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Exploring the relationships between cropland expansion and their driving factors is crucial to implement cropland protection policies. Previous research primarily explored their linear relationships but seldom discussed the non-linear effects that better reflect the changes in the real world. Thus, a machine learning method, namely, the gradient boosting decision tree (GBDT) model, is introduced to identify the threshold effect and the non-linear correlations between cropland expansion and driving factors in the middle reaches of the Yangtze River urban agglomerations (MRYR), China. Results show the following: (1) During 2000–2020, a 13,141.76 km2 of cropland is expended by taking in other land use types, among which forest and construction land have the top proportions. (2) The relative importance (RI) identified by the GBDT model indicated that area of the county (AC) and cropland area (CA) were the most important variables that affected cropland expansion values of RI at 56.94% and 12.14%, respectively. (3) A non-linear correlation exists between cropland expansion and each explanatory variable, which can be represented by a curve with thresholds. In addition, three correlation types were identified: positive, negative, and piecewise non-linear correlations. This research emphasizes that the non-linear relationships and threshold effect of the socioeconomic development factors on cropland protection should be considered when formulating cropland protection policies. [ABSTRACT FROM AUTHOR]

Construction and protection of ecological networks (ENs) is considered to be an effective means to curb habitat fragmentation and strengthen landscape connectivity. In this study, a complete evaluation framework of ENs based on "quality–function–structure" was proposed to support the formulation of protection strategies for ENs. First, we built the ENs of Wuhan urban agglomeration (WUA) from 2000 to 2020 based on the advantages of circuit theory and remote sensing data of land use monitoring. The results showed that land development activities are an important driving force for the temporal and spatial evolution of global ENs. Forest fragmentation, transitional urban expansion, and agricultural reclamation were important inducements for the shrinkage of ecological sources. They may also increase the resistance of species migration, which will lead to qualitative change and even fracture of ecological corridors. Second, circuit theory, centrality index, and complex network theory were applied to evaluate the quality defects, functional connectivity, and topology characteristics of ENs in WUA, respectively, from 2000 to 2020. The results showed that the antagonism between ecological corridors and land development activities led to ecological quality defects (ecological barriers and pinchpoints). Different land development models had differential effects on centrality indexes. Moreover, the main trunk in the northern Dabie Mountains and the southern Mufu mountains was developed, while the secondary trunks were abundant in the middle of WUA. Finally, we proposed protection strategies for ENs based on the coupling of the "quality–function–structure" of WUA in 2020. It is suggested that all ecological sources must be included in nature reserves to prevent natural or manmade erosion. The key areas to be repaired were determined through the quality evaluation of ecological corridors. The priority of construction and protection of ecological corridors was determined by coupling two topological structures and functions. We argue that specific protection strategies and directions can be determined according to the construction objectives of local ENs. [ABSTRACT FROM AUTHOR]

• A historical-information-based PMACO model was proposed to support land planning. • Methods for quantifying and coupling historical information were designed. • Interpretable machine learning models were used to explain land use evolution. • A size-adaptive strategy is applied to depict the heterogeneity in neighborhood. • The effectiveness of the HI-PMACO model was compared and validated. Land use optimization is a crucial approach for promoting sustainable development. However, current land use optimization models usually ignore the temporal pattern of land use evolution. Research on how to quantify and incorporate historical information into land use optimization process is scarce, and worth exploring. This study proposed a historical-information-based patch-level multi-type ant colony optimization (HI-PMACO) model to examine the effect of incorporating historical information into the optimization model from both macro and local perspectives. Specifically, we (1) constructed five machine learning models to explore the transition potentials and used the SHAP algorithm to visualize the non-linear effects of spatial variables; (2) introduced a size-adaptive neighborhood strategy to quantify the local land use evolution preference; (3) designed an evolution preference-weighted roulette wheel mechanism to incorporate the extracted historical information into the biomimetic intelligent algorithm; and (4) verified the effect of the HI-PMACO model. Results demonstrated that the proposed HI-PMACO model exhibited better performance in improving economic benefit and transition potential objectives with smaller land use change costs, and the local details were highly in line with relevant planning policies. This study contributes to spatio-temporal land use optimization modeling in methodology and land use management considering temporal evolution patterns. [ABSTRACT FROM AUTHOR]

