Impacts of Climate and Land-Use Change on Fraction Vegetation Coverage Based on PLUS-Dimidiate Pixel Model
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsDear Editor,
I am pleased to recommend the manuscript entitled “Asymmetric impacts of climate and land-use change on vegetation coverage” for publication in Sustainability. This study offers valuable insights into how climate and land-use changes interact to influence vegetation coverage in the Chengdu-Chongqing Economic Circle region. The authors effectively demonstrate that climate and land-use change can jointly enhance vegetation restoration efforts, highlighting a prevailing trend of vegetation recovery over recent decades. Additionally, the manuscript emphasizes the importance of understanding these interactive effects to guide future restoration initiatives, showcasing a clear potential for positive outcomes under adaptive management strategies. The research aligns well with the objectives of Sustainability, offering practical implications for improving ecosystem resilience and sustainable land management.
Comments for author File: 
Comments.pdf
Author Response
Thank you very much for the reviewers’ comments. According to their suggestions, we replied to the reviewer’s opinions one by one as follows. In document of “Response” and “Manuscripts”, blue means modified, black means unmodified.
Review 1
(1)Introduction
Line 31: Consider providing a clearer definition ofthe term "plant community." I suggest:"Vegetation, considered a community of plants, plays..." to ensure immediate readei comprehension.
Response: Thanks for the comments. We accepted the suggestions, and revised the statements in the literature review .
Line 31-32 “Vegetation, considered a community of plants [1], plays a role in connecting the atmosphere, soil and hydrosphere in a certain surface ecosystem[2].”
Line 38: Use "climate changes" instead of just "climate change" to better align with the broader idea of alterations in temperature and precipitation.
Response: Thanks for the comments. We accepted the suggestions, and revised the statements in the paper.
Line 40: "Sources and sinks" would be a better choice of words to describe vegetation responses to the mentioned factors, highlighting the dynamic exchange of gases andbiomass.
Response: Thanks for the comments. We accepted the suggestions, and revised the statements in the literature review .
Line 40-41 “In contrast, other studies held that human activities were also the source and sink of FVC[14].”
Lines 51-59: It would be helpful to mention the general limitations of each model morebalancedly, highlighting not only their weaknesses but also their strengths for a more comprehensive analysis.
Response: Line 66-78, the relevant content of the article has been modified to comprehensively present the advantages and disadvantages of each model, and explain why the plus model is selected.
Line 66-78 “Future land-use data comes from land use simulation. At present, land-use simulation models are mainly divided into two types: quantitative simulation and spatial simulation[23]. Among them, Markov, regression analysis, system dynamics and other quantitative simulation models can quantitatively simulate land quantity and structure changes, they can quantify the transformation of land-use type and conversion rate, but cannot show the spatial changes[24]. Compared with quantitative simulation model, spatial simulation model can describe spatial changes effectively. FLUS model introduces the adaptive coefficient and roulette mechanism, which can better deal with the uncertainty of land development[25]. But FLUS model is limited in reflecting the spatial differences of land-use changes [26]. The CLUE-S model can evaluate the influencing factors of land-use changes through logistic regression analysis, but it takes less account of land-use changes over time and the impact of external factors on land-use [27]. ”
(2)Result
Ensure consistent use of terms throughout the text, such as "FVC" (Fractional VegetationCover) and "land use." Avoid variations like "soil use" or "cover index," unless needed to distinguish specific contexts. Improve figure and table captions by providing more context about what they represent. This helps readers understand how each visualization complements the text and how the data illustrate key analysis points.
Response: Thanks for the comments. We accepted the suggestions, and revised the statements in the literature review . The full text FVC and land use are unified. 2. “FVC” and “land use” used in the picture and title have been corrected
(3)Discusion
1.Lines 335-337: To strengthen this argument, the authors could consider adding data orpercentages related to "the proportion of medium and high FVC that increased in 2020."This would make the text more persuasive and help readers understand the scale of improvements in vegetation cover.
Response: Thanks for the comments. We accepted the suggestions and added the data of medium and high vegetation coverage and high vegetation coverage changes from 2020 to 2020 to increase the persuasiveness.
Line377-380 “In 2020, the middle coverage and high coverage in the CCEC region increased by 24.59% and 21.68% respectively. This is because from 2000 to 2010, the pilot project of return-ing farmland to forest in the China Economic Cooperation Zone restored the forest ar-ea and encouraged the continuous expansion of forests.”
2.Lines 342-347: The authors' mention of "decreased vegetation cover and stability" at the end of the paragraph could be more detailed, exploring how urbanization affects ecological resilience. This could enrich the analysis by highlighting the adverse impacts of accelerated urbanization.
Response：Thanks for the comments. We accepted the suggestions and added the description of vegetation coverage and stability, and added the content of how urbanization affects ecological resilience.
Line 389-397 “A large amount of land has been used for industrialization, urban construction and agricultural production, resulting in the destruction and change of the land which was originally covered with vegetation and the reduction of FVC. Population growth and economic development have led to the reduction of FVC, the decline of ecosystem resilience and the deterioration of vegetation stability. The outward expansion of cities has led to the gradual depletion of land resources. The community structure of ecosystem has changed to a single one, aggravating the loss of biodiversity. Soil erosion and soil loss have increased the risk of geological disasters. “
3.Additionally, when discussing the driving role of Chengdu and other cities, the authors could include recommendations for urban planning and conservation policies or practices that could balance development with sustainability.
Response: Thanks for the comments. We accepted the suggestions and put forward suggestions on urban planning and ecological protection.
Lines 397-400 “Therefore, in terms of urban planning, we should delimit the urban growth boundary, curb the disorderly spread of construction land, and control the damage of urban development and construction to the surrounding resources. ”
4.Lines 350-353: When mentioning panel model results, it is important to indicate the magnitude or direction of correlations beyond the p-value. For example, when p-valuesfor temperature, wind speed, and precipitation are less than 0.01, specify whether the effect was positive or negative.
Response: Thanks for the comments. We accepted the suggestions. Line 408-409 complements the positive and negative effects of land use and climate on FVC. In this paper, the future FVC is simulated by correlation. There are some limitations in this aspect. In the discussion part, the research limitations and future prospects are discussed.
Line 408-409 “Precipitation is positively correlated with vegetation cover, while land-use degree, temperature and wind speed are negatively correlated with vegetation cover.”
5.Lines 366-367: When stating that "land-use change was the crucial factor contributing to the decrease of FVC," emphasize the need for sustainable land-use policies to mitigate these impacts.
Response: Thanks for the comments. We accepted the suggestions and emphasized the need for sustainable land-use policies to mitigate these impacts.
