As China rapidly urbanizes, land resources tend to deplete. This paper aims to identify and propose a resolution of land use conflicts to promote sustainable land use and coordinate the interaction between humans and the environment in urban areas. The methodology of land use conflict assessment within spatial zoning of the Su–Xi–Chang region was evaluated. Taking into consideration the intensity of human activities and the background condition of the natural environment, we divided the study area into a few regions. Furthermore, we developed a methodology by calculating landscape complexity, fragility, and stability based on spatial zoning so as to derive the spatio-temporal characteristics of the land use conflict index (LUCI) in the Su–Xi–Chang region. The results indicate the following: (1) According to the urban spatial attribute index (USAI) statistics, we delineate the core, fringe, and suburban zones of the Su–Xi–Chang region, which accounted for 9.61%, 11.06%, and 79.33% of urban agglomerations respectively; (2) from 1990 to 2018, the fragility index (FI) and LUCI showed S-shaped curves, while the complexity (CI) and the stability indices (SI) exhibited minor fluctuations in the fringe and suburb zones; and (3) intensive and severe conflict is concentrated in core areas due to quite intense human activities and in fringe areas due to an increased interaction between humans and land, while moderate conflict is mainly found in rural and suburban areas that pose as a natural environmental space. The results can serve as a theoretical framework for an effective identification of the LUCI in an urban agglomeration and coordination of the optimal allocation of regional land resources.

Under the background of green development, the spatial structure of urban agglomerations (UA) has an important impact on urban land use efficiency (ULUE), but few studies have explored the impact mechanism between the two. This research explores the impacts of polycentric development on ULUE of UA, using data for 140 cities in China’s top ten key UA covering the period from 2004–2019. The linkage between polycentric development and ULUE is explored by estimating models of determinants of ULUE. This research also examines the mechanism of the polycentric spatial structure of UA on ULUE by using a moderated mediation model. The main findings of the research can be concluded as below. The eastern UAs show a mostly polycentric spatial structure, whereas the central and western UAs show a weak polycentric spatial structure. The polycentric spatial structure of UA has a positive impact on ULUE. An inverted U-shape curve depicts the relationship between the polycentric spatial structure of UA and ULUE. However, the mediating variables, integration of industrial structure and factor mobility have a positive and partially mediating effect between the polycentric spatial structure of UA and ULUE. The infrastructure level has a positive U-shaped regulation effect, in which the impact coefficient of transport infrastructure is more significant. These findings provide empirical evidence for the coordinated development of China’s regional space planning and ULUE.

In the context of international carbon neutrality, energy prices are affected by several nonlinear and nonstationary factors, making it challenging for traditional forecasting models to predict energy prices effectively. The existing literature mainly uses linear models or a combination of multiple models to forecast energy prices. For the nonlinear relationship between variables and the mining of historical data information, the prediction strategy and accuracy of the existing literature need to be improved. Thus, this paper improves the prediction accuracy of energy prices by developing a “decomposition-reconstruction-integration” thinking strategy that affords medium- and short-term energy price prediction based on carbon constraint, eigenvalue transformation and deep learning neural networks. Considering 2011–2020 as the research period, the prices for traditional energy resources and polysilicon in clean photovoltaic energy raw materials are selected as representatives. Based on energy price decomposition using the Singular Spectrum Analysis (SSA) method, and combining it with Learning Vector Quantization (LVQ) cluster technology, the decomposed quantities are aggregated into price sequences with different characteristics. Additionally, the carbon intensity is considered the leading market’s overall constraint, which is input with the processed price data into a Long Short-Term Memory network (LSTM) model for training. Thus, the SSA-LSTM combined forecasting model is developed to predict the energy price under carbon neutrality. Four indices are employed to evaluate the prediction accuracy: Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and R-squared. The results highlight the following observations. (1) Using a sequence decomposition clustering strategy significantly improves the model’s prediction accuracy. This strategy enhances predicting the overall trend of the price series and the changes in different periods. For coal price, the RMSE value decreased from 0.135 to 0.098, the MAE value decreased from 0.087 to 0.054, the MAPE value decreased from 0.072 to 0.064, and the R-squared value increased from 0.643 to 0.725. Regarding the polysilicon price, the RMSE value decreased from 0.121 to 0.096, the MAE value decreased from 0.068 to 0.064, the MAPE value decreased from 0.069 to 0.048, and the R-squared value increased from 0.718 to 0.764. (2) The prediction effect is better in the case of carbon constraint. Considering “carbon emission intensity” as the overall constraint of the leading market, it can effectively explore the typical characteristics of energy price information. Four evaluation indicators show that the accuracy of the model prediction can be improved by more than 3%. (3) When the proposed SSA-LSTM model is used to predict both prices, the results show that the evaluation index of the prediction error remained at about 1%, while the model’s accuracy was high. This also proves that the proposed model can predict traditional energy prices and new energy sources such as solar energy.