Land surface area estimation can provide basic information for accurately estimating vegetation carbon storage under complex terrain. This study selected China, a country dominated by mountains, as an example, and calculated terrestrial vegetation carbon storage (VCS) for 2000 and 2015 using land surface area and traditional ellipsoid area. The land surface area is estimated by a triangular network on the high precision digital elevation model. The results showed that: 1) The VCS estimated by the surface area measurement in 2000 and 2015 were 0.676 and 0.692 Pg C (1 Pg = 1015 g) higher than the VCS calculated using the ellipsoid area, respectively. 2) As the elevation increases, the differences between VCS estimated by surface area measurement and ellipsoid area measurement are expanding. Specially, a clear gap was present starting from an elevation of 500 m, with the relative error exceeds 8.99%. 3) The total amount of carbon emitted due to land use change reached 0.114 Pg C. The conversions of forestland and grassland to other land use type are the main reasons of the loss of vegetation carbon storage, resulting in a total amount of biomass carbon storage decreased by 0.942 and 0.111 Pg C, respectively. This study was a preliminary exploration of incorporating land surface area as a factor in resource estimation, which can help more accurately understand the status of resources and the environment in the region. [ABSTRACT FROM AUTHOR]

Highlights • Identifying the advantages and disadvantages of the extant RHL transfer modes. • A new framework for RHL transfer is established based on the separation of three rights and two values. • A long-term mechanism to protect farmers' interests is built under collective membership. • It increases the understanding of the relationships among farmers, collectives, and governments. Abstract Rapid urbanization in China has triggered the mass migration of rural populations to cities, resulting in a shortage of urban land and inefficient use of rural homestead land (RHL). To address these issues, there is increasing interest in allowing for RHL transfer. Although several transfer modes have been implemented in pilot areas, the long-term protection of farmers' interests has been largely neglected. One-off transfer compensation and forced transfer often occur in practice, and there is no collective profit sharing. This paper explores the advantages and disadvantages of the extant transfer modes using comparative analysis. We propose a novel RHL transfer system under collective ownership, and three highly related key aspects add layers of protection: the separation of three sets of rights (ownership, tenure, and membership), the separation of land value from the value of accessory buildings and durable goods, and profit sharing among the collective members. The advantages of the proposal are summarized as follows: (1) it provides long-term protection for farmers' interests based on membership in the collective; (2) endows the collective with actual rights of self-governance and collective autonomy; and (3) decreases institutional costs and reform risks and improves land-use efficiency of RHL. The implications of the proposal regarding topics of concern are also discussed. This study offers a clear direction for RHL transfer and increases the understanding of the essence of the collective ownership of RHL and relationships among farmers, collectives, and governments during RHL transfer. [ABSTRACT FROM AUTHOR]

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Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining (GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%-70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors. [ABSTRACT FROM AUTHOR]

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning. [ABSTRACT FROM AUTHOR]

Land-use patterns can be considered as a consequence of competitions between different land-use types. How to coordinate the competitions is the key to land-use spatial optimization. In order to improve the ability of existing land-use spatial optimization models for addressing local land-use competitions (the competitions on land units), a loosely coupled model based on a genetic algorithm (GA) and game theory is constructed. The GA is repeatedly executed to separately optimize the spatial layout of each land-use type. The land-use status quo is overlaid with the optimization results to find local land-use competitions. The concept of land-use competition zones is introduced in this study. Using the competition zones as the basic units, the model utilizes multi-stakeholder games and the knowledge of land-use planning to coordinate the local land-use competitions. The final solution is obtained after the land-use coordination. Gaoqiao Town, Zhejiang Province is selected as the study area to verify the validity of the model. The experimental results confirm that the model is feasible to undertake land-use spatial optimization and to coordinate the competitions between different land-use types. [ABSTRACT FROM AUTHOR]

