Land | Special Issue : Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization

Research

30 pages, 5648 KiB

Open AccessArticle

Sub-District Level Spatiotemporal Changes of Carbon Storage and Driving Factor Analysis: A Case Study in Beijing

by Yirui Zhang, Shouhang Du, Linye Zhu, Tianzhuo Guo, Xuesong Zhao and Junting Guo

Land 2025, 14(1), 151; https://doi.org/10.3390/land14010151 - 13 Jan 2025

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Analyzing the current trends and causes of carbon storage changes and accurately predicting future land use and carbon storage changes under different climate scenarios is crucial for regional land use decision-making and carbon management. This study focuses on Beijing as its study area [...] Read more.

Analyzing the current trends and causes of carbon storage changes and accurately predicting future land use and carbon storage changes under different climate scenarios is crucial for regional land use decision-making and carbon management. This study focuses on Beijing as its study area and introduces a framework that combines the Markov model, the Patch-based Land Use Simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to assess carbon storage at the sub-district level. This framework allows for a systematic analysis of land use and carbon storage spatiotemporal evolution in Beijing from 2000 to 2020, including the influence of driving factors on carbon storage. Moreover, it enables the simulation and prediction of land use and carbon storage changes in Beijing from 2025 to 2040 under various scenarios. The results show the following: (1) From 2000 to 2020, the overall land use change in Beijing showed a trend of “Significant decrease in cropland area; Forest increase gradually; Shrub and grassland area increase first and then decrease; Decrease and then increase in water; Impervious expands in a large scale”. (2) From 2000 to 2020, the carbon storage in Beijing showed a “decrease-increase” fluctuation, with an overall decrease of 1.3 Tg. In future carbon storage prediction, the ecological protection scenario will contribute to achieving the goals of carbon peak and carbon neutrality. (3) Among the various driving factors, slope has the strongest impact on the overall carbon storage in Beijing, followed by Human Activity Intensity (HAI) and Nighttime Light Data (NTL). In the analysis of carbon storage in the built-up areas, it was found that HAI and DEM (Digital Elevation Model) have the strongest effect, followed by NTL and Fractional Vegetation Cover (FVC). The findings from this study offer valuable insights for the sustainable advancement of ecological conservation and urban development in Beijing. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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24 pages, 28228 KiB

Open AccessArticle

Spatio-Temporal Change in Urban Carbon Metabolism Based on Ecological Network Analysis: A Case Study in the Beijing–Tianjin–Hebei Urban Agglomeration, China

by Fang Xu and Xiaoyou Guo

Land 2024, 13(12), 2252; https://doi.org/10.3390/land13122252 - 23 Dec 2024

Viewed by 571

Abstract

Urban carbon emissions significantly contribute to climate change, exacerbating environmental issues such as global warming. Understanding carbon metabolism is vital for identifying key emission sources and implementing targeted mitigation strategies. This study presents an innovative carbon metabolism analysis framework that integrates an ecological [...] Read more.

Urban carbon emissions significantly contribute to climate change, exacerbating environmental issues such as global warming. Understanding carbon metabolism is vital for identifying key emission sources and implementing targeted mitigation strategies. This study presents an innovative carbon metabolism analysis framework that integrates an ecological network analysis (ENA) with land use dynamics, enriching the theoretical system and providing policy recommendations for sustainable urban development. We investigated carbon metabolism in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA) from 2000 to 2020 using land use and statistical data. The ENA method quantified the ecological relationships between land use compartments. Our findings revealed that industrial and transportation land exhibited the highest carbon emission density, while forest land demonstrated the highest carbon sequestration density. Notably, the negative net horizontal carbon flow indicated that land use changes exacerbated the disorder of carbon metabolism. The increasing mutualism index suggested a reduction in the negative impacts of land use changes on carbon metabolism. This study highlights the importance of spatial planning in transforming ecological relationships and provides a comprehensive understanding of carbon metabolism dynamics influenced by land use changes. The insights gained can inform effective mitigation strategies in the BTHUA and similar urban agglomerations, ultimately contributing to sustainable urban development. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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19 pages, 14781 KiB

