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Land
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Climate and Carbon Cycle Impact Assessment of Land Policies, Prospects...
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Climate and Carbon Cycle Impact Assessment of Land Policies, Prospects and Challenges

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Use, Impact Assessment and Sustainability".

Deadline for manuscript submissions: 15 July 2026 | Viewed by 4729

Special Issue Editors

Dr. Jian Zhang

E-Mail Website
Guest Editor
Research Center for Land Use and Ecological Security Governance in Mining Areas, China University of Mining and Technology, Xuzhou 221116, China
Interests: land economy and policies; rural land property rights and systems; economic and social performance of the land market
Prof. Dr. Xin Li

E-Mail Website1 Website2
Guest Editor
Research Center for Land Use and Ecological Security Governance in Mining Areas, China University of Mining and Technology, Xuzhou 221116, China
Interests: land use and policies; spatial planning; land information; remote sensing monitoring
Prof. Dr. Hossein Azadi

E-Mail Website
Guest Editor
Department of Geography, Ghent University, 9000 Ghent, Belgium
Interests: land governance; land use policy; land use planning; land degradation & development; human geography; agricultural landscape; resilience; decision support systems; sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land use policies are increasingly being recognized as pivotal drivers of climate change mitigation and carbon cycle dynamics. While land management practices and carbon policies have been extensively debated, the impacts of land management policies on carbon emissions and the adaptive practices in land management for climate change remain underexplored. Land management policies include a series of related policies on agricultural production, land use, spatial planning, etc. How these policies affect carbon emissions from agricultural production, land use/cover changes, crop structure, etc., as well as how to improve the adaptability of land policies to climate change and carbon reduction, have significant research and policy implications.

The goal of this Special Issue is to collect papers (original research articles and review papers) to provide insights into the impact of land management policies on carbon emissions and carbon sinks, as well as the simulations and the innovation of land systems to adapt to climate change and carbon neutrality goals. A wide range of agricultural, land use, ecological compensation, environment protection, spatial planning, and other policies are welcomed.

This Special Issue will welcome manuscripts that link the following themes:

  • Review and discussion on carbon reduction and climate adaptive land management policies.
  • Agricultural land use and policies on carbon emissions and carbon sinks.
  • Urban land use and policies on carbon emissions and carbon sinks.
  • Carbon and climate simulation of land use and policies.
  • Land management policies adaptive to climate change and carbon reduction.
  • The synergy between land policies and carbon reduction practices.

We look forward to receiving your original research articles and reviews.

Dr. Jian Zhang
Prof. Dr. Xin Li
Prof. Dr. Hossein Azadi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • land use policy
  • carbon reduction
  • climate change
  • carbon and climate simulation
  • agricultural land
  • urban land use
  • land management

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Published Papers (5 papers)