Land-use allocation is an important way to promote the intensive and economic use of land resources and achieve the goal of sustainable development. It is a complex spatial optimization problem, and heuristic algorithms have been one of the most effective ways to solve it in past studies. However, heuristic algorithms lack the guidance of planning knowledge, which makes land-use patterns usually unreasonable in practice. This research proposes a spatially explicit genetic algorithm (SEGA) that integrates land-use planning knowledge with the genetic algorithm (GA). The SEGA transforms the spatially implicit computation mode of the GA into a spatially explicit optimization style, which helps to promote the effectiveness of regional land-use allocation. Gaoqiao Town, China, was selected as the study area to test the SEGA. Results show that: (1) land-use conversions are reasonable in accordance with planning knowledge, and they improve overall land-use suitability and spatial compactness; (2) compared with the GA, the SEGA is superior in achieving global objectives and simulating local dynamics. We demonstrated that planning knowledge is essential to heuristic algorithms for land-use allocation. [ABSTRACT FROM AUTHOR]

Analyzing and evaluating spatial pattern and the spatial disparity of land consolidation projects scientifically is of great theoretical and practical value for improving land consolidation scientific decision-making. Based on the data of the land consolidation projects from 1999 to 2010 at the district or county-level in Hubei Province, this article explores empirically land consolidation differences in time, space, and autocorrelation with four indexes: land consolidation investment scale, land consolidation construction scale, the newly-added cultivated land area, and the number of land consolidation projects. The spatial disparity of land consolidation projects was studied with the methods of the standard deviation index, the coefficient of variation, and a spatial autocorrelation analysis. The conclusions can be summarized as following: (1) Utilizing the data of land consolidation projects every year in Hubei Province, we find that land consolidation projects grow rapidly in Hubei Province and land consolidation investment scale and land consolidation construction scale showed a rising trend in the wave-like characteristics. The scale of the newly-added cultivated land area increased from 1999 to 2008 and started to fall since 2008. The number of land consolidation projects increased year by year. Utilizing the data of land consolidation projects data in each space unit, we found that land consolidation investment scale and land consolidation construction scale were present in large scale in the middle of Hubei Province, and in small scale in the east and west ends. The scale of the newly-added cultivated land area also showed a high value in the middle area. The spatial pattern of the number of land consolidation projects was scattered and ruleless. (2) By calculating the standard deviation index and the coefficient of variation of land consolidation projects by year, we found that the absolute difference of land consolidation projects among each district or county showed an expansion trend from 1999 to 2010, and that the absolute scale of land consolidation projects among each district or county showed a pronounced increasing tendency, and the relative difference showed a decreasing tendency, which indicated a balanced development trend among each district or county. (3) With the of calculating Moran's I and local Moran's I in three time periods (1999-2010, 1999-2005 and 2006-2010), we found that the spatial patterns of land consolidation projects showed strong spatial autocorrelation characteristics and that spatial autocorrelation was becoming stronger. We also found that the spatial patterns of the LISA maps showed similar characteristics as the distribution of cultivated lands and fit in with the key construction direction of important land consolidation projects in Hubei Province. The patterns of the LISA maps of land consolidation investment scale and land consolidation construction scale were developing and becoming steady. The patterns of the LISA maps of the newly-added cultivated land area and the number of land consolidation projects were changing greatly. (4) Based on the previous analysis, we suggested that Hubei should continue to insist on focusing on farmland rearrangement in the future 5-10 a. The central plain area of Hubei Province should continue to insist on focusing on the high criterion basic farmland construction, that the east and southeast area of Hubei Province should advance the low-hilly land construction, that western Hubei Province should promote a slope cropland renovation project, and that north Hubei Province should put particular emphasis on the mid-low yield land construction and the low-hilly land construction. [ABSTRACT FROM AUTHOR]