Line 423-425 “In order to prevent vegetation cover degradation, it is necessary to formulate land use policies for sustainable development, such as land use control, comprehensive land consolidation and ecological land protection”
6.Lines 381-386: I recommend that the authors clarify the practical difference between SSP245 and SSP585 scenarios when discussing the results, highlighting how specific conditions of each scenario influence the interaction between climate and land use on FVC.
Response: Thanks for the comments. We accepted the suggestions.
Line 436-448 “Under the SSP245 scenario in 2050, compared with 2020, the average annual temperature in Chengdu and Chongqing decreased by 4.42 ℃, the average annual precipitation decreased by 293.98mm, and the average annual wind speed increased by 1.33m/s. Under the scenario of SSP585 in 2050, the average annual temperature in Chengdu and Chongqing decreased by 3.87 ℃, the average annual precipitation decreased by 95.23mm, and the average annual wind speed increased by 1.38m/s. Results of the effects of climate factors on FVC obtained from the panel model results showed that, under SSP245 scenario, the overall FVC increased by 0.065 for the decrease of temperature, the overall FVC decreased by 0.071 for the decrease of precipitation, and the overall FVC decreased by 0.019 for the increase of wind speed. Under the SSP585 scenario, the overall of FVC increased by 0.056 for the decrease of temperature, the overall FVC decreased by 0.023 for the decrease of precipitation, the overall of FVC decreased by 0.020 for the increase of wind speed.
”
7.Lines 382-386: When mentioning the percentages of superposition and compensation effects (90.69%, 90.57%, 9.31%, 9.43%), consider including a brief explanation of what they mean in practice.
Response: Thanks for the comments. We accepted the suggestions and explained it with reference to the literature.
Line 462-467 “As indicated by Zhu, et al. [60]), the influence of land use, temperature and precipitation on NDVI presented an interactive enhancement. Huo and Sun [61]) found that the explanatory power of construction land, temperature and precipitation on the FVC in the northwest Yunnan Plateau was more significant after interaction. Meng, et al. [62]) reported that mutual enhancement and nonlinear enhancement were manifested when factors interacted. ”
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsI am pleased to have reviewed the manuscript titled "Asymmetric impacts of climate and land-use change on vegetation coverage." It is essential to explore the effects of global climate change and rapid land-use alterations on vegetation coverage under the dual backdrop of these pressing issues. Overall, the manuscript attempts to address a highly significant scientific question with a clear framework. However, there are several issues that require immediate attention:
1 Introduction
(1) The logic of the introduction is somewhat chaotic and lacks a literature review to address why it is necessary to study the "Asymmetric impacts of climate and land-use change on vegetation coverage." From the current introduction, we cannot discern what previous researchers have done in exploring the impacts of climate and land-use changes on vegetation coverage, what progress has been made, why it is important to study the asymmetric effects of climate and land-use changes on vegetation coverage, how to define "asymmetric impacts," and the significance of studying this issue.
(2) The third paragraph of the introduction (lines 51-60) lacks logical connection with the surrounding context. What is the relationship between land-use simulation models and vegetation coverage? How are land-use simulation models related to the asymmetric impacts on vegetation coverage? The literature review should focus on how land-use simulation models are related to addressing the scientific questions of the manuscript, rather than simply comparing and introducing various land-use simulation models.
(3) The introduction also fails to answer the question of why we should study the “Chengdu-Chongqing Twin-city Economic Circle”, why we should study the “asymmetric impacts of climate and land-use change on vegetation cover in the Chengdu-Chongqing Twin-city Economic Circle”, and what are the practical significance of the study of this area and what are the theoretical significance. All these need to be answered by the authors.
2 L97, Figure 1 also needs to show the current land use status of the study area
3 L233-L240, please show a comparison between the current land use map and the simulation for 2020.
4 L252-L272, How is the impact of climate on land use represented in the land use simulation for 2050?
5 L278-L318, how is the asymmetric effect of climate and land use change on vegetation cover represented?
6 Please add to the discussion section on the shortcomings and future outlook of the manuscript.
7 L398-L445, the conclusion section is written like a result and is too lengthy. Please summarize the results throughout the text and condense the concluding statements.
Author Response
Thank you very much for the reviewers’ comments. According to their suggestions, we replied to the reviewer’s opinions one by one as follows. In document of “Response” and “Manuscripts”, blue means modified, black means unmodified.
Review 2
1.Introduce
（1）The logic of the introduction is somewhat chaotic and lacks a literature review to address why it is necessary to study the "Asymmetric impacts of climate and land-use change on vegetation coverage." From the current introduction, we cannot discern what previous researchers have done in exploring the impacts of climate and land-use changes on vegetation coverage, what progress has been made, why it is important to study the asymmetric effects of climate and land-use changes on vegetation coverage, how to define "asymmetric impacts," and the significance of studying this issue.
Response: Thanks for the comments. We re-examined the findings and found that the use of asymmetric effects was a bit overstated. In this paper, we studied the superposition effect and compensation effect of land use and climate defense on FVC. The superposition effect indicates that the impact of climate change and land use change on FVC is positive or negative at the same time, and the compensation effect indicates that the impact of climate change and land use change on FVC is positive and negative at the same time. We revised the full text, including the title which is changed to "Impacts of climate and land-use change on fraction vegetation coverage based on PLUS-Dimidiate Pixel model".
Line 87-94 “The geographic detector explored the explanatory power of the driving factors of FVC, but the positive and negative effects of driving factors cannot be revealed. At the same time, previous studies mostly analyzed the effects of land use and climate changes on FVC. Therefore, this paper explored the response mechanism of FVC to future climate and land-use changes by coupling PLUS model and dimidiate pixel model. In addition, a quantitative analysis of the correlation between multiple driving factors and FVC was performed to reveal the positive and negative effects of both land-use and climate changes.”
Line 314-359 “The impacts of land use and climate change on FVC are superimposed by ArcGIS software to identify the space of positive and negative effects.The analysis of the impacts of climate and land-use change on FVC in the CCEC region was performed in the research (Fig. 7). FVC exhibited significantly negative and positive responses to climate and land-use change, respectively. It can be seen that under the SSP245 scenario, land-use change exhibits an enhancement effect on FVC in 6.33% of the total study area, with an area of 11783.4km². 10.03% of the total study area subjects to FVC degradation due to land-use change, with corresponding area of 18658.14km². Climate change exhibits significantly negative and positive responses to FVC. It exhibits an enhancement effect on FVC in 40.70% of the total study area, with an area of 75722.23km². 59.30% of the total study area subjects to FVC degradation due to climate change, with corresponding area of 110345.38km². Obviously, climate and land-use change jointly in-creased or decreased cumulative percentage of FVC area. It is necessary to weigh the pros and cons of the effects of climate and land-use change on FVC to analyze their interactive effects. Thus, results in Table 2 were used to recalculate with the raster calculator in Arcgis. If the effects of climate and land-use on FVC are both positive or negative, then there is a superposition effect. If the effects of climate and land use on FVC are reversed, indicating a compensation effect between them. The compensation effect of one factor to another was evaluated by its net contribution to the variance of FVC. Then the spatial distribution and change area of FVC under the future scenario were visualized.