Open AccessArticle

Characteristics of Spatial Correlation Network Structure and Carbon Balance Zoning of Land Use Carbon Emission in the Tarim River Basin

by Zhe Gao, Jianming Ye, Xianwei Zhu, Miaomiao Li, Haijiang Wang and Mengmeng Zhu

Land 2024, 13(11), 1952; https://doi.org/10.3390/land13111952 - 19 Nov 2024

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Abstract

An accurate understanding of the structure of spatial correlation networks of land use carbon emissions (LUCEs) and carbon balance zoning plays a guiding role in promoting regional emission reductions and achieving high-quality coordinated development. In this study, 42 counties in the Tarim River [...] Read more.

An accurate understanding of the structure of spatial correlation networks of land use carbon emissions (LUCEs) and carbon balance zoning plays a guiding role in promoting regional emission reductions and achieving high-quality coordinated development. In this study, 42 counties in the Tarim River Basin from 2002 to 2022 were chosen as samples (Corps cities were excluded due to missing statistics). The LUCE spatial correlation network characteristics and carbon balance zoning were analyzed by using the Ecological Support Coefficient (ESC), Social Network Analysis (SNA), and Spatial Clustering Data Analysis (SCDA), and a targeted optimization strategy was proposed for each zone. The results of the study indicate the following: (1) The LUCEs showed an overall upward trend, but the increase in LUCEs gradually slowed down, presenting a spatial characteristic of “high in the mid-north and low at the edges”. In addition, the ESC showed an overall decreasing trend, with a spatial characteristic opposite to that of the LUCEs. (2) With an increasingly close spatial LUCE correlation network in the Tarim River Basin, the network structure presented better accessibility and stability, but the individual network characteristics differed significantly. Aksu City, Korla City, Bachu County, Shache County, Hotan City, and Kuqa City, which were at the center of the network, displayed a remarkable ability to control and master the network correlation. (3) Based on the carbon balance analysis, the counties were subdivided into six carbon balance functional zones and targeted synergistic emission reduction strategies were proposed for each zone to promote fair and efficient low-carbon transformational development among the regions. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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22 pages, 11105 KiB

Open AccessArticle

A Simulation-Based Prediction of Land Use Change Impacts on Carbon Storage from a Regional Imbalance Perspective: A Case Study of Hunan Province, China

by Jingyi Zhang, Hanqi Ding, Jingkun Xu and Bohong Zheng

Land 2024, 13(10), 1721; https://doi.org/10.3390/land13101721 - 20 Oct 2024

Cited by 2 | Viewed by 1084

Abstract

Land use imbalances are a critical driving factor contributing to regional disparities in carbon storage (CS). As a significant component of China’s Yangtze River Economic Belt, Hunan Province has undergone substantial shifts in land use types, resulting in an uneven distribution of ecosystem [...] Read more.

Land use imbalances are a critical driving factor contributing to regional disparities in carbon storage (CS). As a significant component of China’s Yangtze River Economic Belt, Hunan Province has undergone substantial shifts in land use types, resulting in an uneven distribution of ecosystem CS and sequestration capacity. Therefore, within the framework of the “dual carbon” strategy, examining the effects of land use changes driven by regional resource imbalances on CS holds practical importance for advancing regional sustainable development. This study focuses on Hunan Province, utilizing the PLUS-InVEST model to assess the spatiotemporal evolution of CS under land use changes from 1990 to 2020. Additionally, multiple scenario-based development modes were employed to predict county-level CS. The results indicate the following: (1) From 1990 to 2020, Hunan Province experienced continuous urban expansion, with forest land and cultivated land, which are core ecological land types, being converted into construction land. (2) Over these 30 years, the province’s total CS increased by 2.47 × 10⁸ t, with significant spatial differentiation. High-value zones were concentrated in bands along the province’s borders, while lower values were observed in the central and northern regions. The highest CS values were recorded in forested areas at the province’s periphery, whereas the lowest values were observed in the northern water bodies. (3) The scenario-based predictions revealed notable differences, with the ecological protection scenario demonstrating a substantial carbon sink effect. By prioritizing forest and cultivated land, CS could be maximized. This research provides valuable insights for enhancing CS and optimizing land use structures in regions facing resource imbalances. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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18 pages, 13052 KiB