Land consolidation is the most effective land management approach to optimize land-use structure and improve the natural environment. This study aims to shed light on land consolidation planning processes in China, and to highlight the characteristics and contents of thematic maps in provincial-level planning. The study area, Hubei Province, has an area of 1,85,900 km2and is located in Central China. The land consolidation potential, that is, the net increase area of arable land was calculated according to the land consolidation types in each county. The spatial characteristics of land consolidation potential, key areas, and key engineering and projects were presented on a scale of 1: 5,00,000 utilizing counties as evaluation units. The thematic maps can provide important information for policymakers and planning workers, and guide any subsequent land consolidation planning at the county level in China. [ABSTRACT FROM AUTHOR]

Abstract: The inference rules relating land characteristics to suitability class are crucial to the estimation of agricultural land suitability. In fuzzy logic modeling for agricultural land evaluation, the fuzzy inference, based on membership functions and rule aggregation, is constructed with predetermined evaluation criteria, including value ranges for fuzzy linguistic terms, and weights of land variables. However, most existing evaluation criteria systems are built on the basis of expert knowledge and can be highly subjective and contain uncertainty. This study integrates a genetic algorithm with a multi-criteria evaluation based fuzzy inference system (FIS) to construct a self-adapting system that calibrates its evaluation criteria by self-learning from land samples. In the proposed GA-optimized fuzzy inference model, the criteria for land evaluation are encoded into chromosomes, i.e., each chromosome represents a solution for the evaluation criteria system. The performance of the fuzzy inference system on a training set is used as the fitness of an individual chromosome. The genetic algorithm repeatedly modifies a population of chromosomes through selection, crossover and mutation. To reduce the violation of the constraints for chromosomes and the destruction of excellent genes, the subsets in chromosomes are used as the basic units in crossover and mutation. Some transformations are implemented in mutation to ensure that the new individuals are accorded with the constraints in the evaluation criteria. Three-fold cross-validation (3 CV) is employed to prevent overfitting and to evaluate the performance of the model. The optimized evaluation criteria are produced by decoding the final best chromosome. In the application of the model to the case study area, the accuracy of the evaluation criteria system for the training set increased from 72.08% to 93.34%. The results show that the model is both effective and robust. [Copyright &y& Elsevier]

Abstract: A variety of studies have been conducted to assess the impact of farmland preservation policies in China. Most of these studies focus on the use of pure statistical approaches to assess the policy impact. A spatially explicit modeling framework is, however, often required to better assess the policy impact and to help understand the consequence of these policies. In this article, we developed such a spatially explicit modeling framework to assess the impact of policies on arable land loss and urban sprawl through the combination of counterfactual analysis with a scenario simulation approach. Counterfactual analysis provides support to assess the impact of farmland preservation policies, while scenario simulation enables us to generate counterfactual outcomes to capture possible land use patterns without policy intervention. With support from cellular automata, farmland preservation policies are integrated into the decision-making processes of land use conversion to link policy with scenario simulation. Our case study demonstrates the potential of the proposed modeling framework for the assessment of farmland preservation policies. Experimental results indicate that farmland preservation policies play an important role in terms of reducing the rate of arable land loss and governing spontaneous urban sprawl. [Copyright &y& Elsevier]

Abstract: Shape is an important aspect of the spatial attributes of land-use segments in remotely sensed imagery, but it is still rarely used as a component in land-use classification or image-based land-use analysis. This study aimed to quantitatively characterize land-use classes using shape metrics. The study was conducted in a case area located in southern China, covering 12 scenes of SPOT-5 images. There were a total of 10 metrics selected for the analysis: convexity (CONV), solidity (SOLI), elongation (ELONG), roundness (ROUND), rectangular fitting (RECT), compactness (COMP), form factor (FORM), square pixel metric (SqP), fractal dimension (FD), and shape index (SI). The last five metrics were used to measure the complexity of shape. Six land-use classes were investigated in the case area: roads; cultivated lands; settlements; rivers; ponds; and forest and grass lands. The results showed that all the typical shape properties of the land-use segments can be well measured by shape metrics. We identified the land-use classes whose values were significantly differentiated from the other classes for each metric. Finally, we selected five shape metrics (SOLI, ELONG, ROUND, RECT, FORM) by visual comparison and statistical analysis of the metrics values, and deduced the “shape metric signatures” (SMS) of the different land-use classes. SMS were found to be accurate and predictive discriminators of land-use classes within the study area. Our results showed that SMS can clearly distinguish spectrally similar land-use classes. The results of this study will help to build a more accurate and intelligent object-oriented classification system for land-use classes. [Copyright &y& Elsevier]