Based on the panel model, the variable relationship between FVC, land use, and climate was revealed. The land use and climate change data were overlaid and analyzed using ArcGIS software to quantify the impact of land use and climate change on FVC.The obtained results indicated that FVC value in the CCEC region also changes as a consequence of interactive effects from climate and land-use change. As shown in Figure 7c, the area in which FVC affected by climate change compensates for the area in which FVC affected by land-use change is 9733.23km², accounting for 5.23%. The ar-ea in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 7594.33km², accounting for 4.08%. Land-use and climate change can also promote the improvement of FVC jointly, and the area with positive superposition effect is 65989km², accounting for 35.47%. The area with negative su-perposition effect is 102751.05km², accounting for 55.22%.
Due to the difficulty in simulating land policies and management, it was consid-ered that the land-use change under the SSP585 scenario is similar to that under the SSP245 scenario. The area of FVC improved by climate change is 86804.93km², ac-counting for 46.65% of the study area. The area in which FVC declined due to climate change is 99262.68km², accounting for 53.35% of the study area. For the interaction of land-use and climate change on FVC show that the area in which FVC affected by cli-mate change compensates for the area in which FVC affected by land use change is 10,698.95km², accounting for 5.75%. The area in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 6851.74km², ac-counting for 3.68%. The area with positive superposition effect of land use change and climate change on FVC is 76105.98km², accounting for 40.90%. The area with negative superposition effect of land-use changes and climate change on FVC is 92410.94km², accounting for 49.67%.”
(2)The third paragraph of the introduction (lines 51-60) lacks logical connection with the surrounding context. What is the relationship between land-use simulation models and vegetation coverage?
Response: Thanks for the comments. We accepted the suggestions. This paper simulated future vegetation coverage based on land use and climate change, among which it simulated future land use through PLUS model, extracted vegetation coverage through Dixel Pixel model, coupled PLUS model and Dixel Pixel model, explored their relationship through panel model, and discussed FVC's response to future climate and land use change. In short, this paper simulated the future vegetation cover based on the future land use and future climate data. Line 66-79 to explore future land use data.
Line 66-79 “Future land-use data came from land use simulation. At present, land-use simulation models are mainly divided into two types: quantitative simulation and spatial simulation[23]. Among them, Markov, regression analysis, system dynamics and other quantitative simulation models can quantitatively simulate land quantity and structure changes, they can quantify the transformation of land-use type and conversion rate, but cannot show the spatial changes[24]. Compared with quantitative simulation model, spatial simulation model can describe spatial changes effectively. FLUS model introduces the adaptive coefficient and roulette mechanism, which can better deal with the uncertainty of land development[25]. But FLUS model is limited in reflecting the spatial differences of land-use changes [26]. The CLUE-S model can evaluate the influencing factors of land-use changes through logistic regression analysis, but it takes less account of land-use changes over time and the impact of external factors on land-use [27]. The PLUS model can simulate the evolution of land-use patches with high accuracy, and can quantitatively describe the nonlinear relationship between various driving factors and land type change [28].”
（3）How are land-use simulation models related to the asymmetric impacts on vegetation coverage?
Response: Thanks for the comments. We re-examined the findings and found that the use of asymmetric effects was a bit overstated. In this paper, we studied the superposition effect and compensation effect of land use and climate defense on FVC. The superposition effect indicates that the impact of climate change and land use change on FVC is positive or negative at the same time, and the compensation effect indicates that the impact of climate change and land use change on FVC is positive and negative at the same time. We revised the full text, including the title which is changed to "Impacts of climate and land-use change on fraction vegetation coverage based on PLUS-Dimidiate Pixel model".
Line 87-94 “The geographic detector explored the explanatory power of the driving factors of FVC, but the positive and negative effects of driving factors cannot be revealed. At the same time, previous studies mostly analyzed the effects of land use and climate changes on FVC. Therefore, this paper explored the response mechanism of FVC to future climate and land-use changes by coupling PLUS model and dimidiate pixel model. In addition, a quantitative analysis of the correlation between multiple driving factors and FVC was performed to reveal the positive and negative effects of both land-use and climate changes.”
Line 314-359 “The impacts of land use and climate change on FVC are superimposed by ArcGIS software to identify the space of positive and negative effects.The analysis of the impacts of climate and land-use change on FVC in the CCEC region was performed in the research (Fig. 7). FVC exhibited significantly negative and positive responses to climate and land-use change, respectively. It can be seen that under the SSP245 scenario, land-use change exhibits an enhancement effect on FVC in 6.33% of the total study area, with an area of 11783.4km². 10.03% of the total study area subjects to FVC degradation due to land-use change, with corresponding area of 18658.14km². Climate change exhibits significantly negative and positive responses to FVC. It exhibits an enhancement effect on FVC in 40.70% of the total study area, with an area of 75722.23km². 59.30% of the total study area subjects to FVC degradation due to climate change, with corresponding area of 110345.38km². Obviously, climate and land-use change jointly in-creased or decreased cumulative percentage of FVC area. It is necessary to weigh the pros and cons of the effects of climate and land-use change on FVC to analyze their interactive effects. Thus, results in Table 2 were used to recalculate with the raster calculator in Arcgis. If the effects of climate and land-use on FVC are both positive or negative, then there is a superposition effect. If the effects of climate and land use on FVC are reversed, indicating a compensation effect between them. The compensation effect of one factor to another was evaluated by its net contribution to the variance of FVC. Then the spatial distribution and change area of FVC under the future scenario were visualized.
Based on the panel model, the variable relationship between FVC, land use, and climate was revealed. The land use and climate change data were overlaid and analyzed using ArcGIS software to quantify the impact of land use and climate change on FVC.The obtained results indicated that FVC value in the CCEC region also changes as a consequence of interactive effects from climate and land-use change. As shown in Figure 7c, the area in which FVC affected by climate change compensates for the area in which FVC affected by land-use change is 9733.23km², accounting for 5.23%. The ar-ea in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 7594.33km², accounting for 4.08%. Land-use and climate change can also promote the improvement of FVC jointly, and the area with positive superposition effect is 65989km², accounting for 35.47%. The area with negative su-perposition effect is 102751.05km², accounting for 55.22%.