Open AccessArticle

Multi-Scenario Simulation of Land-Use/Land-Cover Changes and Carbon Storage Prediction Coupled with the SD-PLUS-InVEST Model: A Case Study of the Tuojiang River Basin, China

by Qi Wang, Wenying Zhang, Jianguo Xia, Dinghua Ou, Zhaonan Tian and Xuesong Gao

Land 2024, 13(9), 1518; https://doi.org/10.3390/land13091518 - 19 Sep 2024

Viewed by 1414

Abstract

Land-use and land-cover changes (LUCCs) significantly impact carbon sequestration by modifying the structure and function of terrestrial ecosystems. This study utilized GIS and remote sensing techniques to forecast future LUCC patterns and their influence on regional carbon budgets, which is essential for sustainable [...] Read more.

Land-use and land-cover changes (LUCCs) significantly impact carbon sequestration by modifying the structure and function of terrestrial ecosystems. This study utilized GIS and remote sensing techniques to forecast future LUCC patterns and their influence on regional carbon budgets, which is essential for sustainable development. We devised a coupled system dynamics (SD) model integrated with a patch-generating land-use simulation (PLUS) model to simulate LUCCs under diverse future scenarios using multisource environmental data. Additionally, the InVEST model was employed to quantify carbon storage in terrestrial ecosystems. By establishing three scenarios—ecological priority (EP), highly urbanized (HU), and coordinated development (CD)—this study’s aim was to predict the LUCC patterns and carbon storage distribution of the Tuojiang River Basin (TRB), China, up to 2035. The results showed that (1) from 2000 to 2020, significant LUCCs occurred in the TRB, primarily involving the conversion of cultivated land into construction areas and forestland; (2) LUCCs had a substantial impact on carbon storage in the TRB, with the EP scenario demonstrating the highest carbon storage by 2035 due to extensive forest expansion, while the HU scenario indicated a decline in carbon storage associated with rapid urbanization; and (3) the mountainous regions of the TRB, dominated by forestland, consistently exhibited higher carbon storage, whereas the Chengdu Plain region in the upper basin displayed the lowest. In conclusion, we recommend prioritizing the CD scenario in future development strategies to balance economic growth with ecological protection while simultaneously enhancing carbon storage. Our findings offer valuable insights to shape future LUCC policies in the Tuojiang River Basin, underscoring the adaptability of the coupled model approach to a wide range of geographic scales and contexts. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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17 pages, 2048 KiB

Open AccessArticle

Analysis of the Spatial Characteristics and Influencing Factors of Large-Scale Land Acquisition Projects in Southeast Asia

by Jing Han, Xiaoting Han and Zichun Pan

Land 2024, 13(9), 1498; https://doi.org/10.3390/land13091498 - 15 Sep 2024

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Abstract

Southeast Asia is an essential region for companies carrying out large-scale land acquisitions (LSLAs). Exploring the distribution patterns and influencing factors of LSLA projects in this region is of great practical significance for summarizing the characteristics of LSLA projects in Southeast Asia, for [...] Read more.