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Research

30 pages, 22668 KB  
Article
Coupling System Dynamics and Mixed Cellular Automata for Carbon-Economic Optimization in Coastal Zones: A Multi-Scenario Simulation Under SSP-RCPs
by Jiahui Chen, Yuting Jiang, Wenrui Yu and Gang Yang
Land 2026, 15(4), 648; https://doi.org/10.3390/land15040648 - 15 Apr 2026
Viewed by 289
Abstract
Rising greenhouse gas concentrations have exacerbated global warming, elevating the importance of land use and land cover (LULC) changes in achieving carbon neutrality. This is especially true in coastal areas, which face dual pressures from rapid urbanization and the need to protect carbon [...] Read more.
Rising greenhouse gas concentrations have exacerbated global warming, elevating the importance of land use and land cover (LULC) changes in achieving carbon neutrality. This is especially true in coastal areas, which face dual pressures from rapid urbanization and the need to protect carbon sinks. This study developed an SD-MCCA coupling framework to predict the dynamic changes in LULC in four SSP scenarios (SSP126, SSP245, SSP370, SSP585) in the coastal zone of Zhejiang Province from 2020 to 2100. Among them, the carbon storage was estimated by the InVEST model, and the dual-target optimization was carried out using the NSGA-II algorithm. Results indicated that construction land expanded significantly across all scenarios (50.3–110.2%), leading to a decline in carbon storage. However, outcomes were highly scenario-dependent; by 2100, carbon storage under the SSP126 pathway (1032.94 Mt) was notably higher than under the SSP585 pathway (1012.90 Mt). Coastal wetlands and forests emerged as major contributors to carbon storage, exhibiting high positive contribution scores, while construction land sites show significant negative correlations. Dual-target optimization achieved collaborative improvement: the optimized SSP126 scenario increased carbon storage by 1.16%, while economic benefits increased by 9.05%. The policy proposal emphasizes the priority of the SSP126 scenario, restricts the expansion of construction land, and enforces the ecological red line of wetlands and forests, guided by the phased Pareto optimal strategy. Full article
(This article belongs to the Special Issue Climate and Carbon Cycle Impact Assessment of Land Policies, Prospects and Challenges)
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23 pages, 1709 KB  
Article
Adaptation of Maize Farmers to Climate Risk Under the Influence of Perceptions and Attitudes Towards Risk: A Case Study in Jilin Province, China
by Yujie Xia and Hongpeng Guo
Land 2026, 15(2), 314; https://doi.org/10.3390/land15020314 - 12 Feb 2026
Viewed by 436
Abstract
Agriculture is particularly vulnerable to climate change, as shifting seasonal patterns disrupt farming cycles and changing rainfall patterns, along with extreme weather events, present significant challenges. From the perspectives of risk perception and risk attitudes, this study elucidates the decision-making mechanisms underlying climate [...] Read more.
Agriculture is particularly vulnerable to climate change, as shifting seasonal patterns disrupt farming cycles and changing rainfall patterns, along with extreme weather events, present significant challenges. From the perspectives of risk perception and risk attitudes, this study elucidates the decision-making mechanisms underlying climate adaptation behaviors among maize growers in China, providing insights to inform climate adaptation policies, land management strategies, and food security protection. This study surveyed 752 maize growers in Jilin province, China, and employed factor analysis to quantify climate risk perception and risk attitudes. Using the Probit model and moderation analysis, this study examines the impact of climate risk perception on adaptive behavior and investigates the moderating effect of risk attitude on the relationship between risk perception and climate adaptation behavior. It then explores heterogeneity across production scales and generations. (1) We categorize adaptation behaviors into three types—capital-based, labor-based, and technology-based—according to the input factors involved. Climate risk perception promotes all three types of adaptation behaviors, whereas risk aversion primarily exerts a significant inhibitory effect on technology-based adaptations. (2) Risk attitudes exert a negative moderating effect on the relationship between climate risk perception and the adaptation behaviors of maize growers. Specifically, a higher propensity for risk aversion attenuates the positive influence of risk perception on labor-based and technology-based adaptation behaviors. (3) Heterogeneity analysis reveals that the moderating effect of risk attitude is more pronounced among small-scale farmers and younger generations. In contrast, it remains statistically insignificant for large-scale operators and older-generation cohorts. Therefore, it is important to enhance farmers’ awareness of climate risks by strengthening the dissemination of meteorological information and early warnings. Technical guidance should be intensified to improve maize growers’ understanding and mastery of relevant technologies. Develop targeted land-use strategies for climate change adaptation based on maize growers’ age, farm size, and geographic location. Full article
(This article belongs to the Special Issue Climate and Carbon Cycle Impact Assessment of Land Policies, Prospects and Challenges)
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20 pages, 10359 KB  
Article
Spatial and Temporal Variation of Vegetation NPP in a Typical Area of China Based on the CASA Model
by Kuankuan Cui, Fei Yang, Qiulin Dong, Zehui Wang, Tianmeng Du and Zhe Wang
Land 2026, 15(2), 237; https://doi.org/10.3390/land15020237 - 30 Jan 2026
Viewed by 356
Abstract
To host the 2022 Winter Olympics, Beijing and Zhangjiakou implemented extensive ecological restoration projects, improving the ecological quality of the region. However, detailed evidence of long-term spatiotemporal dynamics in vegetation productivity remains limited. This study employed the Carnegie–Ames–Stanford Approach (CASA) to estimate the [...] Read more.