Due to the difficulty in simulating land policies and management, it was considered that the land-use change under the SSP585 scenario is similar to that under the SSP245 scenario. The area of FVC improved by climate change is 86804.93km², ac-counting for 46.65% of the study area. The area in which FVC declined due to climate change is 99262.68km², accounting for 53.35% of the study area. For the interaction of land-use and climate change on FVC show that the area in which FVC affected by climate change compensates for the area in which FVC affected by land use change is 10,698.95km², accounting for 5.75%. The area in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 6851.74km², ac-counting for 3.68%. The area with positive superposition effect of land use change and climate change on FVC is 76105.98km², accounting for 40.90%. The area with negative superposition effect of land-use changes and climate change on FVC is 92410.94km², accounting for 49.67%.”
（4）The literature review should focus on how land-use simulation models are related to addressing the scientific questions of the manuscript, rather than simply comparing and introducing various land-use simulation models.
Response：Thanks for the comments. We accepted the suggestions. This paper simulated future vegetation coverage based on future land use and climate change, simulated future land use through plus model, extracted vegetation coverage through pixel dichotomy model, coupled plus model and pixel dichotomy model, explored their relationship through panel model, and discussed FVC's response to future climate and land use change.
Line 64-66 “In practice, it is beneficial to take targeted measures for ecological restoration in Chengdu Chongqing region.
Future land use data came from land use simulation. “
Line 90-97 “Therefore, this paper explored the response mechanism of FVC to future climate and land-use change by coupling PLUS model and dimidiate pixel model. In addition, a quantitative analysis of the correlation between multiple driving factors and FVC was performed to reveal the positive and negative effects of both land-use and climate changes. The results of this paper provided a scientific basis for vegetation restoration project in the CCEC region, which was also instructive to other regions.“
(5)The introduction also fails to answer the question of why we should study the “Chengdu-Chongqing Twin-city Economic Circle”,
Response: Thanks for the comments. We accepted the suggestions. Line51-65 explained the reason of studying the Chengdu-Chongqing Twin-city Economic Circle.
Line52-65 “FVC is a key indicator of regional ecosystem vitality. Exploring the impact of land use and climate on FVC will help to understand the coupling mechanism of human activities and ecological processes under specific conditions, and provide strategies for regional sustainable development. Chengdu-Chongqing Economic Circle (CCEC) region is the ecological barrier in the upper reaches of the Yangtze River, and has a very high ecological status. However, the early pursuit of economic growth has brought ecological problems with the advancement of industrialization and urbanization. Therefore, in order to deal with the risk of ecological degradation in the CCEC region, it is necessary to study the response of future FVC to land use and climate changes. Based on the future climate and land use data, this paper analyzes the change of FVC in the CCEC region. Theoretically, it is helpful to expand the thinking of cellular automata theory in land space simulation and improve the theoretical system of ecological restoration; In practice, it is beneficial to take targeted measures for ecological restoration in the CCEC region.“
（6）why we should study the “asymmetric impacts of climate and land-use change on vegetation cover in the Chengdu-Chongqing Twin-city Economic Circle”.
Response: Thanks for the comments. We accepted the suggestions. We re-examined the findings and found that the use of asymmetric effects was a bit overstated. In this paper, we studied the superposition effect and compensation effect of land use and climate defense on FVC. The superposition effect indicates that the impact of climate change and land use change on FVC is positive or negative at the same time, and the compensation effect indicates that the impact of climate change and land use change on FVC is positive and negative at the same time. We revised the full text, including the title which is changed to "Impacts of climate and land-use change on fraction vegetation coverage based on PLUS-Dimidiate Pixel model".
Line 87-94 “The geographic detector explored the explanatory power of the driving factors of FVC, but the positive and negative effects of driving factors cannot be revealed. At the same time, previous studies mostly analyzed the effects of land use and climate changes on FVC. Therefore, this paper explored the response mechanism of FVC to future climate and land-use changes by coupling PLUS model and dimidiate pixel model. In addition, a quantitative analysis of the correlation between multiple driving factors and FVC was performed to reveal the positive and negative effects of both land-use and climate changes.”
Line 314-359 “The impacts of land use and climate change on FVC are superimposed by ArcGIS software to identify the space of positive and negative effects.The analysis of the impacts of climate and land-use change on FVC in the CCEC region was performed in the research (Fig. 7). FVC exhibited significantly negative and positive responses to climate and land-use change, respectively. It can be seen that under the SSP245 scenario, land-use change exhibits an enhancement effect on FVC in 6.33% of the total study area, with an area of 11783.4km². 10.03% of the total study area subjects to FVC degradation due to land-use change, with corresponding area of 18658.14km². Climate change exhibits significantly negative and positive responses to FVC. It exhibits an enhancement effect on FVC in 40.70% of the total study area, with an area of 75722.23km². 59.30% of the total study area subjects to FVC degradation due to climate change, with corresponding area of 110345.38km². Obviously, climate and land-use change jointly in-creased or decreased cumulative percentage of FVC area. It is necessary to weigh the pros and cons of the effects of climate and land-use change on FVC to analyze their interactive effects. Thus, results in Table 2 were used to recalculate with the raster calculator in Arcgis. If the effects of climate and land-use on FVC are both positive or negative, then there is a superposition effect. If the effects of climate and land use on FVC are reversed, indicating a compensation effect between them. The compensation effect of one factor to another was evaluated by its net contribution to the variance of FVC. Then the spatial distribution and change area of FVC under the future scenario were visualized.
Based on the panel model, the variable relationship between FVC, land use, and climate was revealed. The land use and climate change data were overlaid and analyzed using ArcGIS software to quantify the impact of land use and climate change on FVC.The obtained results indicated that FVC value in the CCEC region also changes as a consequence of interactive effects from climate and land-use change. As shown in Figure 7c, the area in which FVC affected by climate change compensates for the area in which FVC affected by land-use change is 9733.23km², accounting for 5.23%. The ar-ea in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 7594.33km², accounting for 4.08%. Land-use and climate change can also promote the improvement of FVC jointly, and the area with positive superposition effect is 65989km², accounting for 35.47%. The area with negative su-perposition effect is 102751.05km², accounting for 55.22%.
Due to the difficulty in simulating land policies and management, it was considered that the land-use change under the SSP585 scenario is similar to that under the SSP245 scenario. The area of FVC improved by climate change is 86804.93km², ac-counting for 46.65% of the study area. The area in which FVC declined due to climate change is 99262.68km², accounting for 53.35% of the study area. For the interaction of land-use and climate change on FVC show that the area in which FVC affected by climate change compensates for the area in which FVC affected by land use change is 10,698.95km², accounting for 5.75%. The area in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 6851.74km², ac-counting for 3.68%. The area with positive superposition effect of land use change and climate change on FVC is 76105.98km², accounting for 40.90%. The area with negative superposition effect of land-use changes and climate change on FVC is 92410.94km², accounting for 49.67%.”
（7）What are the practical significance of the study of this area and what are the theoretical significance. All these need to be answered by the authors.