Southeast Asia is an essential region for companies carrying out large-scale land acquisitions (LSLAs). Exploring the distribution patterns and influencing factors of LSLA projects in this region is of great practical significance for summarizing the characteristics of LSLA projects in Southeast Asia, for gaining a thorough understanding of LSLA project development rules, and for formulating reasonable policies to guide local LSLA projects. This study explores the spatial distribution and influencing factors of LSLA projects in Southeast Asia using the mean center method, the kernel density estimation method, and the grey correlation method. The findings indicate the following: Firstly, the majority of LSLA projects in Southeast Asia are located in the Indo-China Peninsula, Cambodia, Myanmar, Laos, and other countries, which represent significant regions of interest for LSLA projects in this region. Secondly, the spatial distribution of LSLA intention projects and LSLA contract projects in Southeast Asia is similar, whereas LSLA production projects differ from the former two. Thirdly, the scale of LSLA projects in Southeast Asia is closely related to the host country’s natural resources, socio-economic conditions, governance, and market environment. The total GDP, per capita arable land area, net foreign direct investment inflow, and political stability have been identified as exerting a significant influence on investment corporations’ selection of LSLA host countries. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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28 pages, 1216 KiB

Open AccessArticle

Digital Economy and Green and Low-Carbon Transformation of Land Use: Spatial Effects and Moderating Mechanisms

by Kunpeng Ai, Honghe Li, Wenjie Zhang and Xiang-Wu Yan

Land 2024, 13(8), 1172; https://doi.org/10.3390/land13081172 - 30 Jul 2024

Cited by 1 | Viewed by 1031

Abstract

The green and low-carbon transformation of land use (GLTLU) is a pressing global issue that requires urgent attention. The digital economy has emerged as a new driver for the GLTLU. However, current research mainly focuses on the measurement and environmental effects of the [...] Read more.

The green and low-carbon transformation of land use (GLTLU) is a pressing global issue that requires urgent attention. The digital economy has emerged as a new driver for the GLTLU. However, current research mainly focuses on the measurement and environmental effects of the digital economy, with less exploration of how the digital economy influences the spatial effects and regulatory mechanisms of GLTLU, particularly regarding the differential impacts and specific mechanisms at the regional level. This study uses panel data from 283 cities in China from 2011 to 2019, employing the spatial Durbin model (SDM) and the panel threshold model to examine the spatial and regulatory mechanisms of the digital economy’s impact on GLTLU. The findings reveal that digital economy promotes GLTLU not only within cities but also in surrounding regions. Robustness analyses support this conclusion. Notably, the digital economy’s positive impact on GLTLU in surrounding areas is confined to the central region of China. In contrast, the Yangtze River Delta urban agglomeration experiences a significant negative impact on GLTLU in nearby regions due to the digital economy. The study also identifies that the positive spatial spillover effect of the digital economy on GLTLU reaches its peak at a distance of 450 km. Additionally, the digital economy’s ability to promote GLTLU is contingent upon financial agglomeration levels exceeding 9.1728. Moreover, the local government’s emphasis on the digital economy and intellectual property protection enhances the digital economy’s impact on GLTLU. The promotion effect is maximized when these factors surpass the thresholds of 27.8054 and 3.5189, respectively. Overall, this study contributes to the understanding of how the digital economy influences sustainable land development, highlighting the critical role of regional factors and regulatory mechanisms in amplifying the digital economy’s positive effects on GLTLU. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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24 pages, 18611 KiB

Open AccessArticle

Optimizing Territorial Spatial Structures within the Framework of Carbon Neutrality: A Case Study of Wuan

by Xiangxue Han, Meichen Fu, Jingheng Wang and Sijia Li

Land 2024, 13(8), 1147; https://doi.org/10.3390/land13081147 - 26 Jul 2024

Viewed by 1046

Abstract

Climate change has become a major worldwide problem, and land use/cover change has consistently played a crucial role in impacting the carbon cycle within terrestrial ecosystems. Territorial spatial planning stands as a relatively good policy option for the low-carbon model. The spatial correlation [...] Read more.

