the entropy weight method and TOPSIS model to evaluate the land use benefits of cities in Henan Province from 2011 to 2020, and constructed an obstacle degree model to identify the primary limiting factors affecting efficient land use. Approved by similar evaluation study, the selection of these methods is justified by their wide application in land use benefit assessment due to their objectivity in weight determination (i.e., entropy weight method) and effectiveness in multi-criteria decision-making (i.e., TOPSIS model) [36,38] Combined with the use of official statistical data (e.g., Henan Statistical Yearbook), the methodological rigor and data reliability enhance the scientific credibility of the results.

Although our findings indicate a steady improvement in Henan’s land use benefit over the past decade, there remains substantial room for enhancement when compared with developed regions in China. For instance, Zhejiang Province has adopted an evaluation system centered on the input-output efficiency of construction land, leveraging market-oriented mechanisms to significantly boost industrial land performance—its industrial land tax revenue per unit area is 2.6 times that of Henan[49]. Similarly, Jiangsu Province has promoted mixed industrial land use policies, raising the plot ratio to 4.0, whereas comparable pilot projects in Zhengzhou (Henan) have only achieved a plot ratio of 2.5[50].

From an international perspective, the Ruhr region in Germany offers a notable example of transforming industrial wastelands into multifunctional landscape parks through ecological restoration and cultural integration. This strategy not only rehabilitates degraded ecosystems but also integrates design, cultural, and tourism functions, fostering mixed-use industrial land development and substantially improving land use benefit [46]. In contrast, Henan’s industrial wastelands remain underutilized, with limited functional diversification. For agricultural land, the Brazilian Cerrado-a rain-fed agricultural region analogous to Henan—has effectively enhanced agricultural land efficiency through reduced tillage frequency and legume-based nitrogen fixation [47]. Drawing parallels, Henan’s agricultural land currently faces challenges of soil compaction and declining ecological benefits, suggesting potential for adopting Brazil’s model of conservation tillage combined with precision fertilization.

Overall, optimizing land use benefits in Henan requires integrating domestic best practices and international experiences, while aligning with its dual positioning as a major grain-producing area and an emerging industrial hub. However, a notable limitation of this study is that it does not explicitly incorporate the direct impacts of key land use policies—particularly the cultivated land protection red line and ecological protection red line—into the analysis of land-use benefits. The cultivated land protection red line, established in 2006 as a legally binding target to safeguard 1.8 billion mu of arable land, imposes stringent constraints on land conversion in Henan, a major grain producing province, potentially limiting the flexibility of land allocation for economic development. Similarly, the ecological protection red line, formally introduced in 2017 to demarcate critical ecological zones, further regulates land use within ecologically sensitive areas of the province. These dual policy red lines undoubtedly shape the trade-offs between agricultural security, ecological preservation, and economic gains in land utilization. However, due to the complexity of quantifying their policy effects and data constraints regarding the intensity of regional policy implementation, this study has not fully unpacked how these red lines directly influence the observed patterns of comprehensive, social, ecological, and economic benefits of land use in Henan. Future research could integrate policy instruments (e.g., ecological compensation mechanisms) into the analytical framework to better disentangle the policy driven impacts on land use benefit.