Response：Thanks for the comments. We accepted the suggestions. The causes and significance of studying the effects of land use and climate change on vegetation cover were supplemented, and the theoretical and practical significance were explained in Line 51-65 .
Line 52-65 “FVC is a key indicator of regional ecosystem vitality. Exploring the impact of land use and climate on FVC will help to understand the coupling mechanism of human activities and ecological processes under specific conditions, and provide strategies for regional sustainable development. Chengdu-Chongqing Economic Circle (CCEC) region is the ecological barrier in the upper reaches of the Yangtze River, and has a very high ecological status. However, the early pursuit of economic growth has brought ecological problems with the advancement of industrialization and urbanization. Therefore, in order to deal with the risk of ecological degradation in (CCEC) region, it is necessary to study the response of future FVC to land use and climate changes. Based on the future climate and land use data, this paper analyzes the change of FVC in (CCEC) region. Theoretically, it is helpful to expand the thinking of cellular automata theory in land space simulation and improve the theoretical system of ecological restoration; In practice, it is beneficial to take targeted measures for ecological restoration in (CCEC) region.”
2 L97, Figure 1 also needs to show the current land use status of the study area.
Response: Thanks for the comments. We accepted the suggestions. The land use status of the study area was supplemented in Figure 1.
3 L233-L240, please show a comparison between the current land use map and the simulation for 2020.
Response: Thanks for the comments. We accepted the suggestions. The comparison between the current land use map and the 2020 model map was supplemented in Figure 5a
4 L252-L272, How is the impact of climate on land use represented in the land use simulation for 2050?
Response: Thanks for the comments. We accepted the suggestions. In this paper, the land use data of 2050 was simulated by the PLUS model, followed by the climate change data of SSP245 and SSP585 in 2050. At the historical data level, the panel model was used to explore the effects of land use and climate change on FVC, the change trend of land use and climate change on FVC in 2050 was simulated. In this paper, the PLUS model was used to simulate the land use in 2050 under the historical development trend. There were certain limitations in this aspect of the paper, which were discussed in the discussion part of the research limitations and future prospects.
5.L278-L318, how is the asymmetric effect of climate and land use change on vegetation cover represented?
Response: Thanks for the comments. We accepted the suggestions. We re-examined the findings and found that the use of asymmetric effects was a bit overstated. In this paper, we studied the superposition effect and compensation effect of land use and climate defense on FVC. The superposition effect indicates that the impact of climate change and land use change on FVC is positive or negative at the same time, and the compensation effect indicates that the impact of climate change and land use change on FVC is positive and negative at the same time. We revised the full text, including the title which is changed to "Impacts of climate and land-use change on fraction vegetation coverage based on PLUS-Dimidiate Pixel model".
Line 87-94 “The geographic detector explored the explanatory power of the driving factors of FVC, but the positive and negative effects of driving factors cannot be revealed. At the same time, previous studies mostly analyzed the effects of land use and climate changes on FVC. Therefore, this paper explored the response mechanism of FVC to future climate and land-use changes by coupling PLUS model and dimidiate pixel model. In addition, a quantitative analysis of the correlation between multiple driving factors and FVC was performed to reveal the positive and negative effects of both land-use and climate changes.”
Line 314-359 “The impacts of land use and climate change on FVC are superimposed by ArcGIS software to identify the space of positive and negative effects.The analysis of the impacts of climate and land-use change on FVC in the CCEC region was performed in the research (Fig. 7). FVC exhibited significantly negative and positive responses to climate and land-use change, respectively. It can be seen that under the SSP245 scenario, land-use change exhibits an enhancement effect on FVC in 6.33% of the total study area, with an area of 11783.4km². 10.03% of the total study area subjects to FVC degradation due to land-use change, with corresponding area of 18658.14km². Climate change exhibits significantly negative and positive responses to FVC. It exhibits an enhancement effect on FVC in 40.70% of the total study area, with an area of 75722.23km². 59.30% of the total study area subjects to FVC degradation due to climate change, with corresponding area of 110345.38km². Obviously, climate and land-use change jointly in-creased or decreased cumulative percentage of FVC area. It is necessary to weigh the pros and cons of the effects of climate and land-use change on FVC to analyze their interactive effects. Thus, results in Table 2 were used to recalculate with the raster calculator in Arcgis. If the effects of climate and land-use on FVC are both positive or negative, then there is a superposition effect. If the effects of climate and land use on FVC are reversed, indicating a compensation effect between them. The compensation effect of one factor to another was evaluated by its net contribution to the variance of FVC. Then the spatial distribution and change area of FVC under the future scenario were visualized.
Based on the panel model, the variable relationship between FVC, land use, and climate was revealed. The land use and climate change data were overlaid and analyzed using ArcGIS software to quantify the impact of land use and climate change on FVC.The obtained results indicated that FVC value in the CCEC region also changes as a consequence of interactive effects from climate and land-use change. As shown in Figure 7c, the area in which FVC affected by climate change compensates for the area in which FVC affected by land-use change is 9733.23km², accounting for 5.23%. The area in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 7594.33km², accounting for 4.08%. Land-use and climate change can also promote the improvement of FVC jointly, and the area with positive superposition effect is 65989km², accounting for 35.47%. The area with negative su-perposition effect is 102751.05km², accounting for 55.22%.
Due to the difficulty in simulating land policies and management, it was considered that the land-use change under the SSP585 scenario is similar to that under the SSP245 scenario. The area of FVC improved by climate change is 86804.93km², ac-counting for 46.65% of the study area. The area in which FVC declined due to climate change is 99262.68km², accounting for 53.35% of the study area. For the interaction of land-use and climate change on FVC show that the area in which FVC affected by climate change compensates for the area in which FVC affected by land use change is 10,698.95km², accounting for 5.75%. The area in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 6851.74km², ac-counting for 3.68%. The area with positive superposition effect of land use change and climate change on FVC is 76105.98km², accounting for 40.90%. The area with negative superposition effect of land-use changes and climate change on FVC is 92410.94km², accounting for 49.67%.”
6 Please add to the discussion section on the shortcomings and future outlook of the manuscript.
Response: Thanks for the comments. We accepted the suggestions. The research limitations and future prospects were added in the discussion section of the article in Line 467-478.
Line 471-480 “It had certain theoretical value and practical significance to simulate the future FVC of the CCEC region, and to explore the response of FVC to land use and climate changes, but there were certain limitations. First of all, for the content of land planning, policy and management was difficult to quantify, the trend of land use change in 2050 were simulated based on the data from 2000 to 2020. Future research needs to consider more land indicators to simulate land use change under different scenarios. Secondly, global scale of future climate data were used in this paper, high-resolution future climate data should be explored for future FVC simulation. Finally, FVC is also affected by human activities and natural environment in the process of regional development, so more models and data simulation should be used in the future.“
7 L398-L445, the conclusion section is written like a result and is too lengthy. Please summarize the results throughout the text and condense the concluding statements.