Climate change has become a major worldwide problem, and land use/cover change has consistently played a crucial role in impacting the carbon cycle within terrestrial ecosystems. Territorial spatial planning stands as a relatively good policy option for the low-carbon model. The spatial correlation between carbon emissions and land use was established through environmental parameters in this paper. The territorial spatial structures in 2035 and 2060 under two scenarios of natural evolution and low-carbon development were simulated through the PLUS model. The results indicate that the spatial pattern of decreasing carbon emissions centered on towns, cities, mines, and industries is related to regional economic development, the distribution of forests, and the urban ecological environment. The implementation of territorial spatial planning aids in achieving carbon neutrality, whereas the low-carbon development scenario is more focused on it, which can provide ideas for territorial spatial planning adjustments. Both scenarios result in a large area of fallow land, indicating some conflict between farmland protection and low-carbon development. Optimizing management measures, energy structure, and industrial layout and strengthening regional coordination are key to promoting low-carbon development. This study might be useful in formulating regional carbon-neutral policies and improving territorial spatial planning. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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24 pages, 2539 KiB

Open AccessArticle

Construction Land Transfer Scale and Carbon Emission Intensity: Empirical Evidence Based on County-Level Land Transactions in Jiangsu Province, China

by Wenying Li, Keqiang Wang, Hongmei Liu, Yixuan Zhang and Xiaodan Zhu

Land 2024, 13(7), 917; https://doi.org/10.3390/land13070917 - 24 Jun 2024

Cited by 1 | Viewed by 1218

Abstract

The expansion of the construction land scale has been vital in supporting rapid economic development and meeting social needs. However, the spatial heterogeneity in the effect of construction land scale on carbon emission intensity at the county level remains underexplored. Therefore, comprehensively investigating [...] Read more.

The expansion of the construction land scale has been vital in supporting rapid economic development and meeting social needs. However, the spatial heterogeneity in the effect of construction land scale on carbon emission intensity at the county level remains underexplored. Therefore, comprehensively investigating the relation between the construction land transfer scale and carbon emission intensity holds substantial research value. Using panel data from 2007 to 2021, this study analyzes the spatiotemporal differentiation characteristics of carbon emission intensity and the effect of construction land scale on carbon emission intensity at the county level in Jiangsu Province, China. The findings reveal that carbon emission intensity at the county level in Jiangsu Province generally exhibits a continuous downward trend over time and a spatial distribution characterized by a gradual decrease from the southern counties to the central and northern counties. Moreover, there is a significant positive relation between the construction land transfer scale and carbon emission intensity, a conclusion supported by robustness tests. Furthermore, mediating analysis indicates that reduction of the construction land transfer scale exhibits a significant promoting effect on green technology innovation and industrial structure upgrading, which, in turn, has a significant inhibitory effect on carbon emission intensity. The impact of the construction land transfer scale from different sources, supply methods, types, and of county economic strength on carbon emission intensity has significant heterogeneity. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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19 pages, 2950 KiB

Open AccessFeature PaperArticle

The Impact of High-Standard Farmland Construction Policies on the Carbon Emissions from Agricultural Land Use (CEALU)

by Fangsheng Liu and Jian Lin

Land 2024, 13(5), 672; https://doi.org/10.3390/land13050672 - 13 May 2024

Cited by 3 | Viewed by 1627

Abstract

Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. Although there are some studies on the impact of high-standard farmland construction policies on carbon emissions, [...] Read more.

Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. Although there are some studies on the impact of high-standard farmland construction policies on carbon emissions, they focus on quantitative analysis and do not give sufficient consideration to the relationship between HSFC and CEALU. Therefore, in this study, by relying on provincial panel data of China for the period 2005–2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: (1) China’s CEALU per unit area presented a fluctuating upward change, but the growth rate slowed down during the period 2005–2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%; (2) the high-standard farmland construction (HSFC) policy led a significant carbon emission reduction effect in agricultural land use and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing change; (3) the carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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22 pages, 2524 KiB

Open AccessArticle

Spatio–Temporal Patterns and Driving Mechanisms of Urban Land High-Quality Use: Evidence from the Greater Pearl River Delta Urban Agglomeration

by Yuying Li, Danling Chen, Xiangqian Tao, Xiaotao Peng, Xinhai Lu and Ziyang Zhu

Land 2024, 13(3), 277; https://doi.org/10.3390/land13030277 - 23 Feb 2024

Cited by 4 | Viewed by 1642

Abstract

Efficient urban land use plays a crucial role in promoting regional development and ensuring economic growth. Analyzing the spatio–temporal pattern of urban land high-quality use (ULHU) and identifying its key influencing factors and pathways can contribute to enhancing land use efficiency and achieving [...] Read more.