Semiarid loess hilly areas in China are enduring a series of environmental conflicts between urban expansion, cultivated land conservation, soil erosion and water shortage, and require land use allocation to reconcile these environmental conflicts. We argue that the optimized spatial allocation of rural land use can be achieved by a Particle Swarm Optimization (PSO) model in conjunction with multi-objective optimization techniques. Our study focuses on Yuzhong County of Gangsu Province in China, a typical catchment on the Loess Plateau, and proposes a land use spatial optimization model. The model maximizes land use suitability and spatial compactness based on a variety of constraints, e.g. optimal land use structure and restrictive areas, and employs an improved PSO algorithm equipped with a determinant initialization method and a dynamic weighted aggregation (DWA) method to obtain the optimized land use spatial pattern. The results suggest that (1) approximately 4% of land use should be reallocated and these changes would alleviate the environmental conflicts in the study area; (2) the major reshuffling is slope farmland and newly added construction and cultivated land, whereas the unchanged areas are largely forests and basic farmland; and (3) the PSO is capable of optimizing rural land use allocation, and the determinant initialization method and DWA can improve the performance of the PSO. [ABSTRACT FROM AUTHOR]

Abstract: The generalization index system is one of the critical issues for computer-aided land use database generalization. This paper studies the scale and land use pattern effects on land use database generalization indices and estimates the thresholds of these indices based on a typical land use database sample. The index system of land use database generalization is discussed and constructed from macro and micro perspectives. Six land use pattern metrics, namely, land use diversity index, land use dominance index, land use homogeneity index, land use fragmentation index, the index of land use type dominance, and the index of land use type fragmentation, are designed to characterize land use patterns and are introduced into the analysis of land use pattern effect on land use database indices. The analysis framework of the scale and land use pattern effects on the land use database indices are proposed by employing statistical techniques. Based on the land use database samples at multiple spatial scales collected in various land use regions across China, the study generates rules for both scale and land use pattern effects on the indices, including map area proportion of land use types, total map load, parcel map load, and minimum parcel area. The thresholds of these indices in land use database generalization are produced at the scales of 1:50,000, 1:100,000, 1:250,000, and 1:500,000. An experimental generalization at county level demonstrates how to determine the generalization index values considering scale and land use pattern, and how to evaluate the generalization results using our macro indices. [Copyright &y& Elsevier]

• This article examines the interaction between land use and commuting flows from mobile phone data based on the moderated multiple regression model. • The results reveal that urban land-use types of commuters' origins and destinations significantly influence commuting flows. • This study indicates that urban land-use types moderate the relationship between the distance and commuting flows as well. Commuting is an essential part of our urban daily life. Understanding of commuting flows is crucial for urban and traffic planning. Urban land use plays a fundamental role of urban studies, given that its verified impact on commuting pattern in previous studies. This paper explores whether urban land use influences the commuting flows and how it impacts the relationship between commuting flows and origin-destination distances (i.e., the accessibility). In this study, the basic gravity model is extended with land use variables. And both multiple regression and moderated multiple regression models are applied to analyze the relationship between commuting flows and land use (i.e., industrial, commercial, residential, educational land etc.), as well as the interaction effect between land use variables and the accessible distance. Commuting data is extracted from Wuhan's mobile phone signaling data in 2016, particularly incorporated in the empirical analysis. The results show that industrial and residential origins are likely to send more commuters while industrial and commercial destinations attract more. An interaction effect between land use and distance is revealed that commuting flows with industrial origins (destinations) decrease fastest with distance increasing while those with commercial origins (destinations) decrease slowest. These findings imply that: 1) Urban land use of commuters' origins and destinations significantly influences commuting flows; and 2) Urban land use moderates the relationship between the distance and commuting flows as well. This study contributes to policies-makings of urban and traffic planning through understanding commuting flows from the mobile phone signaling data perspective [ABSTRACT FROM AUTHOR]