Response：Thanks for the comments. We accepted the suggestions. We have streamlined the conclusion section and extracted the analysis results of the article in Line 480-509.
Line482-513 “This study made projections for FVC changes in the CCEC region in 2050 by coupling PLUS model and dimidiate pixel model. The compensation and superposition effect of climate and land-use changes on the FVC were discussed. These are its conclusions:
From 2000 to 2020, the areas (71731.02km²) experiencing a reduction in FVC accounted for 38.55% of the total area, they were mainly distributed in Chengdu, Deyang, Meishan, Guang 'an, Dazhou and Chongqing. The improved areas (110490.6km²) were concentrated in Yibin, Neijiang and Zigong, accounting for 59.38%. In the past 20 years, the FVC in the CCEC region indicated an upward trend, the proportion of low coverage, extremely low coverage of the FVC decreased gradually, while the proportion of middle coverage and high coverage increased, indicating that the quality of vegetation has improved. According to the relationship between the FVC, climate and land-use changes, it can be seen that land-use changes, wind speed and temperature inhibited the increase of the FVC, while precipitation promoted the increase of the FVC.
Under the SSP245 scenario, area that demonstrating enhanced FVC covers 75489.85km², accounting for 40.57% of the total areas, compared to 46.38% under the SSP585 scenario. While areas with declined FVC value accounts for 59.43% of the total area, compared with 53.62% under the SSP585 scenario. Under the SSP245 scenario, vegetation dynamics in the investigation region are driven by the interplay of the selected factors. 90.69% of the total area are triggered by superposition effect of climate and land-use changes on FVC, while under the SSP585 scenario, the proportion is 90.57%. Areas with mutual compensation effect of climate changes and land-use changes on FVC account for 9.31% of the total area, compared with 9.43% under the SSP585 scenario.
According to the mechanism of climate and land-use changes on FVC, under the SSP245 scenario, the positive effect of climate changes on FVC can compensate for the negative effect of land-use changes on FVC, the area with such compensation effect covers 9733.23km², accounting for 5.23% of the study area. While under the SSP585 scenario, the area with such compensation effect covers 10698.95km², accounting 5.75%. The positive effect of land-use changes on FVC can also compensate for the negative effect of climate changes on FVC, the area with such compensation effect covers 7594.33km², accounting for 4.08% of the study area compared with 3.68% under the SSP585 scenario. “
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors have done a lot of work to show the relationship between FVC and climate, land-use by predicting the land use, climate and FVC in 2050. But there existed a lot of algorithm details and processing procedure details remain unclear. It makes the manuscript very hard to follow. Especially, there lack the description of the prediction method or procedure on FVC, land-use and climate, as well as the "asymmetric impact" and causal relationship between FVC and climate, land-use. Some advice or queries are listed below.
1. the data type of Figure 1 is not clear
2. Table 1 includes a lot of data types and corresponding websites. The name and data source are not clearly divided, which makes the data name hard to relate with the data source.
3. Page 4 line 123, "PLUS" should be presented in detail.
4. line 169, mistake about "... respectively s."
5. part 3.2 is more likely the correlation between FVC and climate, land-use change, rather than the impact on FVC.
6. The data of future land use and future climate are very important for this study. How did the authors get those data? what are the accuracies? These should be clearly defined in the study.
7. Page 9 line 234-235, did the future land use data simulated by CA model? The land-use level was calculated by linear regression? It is very hard to understand the processing procedure.
8. How did the authors identify the vegetation change between FVC or vegetation of land use?
9. why FVC in 2050 was simulated under two scenarios? how about land-use in 2050?
10. what is "Asymmetric impact"?
11. Lines 298-299, how did the authors get this causal relationship between FVC and climate, land-use?
12. How did Figure 7 generate? what did Figure 7 mean? especially Figure (b) and Figure(c)
13. "FVC changes in ....using the PLUS and pixel binary model" was not the same as mentioned above.
Comments on the Quality of English LanguageNo comments about the English writing quality.
Author Response
Thank you very much for the reviewers’ comments. According to their suggestions, we replied to the reviewer’s opinions one by one as follows. In document of “Response” and “Manuscripts”, blue means modified, black means unmodified.
Review 3
- the data type of Figure 1 is not clear
Response: Thanks for the comments. We accepted the suggestions and modified the content of Figure 1.
- Table 1 includes a lot of data types and corresponding websites. The name and data source are not clearly divided, which makes the data name hard to relate with the data source.
Response: Thanks for the comments. We accepted the suggestions. The data in Table 1 has been reorganized.
|
Data |
Time |
Resolution |
Source |
|
Average annual temperature |
2000、2005、2010、2015、2020 |
1km |
Resource and Environmental Science Data Platform （https: //www.resdc.cn） |
|
Average annual precipitation |
2000、2005、2010、2015、2020 |
1km |
|
|
Average annual wind speed |
2000、2005、2010、2015、2020 |
1km |
|
|
Average annual NDVI |
2000、2005、2010、2015、2020 |
1km |
|
|
Future precipitation (SSP245、SSP585) |
2050 |
50km |
|
|
Future temperature(SSP245、SSP585) |
2050 |
50km |
|
|
Soil type |
2020 |
1km |
|
|
Future wind speed (SSP245、SSP585) |
2050 |
50km |
National Tibetan Plateau / Third Pole Environment Data Center （https://data.tpdc.ac.cn/home） |
|
Elevation |
2020 |
30m |
Geospatial Data Cloud (http://www.gscloud.cn) |
|
Slop |
2020 |
30m |
|
|
Average land use 2000-2020 |
2000、2005、2010、2015、2020 |
30m |
Resource and Environmental Science Data Platform （https: //www.resdc.cn） |
|
GDP |
2015、2020 |
1km |
|
|
Population density |
2015、2020 |
1km |
|
|
River |
2020 |
|
|
|
Road |
2020 |
|
OpenStreetMap (https://www.openstreetmap.org) |
|
Point Of Interest (government office and railway station) |
2020 |
|
Guihuayun（http://guihuayun.com/poi/） |
- Page 4 line 123, "PLUS" should be presented in detail.
Response: Thanks for the comments. We accepted the suggestions and supplemented the description of the PLUS model in the research framework in Line 146-148.
Line 146-148 “The PLUS model is a simulation model of land use change generated by patches, which is based on the principle of cellular automata, it simulates land use changes by analyzing the historical data of land use and driving factors.“
- line 169, mistake about "... respectively s."
Response：Thanks for the comments. We accepted the suggestions and corrected the syntax error in Line 192.
Line 188 “By summarizing the previous research, NDVI values with cumulative frequencies of about 5% and 95% were selected asand , respectively.“
- part 3.2 is more likely the correlation between FVC and climate, land-use change, rather than the impact on FVC.