Efficient urban land use plays a crucial role in promoting regional development and ensuring economic growth. Analyzing the spatio–temporal pattern of urban land high-quality use (ULHU) and identifying its key influencing factors and pathways can contribute to enhancing land use efficiency and achieving high-quality development. This study established a comprehensive measurement indicator system for evaluating ULHU using the entropy method and investigated the spatio–temporal evolution pattern of ULHU in the Greater Pearl River Delta (PRD) urban agglomeration in the years 2005, 2010, 2015 and 2020. Furthermore, a multi-period fuzzy-set qualitative comparative analysis method was adopted to explore the concurrent driving mechanisms that impact ULHU from the configuration perspective. The findings reveal that the level of ULHU has exhibited a significant improvement, increasing from 0.1150 in 2005 to 0.2758 in 2020, with an annual growth rate of 8.739%. The spatial pattern in the PRD region exhibits an incremental distribution, characterized by higher values in the central region and lower values in the peripheral area, as this pattern reveals significant heterogeneity across the region. The configurations for ULHU in the PRD were identified, such as Population-industry-talent driven, Openness-fiscal-talent driven, Population-led, and Population-industry driven. Among these configurations, population density and industrial structure were identified as the core driving factors, while the role of talent resources is gradually diminishing. This study provides practical guidance for promoting the ULHU and optimizing national spatial planning. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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22 pages, 8402 KiB

Open AccessArticle

Spatial Characteristics of the Non-Grain Production Rate of Cropland and Its Driving Factors in Major Grain-Producing Area: Evidence from Shandong Province, China

by Liye Wang, Jiwei Xu, Yaolin Liu and Siyu Zhang

Land 2024, 13(1), 22; https://doi.org/10.3390/land13010022 - 22 Dec 2023

Cited by 5 | Viewed by 1587

Abstract

The non-grain production rate (NGPR) of cropland is a grave threat to global grain and food supply, and has been a hot issue across the world. However, few scholars explored the impacts of the NGPRs of different cropland types, such as those of [...] Read more.

The non-grain production rate (NGPR) of cropland is a grave threat to global grain and food supply, and has been a hot issue across the world. However, few scholars explored the impacts of the NGPRs of different cropland types, such as those of paddy land and irrigated land in the same region. Thus, according to the third land survey data, this research first estimated the NGPRs of cropland, paddy land, irrigated land, and dry land at different scales in Shandong Province, China in 2019. Then, their spatial characteristics at a county scale were identified by combining the standard deviation ellipse model and spatial autocorrelation analysis. Finally, the potential driving factors of the NGPR of cropland were explored with the geographical weight regression model. Results are as follows: (1) The NGPR of cropland is at relatively lower level in Shandong Province and is dominated by that of irrigated land, and the NGPR of dry land is higher than those of other cropland types; (2) Significant regional differences exist in the NGPR of cropland, with profound severity in the southeast and much lower in the northwest; (3) At the provincial scale, the total power of agricultural machinery per capita and utilization degree of cropland factors can relieve the NGPR of cropland in nearly the entire research area. The proportion of GDP of the primary industry in GDP, urban population rate, and DEM are the main obstacles for NGPR decrease. At the county scale, the influences of driving factors varied across regions. This research can provide targeted and regional differentiated references for policy improvement and NGPR management. Full article

(This article belongs to the Special Issue Sustainable Land Use under the Target of Carbon Peaking and Carbon Neutralization)

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