Rural land use development is experiencing a transition stage of socioeconomic and land use development in China. Historic land use transition process and policy interventions have key influence on the applicability of land use allocation solutions in future land use management. Strategic land use allocation is therefore required to possess a good adjustment capability to the transition process. Although heuristic optimization methods have been promising to solve land use allocation problems, most of them ignored the spatially explicit effect of historic land use transition and policies. To help resolve this issue, this study aims to optimize future land use pattern in the context of rural land use development. We took Yunmeng County, one of the typical major grain producing and rapidly urbanizing areas in central China, as a case study and solved the sustainable land use allocation problem by using an improved heuristic optimization model. The model was constructed based on the integration of a spatial discrete particle swarm optimization and cellular automata-Markov simulation approach. The spatiotemporal land use patterns and policy interventions were represented by the CA-Markov as in spatially explicit transition rules, and then incorporated into the discrete PSO for optimal land use solutions. We examined the influence of the joint effect of spatiotemporal land use patterns and policy interventions on the land use allocation outcome. Our results demonstrate the robustness and potential of the proposed model, and, more importantly, indicate the significance of incorporating the spatiotemporal land use patterns and policy interventions into rural land use allocation. [ABSTRACT FROM AUTHOR]

Abstract: Distantial attenuation is a significant characteristic of the urban environment. In this paper we explore the relative contributions of different land uses to the urban residential environment according to distances with an analysis on the most significant scope of these factors. Two types of models are developed. One employs the distance to city center, main road, public facilities and environment factors as the variables for macro environment analysis, and the another one includes all factors to analyze the influences of the micro environment. In the models of the latter type, the contributions of the neighboring land uses are magnified with a specially designed variable measurement scheme in which variables are evaluated specially for each model so that the contributions of the variables become comparable from model to model. With an application to the case study of Danyang, China, we measure the distantial functions of the urban environment (e.g. the surrounding land uses) including both the most influential scopes and the relative contributions by means of model summary and regression coefficient comparisons. Finally, case comparison on the samples is introduced to figure out the difference of the functions under micro environment. [Copyright &y& Elsevier]

Human-induced changes in land use and land cover (LULC) considerably impact the global carbon cycle. Rational LULC optimization with full utilization of terrestrial vegetation facilitates reconciling carbon reduction and socio-economic development. To this end, this study develops a multi-objective framework for low-carbon LULC spatial optimization that incorporates carbon suitability, historical suitability, and socio-economic needs. The framework is applied to Hubei Province, China. The key findings include: (1) Considering spatial variations in vegetation carbon sinks could lead to remarkable carbon reductions of 2.75 × 106 t C by 2030 and 7.68 × 106 t C by 2060. It would also lower carbon emissions per unit of gross domestic product (GDP) and enhance carbon sequestration per unit of vegetation by 2030, signifying enhanced carbon reduction efficiency. (2) Integrating carbon sequestration potential and historical suitability can considerably minimize emissions while sustaining socio-economic growth. Our method, compared with strategies based solely on historical development laws, can reduce carbon emissions by approximately 1.3–1.6 × 106 t C·a−1. (3) We also propose targeted low-carbon development suggestions for different LULCs. This study provides optimal spatial LULC allocations and strategic advice for regional LULC planning aimed at low-carbon development, demonstrating the feasibility of reconciling the tension between carbon reduction and socio-economic growth at the regional scale. • A regional spatial LULC optimizing framework balancing carbon, economy, and society. • Carbon-based afforestation outperforms history-based in CO 2 reduction. • Blending carbon with historical suitability balances GDP and ecological benefits. • Afforestation with ideal trees and sites aids CO 2 cut; if not, its returns decline. [ABSTRACT FROM AUTHOR]