Response：Thanks for the comments. We accepted the suggestions. This study compared the future land use and climate with those of 2020 to get the future land use and climate changes. The variable relationship between land use and climate and vegetation cover could be obtained by the panel model and the impact of land use and climate changes on vegetation cover can be quantified by multiplying the correlation coefficient.
Line 253-256 “Comparing the future land use and climate with those of 2020, this paper calculated the future land use and climate change, and multiply it by the correlation coefficient to quantify the impact of land use and climate on FVC.“
- The data of future land use and future climate are very important for this study. How did the authors get those data? what are the accuracies? These should be clearly defined in the study.
Response: Thanks for the comments. We accepted the suggestions. A source description of future land use and climate data has been added to the article. The future land use data was simulated by the PLUS model with an accuracy of 100m. Future climate data were taken from the Coupled Model Intercomparison Project Phase 6 (CMIP6) with an accuracy of 50km in Line 133-139
“The future climate data used in this study were from the Coupled Model Intercomparison Project Phase 6 (CMIP6). SSP245 and SSP585 represent two scenarios. The SSP245 scenario represents the medium pathway of future greenhouse gas emissions and assumes that climate protection measures are being taken. The SSP585 scenario represents the upper boundary of the range of scenarios and promotes rapid economic growth through activities such as the extraction of fossil fuels and energy. Land use data in 2050 are from the simulation results of PLUS model.“
- Page 9 line 234-235, did the future land use data simulated by CA model? The land-use level was calculated by linear regression? It is very hard to understand the processing procedure.
Response: Thanks for the comments. We accepted the suggestions. Based on the land use data from 2000 to 2015, this paper calculated the number of patches of various types of land in 2020 by linear regression, and then simulated the spatial distribution of land use by CA model in Line 262-264.
Line 262-264 “Based on the land use data from 2000 to 2015, the patch number of various types of land in 2020 were calculated based on linear regression, and then the spatial distribution of land use was simulated by CA model. “
- How did the authors identify the vegetation change between FVC or vegetation of land use?
Response：Thanks for the comments. We accepted the suggestions.This study compared the future land use and climate with those of 2020 to get the future land use and climate changes. The variable relationship between land use and climate and vegetation cover could be obtained by the panel model and the impact of land use and climate changes on vegetation cover can be quantified by multiplying the correlation coefficient.
Line 253-256 “Comparing the future land use and climate with those of 2020, this paper calculated the future land use and climate change, and multiply it by the correlation coefficient to quantify the impact of land use and climate on FVC.“
- why FVC in 2050 was simulated under two scenarios? how about land-use in 2050?
Response：Thanks for the comments. We accepted the suggestions. This paper simulated land use change under a single scenario and simulated climate change under SSP245 and SSP585 scenarios. The temperature, precipitation and wind speed data of 2050 SSP245 and SSP585 under two future scenarios released by the Coupled Model Intercomparison Project Phase 6 (CMIP6) were obtained from the Resource Science Data Center and the National Tibetan Plateau Data Center, and the future vegetation cover was simulated through the panel model coupling land use and climate change. The land use in 2050 was simulated according to the PLUS model. The land use change in 2050 was simulated and predicted according to the historical development trend, while the vegetation cover change in 2050 was simulated under two different climate scenarios.
Line284-286 “The land use changes in 2050 is simulated and predicted according to the historical development trend, while the FVC changes in 2050 is simulated under two different climate scenarios. “
- what is "Asymmetric impact"?
Response: Thanks for the comments. We accepted the suggestions. We re-examined the findings and found that the use of asymmetric effects was a bit overstated. In this paper, we studied the superposition effect and compensation effect of land use and climate defense on FVC. The superposition effect indicates that the impact of climate change and land use change on FVC is positive or negative at the same time, and the compensation effect indicates that the impact of climate change and land use change on FVC is positive and negative at the same time. We revised the full text, including the title which is changed to "Impacts of climate and land-use change on fraction vegetation coverage based on PLUS-Dimidiate Pixel model".
Line 87-94 “The geographic detector explored the explanatory power of the driving factors of FVC, but the positive and negative effects of driving factors cannot be revealed. At the same time, previous studies mostly analyzed the effects of land use and climate changes on FVC. Therefore, this paper explored the response mechanism of FVC to future climate and land-use changes by coupling PLUS model and dimidiate pixel model. In addition, a quantitative analysis of the correlation between multiple driving factors and FVC was performed to reveal the positive and negative effects of both land-use and climate changes.”
Line 314-359 “The impacts of land use and climate change on FVC are superimposed by ArcGIS software to identify the space of positive and negative effects.The analysis of the impacts of climate and land-use change on FVC in the CCEC region was performed in the research (Fig. 7). FVC exhibited significantly negative and positive responses to climate and land-use change, respectively. It can be seen that under the SSP245 scenario, land-use change exhibits an enhancement effect on FVC in 6.33% of the total study area, with an area of 11783.4km². 10.03% of the total study area subjects to FVC degradation due to land-use change, with corresponding area of 18658.14km². Climate change exhibits significantly negative and positive responses to FVC. It exhibits an enhancement effect on FVC in 40.70% of the total study area, with an area of 75722.23km². 59.30% of the total study area subjects to FVC degradation due to climate change, with corresponding area of 110345.38km². Obviously, climate and land-use change jointly in-creased or decreased cumulative percentage of FVC area. It is necessary to weigh the pros and cons of the effects of climate and land-use change on FVC to analyze their interactive effects. Thus, results in Table 2 were used to recalculate with the raster calculator in Arcgis. If the effects of climate and land-use on FVC are both positive or negative, then there is a superposition effect. If the effects of climate and land use on FVC are reversed, indicating a compensation effect between them. The compensation effect of one factor to another was evaluated by its net contribution to the variance of FVC. Then the spatial distribution and change area of FVC under the future scenario were visualized.
Based on the panel model, the variable relationship between FVC, land use, and climate was revealed. The land use and climate change data were overlaid and analyzed using ArcGIS software to quantify the impact of land use and climate change on FVC.The obtained results indicated that FVC value in the CCEC region also changes as a consequence of interactive effects from climate and land-use change. As shown in Figure 7c, the area in which FVC affected by climate change compensates for the area in which FVC affected by land-use change is 9733.23km², accounting for 5.23%. The area in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 7594.33km², accounting for 4.08%. Land-use and climate change can also promote the improvement of FVC jointly, and the area with positive superposition effect is 65989km², accounting for 35.47%. The area with negative su-perposition effect is 102751.05km², accounting for 55.22%.