In order to solve the issue of idle rural homesteads and enhance the welfare of peasant households, the Chinese government has implemented various rural homestead withdrawal patterns. In the context of land spatial planning regulation, based on the field survey data from 210 peasant households in Xuzhou City and Ganzhou City, this study constructs a bilateral matching model between rural homestead withdrawal patterns and types of welfare needs of peasant households. This study uses a Discrete Particle Swarm Optimization algorithm improved on the 0–1 knapsack strategy to solve the matching model, aiming to find the optimal homestead withdrawal patterns that match the types of peasant households. The results show that: (1) The matching of rural homestead withdrawal patterns and types of peasant households conforms to the principle of comparative advantage. (2) In the case of “one-to-one matching” between peasant households and homestead withdrawal patterns, matching the “economic-material-oriented” peasant households with the withdrawal pattern of “monetary compensation”, matching the “social-service-oriented” peasant households with withdrawal pattern of “indicator replacement”, and matching the “welfare-assistance-oriented” peasant households with the withdrawal pattern of “asset replacement”. (3) The bilateral overall preference of the combined rural homestead withdrawal patterns is higher than that of the single rural homestead withdrawal pattern, and satisfaction has increased by at least 8 %. The authors argue that the government should design and implement diversified withdrawal patterns based on a full understanding of the welfare needs of peasant households.

Ecosystem services (ES) are a key bridge connecting natural ecosystems with human social development. The core significance of ecosystem service value (ESV) is to quantify the contribution of ecosystems to human well-being. The mining of mineral resources causes disturbance to the structure, function, and value of ecosystems. This study focuses on the high groundwater level coal–grain overlapping areas in eastern China, the mining of mineral resources has led to widespread loss of cropland and carbon sinks in the region. Considering the particularity of ecosystem evolution caused by coal mining subsidence, we developed multiple land use demand scenarios under dual objective constraints based on PIM and Markov chain, including Inertial Development (ID), Food Security (FS), Urban Expansion (UE), Ecological Restoration (ER). The PLUS model was used to simulate the spatial changes of land use and the equivalent factor method was used to calculate the changes in ESV, exploring the best path to improve the ecological benefits of the coal–grain overlapping areas. The results indicate that: (1) By 2030, the study area will add 54,249.09 ha of coal mining subsidence, mainly mild and moderate subsidence, and cropland being the most affected by subsidence among all land types. (2) In the multi-scenarios, the total ESV is ranked as follows: ecological governance scenario (CNY 51.21199 billion) > ID scenario (CNY 51.0898 billion) > food security scenario (CNY 48.4767 billion) > UE scenario (CNY 48.27157 billion). Among them, the ER scenario achieves all individual ESV gains and has the highest overall ESV. (3) Spatial analysis shows that in the ER scenario, the ESV of mining townships significantly increases and the ESV gap between other townships has decreased. However, the FS scenario and UE scenario have led to widespread degradation of ESV between various townships in eastern mountainous areas, and severe degradation of ESV in some urban townships. This study validated the accuracy and applicability of the PLUS model in medium scale and plain regions. The study has confirmed our hypothesis that reasonable land use and ecological restoration methods can achieve Pareto improvement in regional ESV, provided a holistic and local dialectical perspective for related research, and a scientific basis for the sustainable development of coal grain overlapping areas.

Developing a scientifically grounded regionally-balanced pricing mechanism for rural homestead compensation is essential to resolve spatial inequities in withdrawal compensation. Based on the utility theory of regional economics, a regional "ecological economic" land coordination compensation mechanism for rural homestead withdrawal was constructed, and a new round of homestead reform pilot city, Peixian county, Xuzhou city, was taken as the research object. Numerical analysis methods were used for quantitative analysis and empirical testing. The results indicate that: (1) The compensation pricing mechanism for rural homestead withdrawal based on regional "economic ecological" land coordination balances fairness and efficiency, and balances the interest conflicts of stakeholders in different functional areas within the regional scope during the process of homestead withdrawal. (2) From the perspective of regional synergy, when rural homesteads within a region are converted to ecological land types, an additional economic compensation of 145.65 yuan per unit area can be obtained for the withdrawal of homesteads. The main payer is the region where the homesteads are withdrawn and converted to economic land types. (3) From the perspective of regional coordination, the additional compensation amount obtained when rural homesteads are transformed into ecological land can be offset by the value-added income from the exit of rural homesteads and the transformation into economic land. Rural homesteads undergoing withdrawal and conversion to economic land can generate a 5.45% regional value-added premium. Based on the above research conclusions, it is necessary to coordinate the inter-regional interests of different functional zones in the reform of the rural homestead withdrawal system, and actively explore differentiated compensation strategies and standards for homestead withdrawal under the guidance of regional economic ecological system balance.