To host the 2022 Winter Olympics, Beijing and Zhangjiakou implemented extensive ecological restoration projects, improving the ecological quality of the region. However, detailed evidence of long-term spatiotemporal dynamics in vegetation productivity remains limited. This study employed the Carnegie–Ames–Stanford Approach (CASA) to estimate the vegetation Net Primary Productivity (NPP) in the Beijing–Zhangjiakou region from 2004 to 2023, utilizing 250 m monthly NDVI data. The 30 m resolution China Land Cover Dataset (CLCD) was incorporated to mask non-vegetated pixels and refine the vegetation mask, reducing mixed-pixel effects. Spatiotemporal variations, seasonal change-point detection, interannual stability, and trend persistence were analyzed across administrative regions and land cover types. Results indicate pronounced spatial heterogeneity in NPP, with persistently high values in forest-dominated western and northern Beijing and northeastern Zhangjiakou, and lower values concentrated in Beijing’s built-up and cropland-dominated southeastern plain. Pixel-level boxplots suggest stronger intra-regional variability in Beijing than in Zhangjiakou. Across landcover types, forests generally maintain the highest NPP, while grasslands are relatively lower. Boxplots further show that shrubs exhibit the highest variability, with all types showing right-skewed distributions. Annual mean NPP increased significantly for the entire region, Beijing, and Zhangjiakou, with interannual increase rates of 3.57, 1.56, and 4.53 gC·m−2·yr−2, respectively; the lowest values occurred in 2007 and the highest in 2022. Trend maps and category statistics consistently suggest that positive trends dominate most of the region and expanded slightly during 2014–2023. BEAST analysis suggests a stable seasonal NPP cycle with no significant seasonal change points. CV-based assessment indicates generally high to extremely high stability, whereas low-stability zones are mainly associated with urban expansion areas, surrounding croplands, and parts of Zhangjiakou grasslands. Hurst results suggest that persistently increasing trends cover more than 90% of the study area, while persistently decreasing trends account for about 5.25% and are primarily linked to Beijing’s expansion zones. Full article
(This article belongs to the Special Issue Climate and Carbon Cycle Impact Assessment of Land Policies, Prospects and Challenges)
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21 pages, 4684 KB  
Article
Measurement and Scenario Simulation of Territorial Space Conflicts Under the Orientation of Carbon Neutrality in Jiangsu Province, China
by Tao Sun and Jie Guo
Land 2026, 15(1), 135; https://doi.org/10.3390/land15010135 - 9 Jan 2026
Viewed by 457
Abstract
Measuring and simulating territorial space conflicts (TSCs) for the achievement of carbon neutrality is of critical significance for formulating regional sustainable utilization of territorial resources that are inherently green and low-carbon. This study develops a TSC evaluation framework: “conflict identification–scenario simulation–carbon effect assessment”. [...] Read more.
Measuring and simulating territorial space conflicts (TSCs) for the achievement of carbon neutrality is of critical significance for formulating regional sustainable utilization of territorial resources that are inherently green and low-carbon. This study develops a TSC evaluation framework: “conflict identification–scenario simulation–carbon effect assessment”. Focusing on Jiangsu Province, we clarify the evolutionary mechanism of TSCs under carbon neutrality goals, providing a scientific basis for high-quality regional development and low-carbon spatial governance. Results show that Jiangsu’s average TSC level was categorized as “strong conflict” (0.66) during 2005–2020. For 2030, four scenarios (natural development, economic priority, ecological protection, low-carbon development) project TSCs shifting from scattered to point-like distribution, concentrating in key core areas. Corresponding projected average carbon neutrality indices are 1.10, 1.11, 1.33, and 1.11, respectively. Under the low-carbon scenario, grid units with serious TSCs decreased by 4.53% compared to 2020—higher than natural development and economic priority scenarios, but lower than the ecological protection scenario (12.45%). Consequently, the low-carbon development scenario can optimally mitigate land use conflicts while maintaining carbon balance. This research provides robust data support for Jiangsu’s sustainable coordinated development and informs efficient land use and regional ecological security. Full article
(This article belongs to the Special Issue Climate and Carbon Cycle Impact Assessment of Land Policies, Prospects and Challenges)
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27 pages, 5886 KB  
Article
Green Public Procurement and Its Influence on Urban Carbon Emission Intensity: Spatial Spillovers Across 285 Prefectural Cities in China
by Li Wang, Hongxuan Wu and Jian Zhang
Land 2025, 14(8), 1545; https://doi.org/10.3390/land14081545 - 27 Jul 2025
Cited by 3 | Viewed by 2304
Abstract
Green public procurement (GPP) is a pivotal policy instrument for advancing urban low-carbon transitions. Using panel data from 285 Chinese cities (2015–2023), this study employs a panel fixed-effects model, mediation analysis, and spatial Durbin model to assess the impact, influencing mechanisms, and spatial [...] Read more.
Green public procurement (GPP) is a pivotal policy instrument for advancing urban low-carbon transitions. Using panel data from 285 Chinese cities (2015–2023), this study employs a panel fixed-effects model, mediation analysis, and spatial Durbin model to assess the impact, influencing mechanisms, and spatial spillover effects of GPP on urban carbon emissions intensity. The key findings reveal the following: (1) a 1% increase in GPP implementation is associated with a 1.360% reduction in local urban carbon emissions intensity. (2) GPP reduces urban carbon emissions intensity through urban green innovation, corporate sustainability performance, and public ecological awareness. (3) GPP exhibits significant cross-boundary spillovers, where a 1% reduction in local carbon emissions intensity induced by GPP leads to a 14.510% decline in that in neighboring cities. These results provide robust empirical evidence for integrating GPP into the urban climate governance framework. Furthermore, our findings offer practical insights for optimizing the implementation of GPP policies and strengthen regional cooperation in carbon reduction. Full article
(This article belongs to the Special Issue Climate and Carbon Cycle Impact Assessment of Land Policies, Prospects and Challenges)
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