Due to the difficulty in simulating land policies and management, it was considered that the land-use change under the SSP585 scenario is similar to that under the SSP245 scenario. The area of FVC improved by climate change is 86804.93km², ac-counting for 46.65% of the study area. The area in which FVC declined due to climate change is 99262.68km², accounting for 53.35% of the study area. For the interaction of land-use and climate change on FVC show that the area in which FVC affected by climate change compensates for the area in which FVC affected by land use change is 10,698.95km², accounting for 5.75%. The area in which FVC affected by land-use change compensates for the area in which FVC affected by climate change is 6851.74km², ac-counting for 3.68%. The area with positive superposition effect of land use change and climate change on FVC is 76105.98km², accounting for 40.90%. The area with negative superposition effect of land-use changes and climate change on FVC is 92410.94km², accounting for 49.67%.”
11.Lines 298-299, how did the authors get this causal relationship between FVC and climate, land-use?
Response：Thanks for the comments. We accepted the suggestions. Based on the variable relationship between vegetation cover, land use and climate revealed by panel model, the overlay analysis of land use and climate change data was carried out by Arcgis software to quantify the impact of land use and climate change on FVC.
Line 253-256 “Comparing the future land use and climate with those of 2020, this paper calculated the future land use and climate change, and multiply it by the correlation coefficient to quantify the impact of land use and climate on FVC.“
- How did Figure 7 generate? what did Figure 7 mean? especially Figure (b) and Figure(c)
Response：Thanks for the comments. We accepted the suggestions. The impacts of land use and climate changes on FVC were superimposed by ArcGIS software to identify the space of positive and negative effects. Figure 7 (a) showed the impact of climate changes on FVC, Figure 7 (b) showed the impact of land use changes on FVC, and Figure 7 (c) showed the joint impact of land use and climate changes on FVC. In Figure 7 (c), "+" indicated that FVC has increased, "-" indicated that FVC has decreased, "/" indicated that FVC has not changed.
- "FVC changes in ....using the PLUS and pixel binary model" was not the same as mentioned above.
Response：Thanks for the comments. We accepted the suggestions. In this study, PLUS model and pixel binary model were coupled to simulate vegetation cover in the CCEC region in 2050
Line 480-481 “This study made projections for FVC changes in the CCEC region in 2050 by coupling PLUS model and immediate pixel model.“
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThanks the authors for their thorough consideration of my review comments and for revising the manuscript accordingly. I now recommend that Sustainability journal accept and publish this manuscript without delay. Congratulations to the authors on their commendable work!
Author Response
Thank you very much for the reviewers’ comments. According to their suggestions, we replied to the reviewer’s opinions one by one as follows. In document of “Response” and “Manuscripts”, purple means modified, black means unmodified. (1) When the abbreviation of "PLUS" is first time presented in line 77, it should be described as the Full name. Response：Thanks for the comments. We accepted the suggestions. Line 78-81 The full name of PLUS model is Patch-Generating Land Use Simulation (PLUS) model. Line 78-81 “Patch-Generating Land Use Simulation (PLUS) model can simulate the evolution of land-use patches with high accuracy, and can quantitatively describe the nonlinear relationship between various driving factors and land type change [28].” (2) Indent format problem in line 159. Response：Thanks for the comments. We accepted the suggestions. Line 163 format problem was modified (3) The formula should be centered. Response：Thanks for the comments. We accepted the suggestions. Line 162 formula（1）was centered Line 173 formula（2）was centered Line 183 formula（3）was centered Line 199 formula（4）was centered Line 209 formula（5）was centered (4) The PLUS model is shown in the title. But there is no explanation in the abstract or introduction as to why this method was selected for analysis. Response：Thanks for the comments. We accepted the suggestions. Line78-83 The reason for choosing PLUS model is added in the introduction. Line14-17 In the abstract, the coupled PLUS model and Dimidiate Pixel model are added to simulate the future vegetation coverage. Line78-83 “Patch-Generating Land Use Simulation (PLUS) model can simulate the evolution of land-use patches with high accuracy, and can quantitatively describe the nonlinear re-lationship between various driving factors and land type change [28]. Compared with other models, the PLUS model reflects the evolution of land use more realistically, so the PLUS model is selected to simulate the future land use in the CCEC region.” Line14-17 “This study simulated the fraction vegetation coverage in 2050 through coupling Patch-Generating Land Use Simulation (PLUS) model and Dimidiate Pixel model, and explored the effects of climate and land-use change on fraction vegetation coverage in the Chengdu-Chongqing Economic Circle region.”
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThere are some minor problems.
(1) When the abbreviation of "PLUS" is first time presented in line 77, it should be described as the Full name.
(2) Indent format problem in line 159.
(3) The formula should be centered.
(4) The PLUS model is shown in the title. But there is no explanation in the abstract or introduction as to why this method was selected for analysis.
Author Response
Thank you very much for the reviewers’ comments. According to their suggestions, we replied to the reviewer’s opinions one by one as follows. In document of “Response” and “Manuscripts”, purple means modified, black means unmodified.
(1) When the abbreviation of "PLUS" is first time presented in line 77, it should be described as the Full name.
Response：Thanks for the comments. We accepted the suggestions. Line 78-81 The full name of PLUS model is Patch-Generating Land Use Simulation (PLUS) model.
Line 78-81 “Patch-Generating Land Use Simulation (PLUS) model can simulate the evolution of land-use patches with high accuracy, and can quantitatively describe the nonlinear relationship between various driving factors and land type change [28].”
(2) Indent format problem in line 159.
Response：Thanks for the comments. We accepted the suggestions.
Line 163 format problem was modified
(3) The formula should be centered.
Response：Thanks for the comments. We accepted the suggestions.
Line 162 formula（1）was centered
Line 173 formula（2）was centered
Line 183 formula（3）was centered
Line 199 formula（4）was centered
Line 209 formula（5）was centered
(4) The PLUS model is shown in the title. But there is no explanation in the abstract or introduction as to why this method was selected for analysis.
Response：Thanks for the comments. We accepted the suggestions. Line78-83 The reason for choosing PLUS model is added in the introduction. Line14-17 In the abstract, the coupled PLUS model and Dimidiate Pixel model are added to simulate the future vegetation coverage.
Line78-83 “Patch-Generating Land Use Simulation (PLUS) model can simulate the evolution of land-use patches with high accuracy, and can quantitatively describe the nonlinear re-lationship between various driving factors and land type change [28]. Compared with other models, the PLUS model reflects the evolution of land use more realistically, so the PLUS model is selected to simulate the future land use in the CCEC region.”
Line14-17 “This study simulated the fraction vegetation coverage in 2050 through coupling Patch-Generating Land Use Simulation (PLUS) model and Dimidiate Pixel model, and explored the effects of climate and land-use change on fraction vegetation coverage in the Chengdu-Chongqing Economic Circle region.”
Author Response File: Author Response.pdf