Finding ways to identify the coupled relationship between changes in the quantity and quality of ecologically functional land (EFL) is essential for sustainable ecosystem management. However, this coupled relationship has been ignored in the literature. This paper proposes a quality-based quantity (QBQ) method to evaluate the spatiotemporal change in EFL in China. Three Landsat images spanning 20 years were used to investigate the gains and losses of EFL. We compared the differences and linkages between the net change and QBQ change of EFL at the county scale. Continuous EFL loss and growing fragmentation were observed in China. From 1995 to 2015, the main cause of EFL loss was desertification, followed by farmland occupation and construction land consolidation. It should be noted that the EFL loss from 2005 to 2015 was much higher than that from 1995 to 2005. The main gain in EFL was from desert land exploitation, followed by farmland return and construction land consolidation. In particular, grassland degradation was the most severe ecological problem in western China. The QBQ change in EFL showed a more severe situation than did the quantity change. The dynamic processes associated with quantity change and their effects on landscape were well reflected in the QBQ change. These results indicated that the EFL degraded in both quantity and quality in China between 1995 and 2015. EFL conservation policies should focus not only on the dynamic losses and gains in quantity but also on the changes in quality linked to landscape patterns. • Three Landsat images spanning 20 years were used to investigate the gains and losses of ecologically functional land (EFL) in China. • A quality-based quantity (QBQ) method was proposed to evaluate the spatiotemporal change in EFL. • Continuous EFL loss and growing fragmentation were observed between 1995 and 2015. • It advances our understanding of how both the quantity and the quality of land use change are involved in ecological degradation. [ABSTRACT FROM AUTHOR]

Industrial transfers are conducive to reducing regional development disparities, but they may cause pollution transfers through pollution-intensive industries (PIIs). This study tries to characterize transfers of PIIs in China from 2007 to 2016 with newly expanded industrial land use data. The industry transfer relative intensity index is calculated to measure interregional transfers of PIIs, and hot spot analysis is used to illustrate the spatial clustering pattern of PII transfers. The results are as follows. 1) PIIs are transferred from the east to the west and from the eastern coastal region to the northwest and the middle reaches of the Yellow River economic zone. Land use by PIIs in Western China as a proportion of the national total has gradually increased, from third to first rank. 2) Over time, the significant cold spots (i.e., clusters of transfer-out regions) have spread from the eastern coastal provinces to the central provinces, and the hot spots (i.e., clusters of transfer-in regions) have become more significant in the northwestern provinces. 3) PII transfers in urban agglomerations are strongly consistent. 4) Transfers of PIIs are influenced by regional resource endowments, environmental regulations, and other policies. These findings provide vital information to aid environmental protection and policymaking. • Transfers of pollution-intensive industries are measured with newly-increased industrial land. • Land use by pollution-intensive industries in Western China as a proportion of the national total has gradually increased. • Transfers of pollution-intensive industries in urban agglomerations are strongly consistent. • Transfers of pollution-intensive industries are influenced by regional resource endowments and environmental regulations. [ABSTRACT FROM AUTHOR]

Cropland protection strategies have provided a strong contribution to limit cropland transformation worldwide. However, it negatively affects ecological land (e.g., forest, grassland, and wetland). Identifying a win-win approach for cropland protection and ecological conservation is important. Land use optimization plays a vital role in solving conflicts among land uses. Thus, in this research, taking China (mainland) as the study area, we optimized the spatial distribution of urban land and cropland to balance the requirement of cropland protection strategies and their negative effects on ecological land according to the spatial heterogeneity of land agricultural production capacity by using the LAND System Cellular Automata model for Potential Effects (LANDSCAPE). Specifically, we developed three optimization scenarios from compensational, occupancy, and occupancy and compensational sectors. We also developed one non-optimization scenario to remain comparable. Results show that compared with the non-optimization scenario, the reduced loss of ecological land in compensational, occupancy, and occupancy and compensational optimization scenario is 7180, 247, and 7277 km2, respectively. Our research indicates that we should prioritize the quality of compensated cropland when developing cropland protection strategies and planning, considering the low efficiency of the occupancy optimization and the cost of policymaking and implementing. • More ecological land is lost because of cropland compensation. • Land agricultural production capacity can be used to optimize land use. • The optimization effect from compensation is better than that from occupancy. [ABSTRACT FROM AUTHOR]