As an important carrier of expanded urban spatial growth, new towns have been a “policy tool” for spatial production in the new era and have received long-term and constant attention from circles such as geography, planning, and economics. National new districts constitute a new regional space for China to implement the national strategy and promote the transformation of urban development mode. They are mutually reinforcing with their mother cities and hinterland provinces. Based on the geodetector method, this paper reveals the key factors driving the development of national new districts by mother cities and hinterland provinces and their interaction effects, which provides a basis for municipal and provincial governments to accurately formulate policies to promote the development of new towns by classification. The study shows that, firstly, there are five types of driving factors, that is, all-round driving factors, scale-increasing factors, expansion and quality-improving factors, expertise driving factors, and non-driving factors. The strength and dimension of the driving factors are characterized by prominent heterogeneity; R&D personnel, export and import trade are the key factors to expand the increment, optimize the inventory, and improve the quality; the overall development driving forces are in the order of innovation > opening > industry > investment > population. Secondly, the pairwise interaction between different factors exhibits two-factor enhancement, and the population shows a nonlinear increase in the driving force of investment, openness, and innovation on a provincial scale. Thirdly, according to the driving force of the factors and the interaction between them, suggestions are put forward based on the development stage and key demands for city and provincial governments to make policies for the development of national new districts, to support the establishment of scientific competition and cooperation between new towns and mother cities or regions, and to build a long-term collaborative development mechanism.

Introduction: Climate change and land use/cover changes (LUCC) greatly influenced terrestrial carbon sequestration.Methods: This study evaluated the effects of climate change and LUCC on the carbon sequestration of forest ecosystems from 1991 to 2020 in the coastal area of China using a process-based global vegetation dynamic model (IBIS).Results and discussion: The results showed that temperature had an increasing trend, with a rate of 0.02 °C yr⁻¹; 20.00% of the forest coverage shifted spatially but there was only a 0.31% increase in total area. The carbon sequestration amounts by plants (net primary productivity, NPP) and the net carbon budget (net ecosystem productivity, NEP) in the coastal area of China in 2020 were 666.49 and 58.45 Tg C yr⁻¹, respectively, which increased by 18.31% and 2509.30%, respectively, compared to the values in 1991. The increased forest ecosystem NPP and NEP were mainly due to climate change, while forest cover changes increased NPP by only 0.06% and NEP by 9.75% with a strong regional difference. The NPP showed a significant increasing trend, with a rate of 3.01 Tg C yr⁻¹, which was positively correlated with temperature (0.43, p < 0.01) and precipitation (0.42, p < 0.01). However, the NEP largely varied during 1991-2020 and did not show a significant correlation with precipitation or temperature. These results provide scientific guidance for the government to enact environmental protection and low-carbon land use planning policies.

Background: The precise allocation and efficient use of industrial land are necessary for the development and optimization of urban production space; however, the mismatches between urban industrial land consumption and the growth of manufacturing are becoming more serious and has become the primary obstacle to sustainable urban development. Methods: Based on a combination of the Boston Consulting Group matrix, spatial mismatch model, decoupling index, GIS, and Geodetector tools, this paper conducts an empirical study on the Yangtze River Delta region in an attempt to reveal the spatio-temporal evolution of the mismatch between urban industrial land changes and the growth of manufacturing and provide a basis for spatial planning and land management in the new era. Results: The distribution of urban industrial land is characterized by high heterogeneity and agglomeration, the coexistence of expansion and contraction, and increasingly complex and diversified changes. Gross domestic product, government revenue, the added value of tertiary industry, and government investment in science and technology indicate that the goal orientation and scale effect of economic growth play a decisive role in the allocation of urban industrial land and that the influence of industrial structures and technological innovation is rapidly increasing. The interaction between the different factors is a bifactor enhancement, for example, land used for logistics and storage, utilities, commercial and other services, and the import and export trade, which have a strong synergistic enhancement effect. The mismatches between urban industrial land changes and the growth of manufacturing are still within a reasonable degree but there is an increasing number of cities with negative mismatches, making it necessary to implement a differentiated spatial adjustment and management policy. Conclusions: Compared with the mismatches of mobile resources such as labor, finance, and capital, the mismatches of immovable land resources have an increasing impact with more serious consequences and it is harder to make optimizations and corrections. However, the academic community has limited knowledge about land resource mismatches. By quantitatively assessing the mismatches between industrial land consumption and the growth of manufacturing in YRD cities, this paper argues that the mismatches can be rectified through spatial and land use planning and suggests the establishment of a zoning management and governance system to achieve the optimal allocation of urban industrial land resources through the implementation of a “standard land + commitment system” and industrial land protection lines.

Urban park green areas are part of territorial space planning, shouldering the mission of providing residents with high-quality ecological products and public space. Using a combination of several measurement models such as the BCG (Boston Consulting Group) matrix, ESDA (Exploratory Spatial Data Analysis), MLR (Machine Learning Regression), GWR (Geographically Weighted Regression), and GeoDetector, this paper presents an empirical study on the changes in Urban Park Green Areas (UPGAs) in the Grand Canal of China. By quantitatively measuring the spatio–temporal evolution patterns of UPGAs, this study reveals the driving mechanisms behind them and proposes policy recommendations for planning and management based on performance evaluation. The spatio–temporal evolution of UPGAs and their performance in China’s Grand Canal are characterized by significant spatial heterogeneity and correlation, with diversified development patterns such as HH (High-scale–High-growth), HL (High-scale–Low-growth), LH (Low-scale–High-growth), and LL (Low-scale–Low-growth) emerging. The evolution performance is dominated by positive oversupply and positive equilibrium, where undersupply coexists with oversupply. Therefore, this paper recommends the implementation of a zoning strategy in the future spatial planning of ecological green areas, urban parks, and green infrastructure. It is also recommended to design differentiated construction strategies and management policies for each zoning area, while promoting inter-city mutual cooperation in the joint preparation and implementation of integrated symbiosis planning. Furthermore, the spatio–temporal evolution of the UPGAs in the Grand Canal of China is influenced by many factors with very complex dynamic mechanisms, and there are significant differences in the nature, intensity, spatial effects, and interaction effects between different factors. Therefore, in the future management of ecological green areas, urban parks, and green infrastructure, it is necessary to interconnect policies to enhance their synergies in population, aging, industry and economy, and ecological civilization to maximize the policy performance.

As the global urban economy accelerates its transition from an “industrial economy” to a “service economy”, consumption has replaced investment as the core engine driving economic development. Commercial land serves as the physical foundation for consumer activities and plays a vital role in boosting urban economic vitality, enhancing residents’ quality of life, and promoting regional sustainable development when appropriately allocated. This study constructs a technical framework for analyzing the mismatch between commercial land supply and residential consumption demand, along with its impact mechanism, based on the integrated application of the multidisciplinary quantitative models such as the Boston Consulting Group Matrix (BCGM), Exploratory Spatial Data Analysis (ESDA), Decoupling Model (DM), and Explainable Machine Learning (EML). It conducts empirical research across 87 county-level cities in Gansu Province. The findings reveal that commercial land supply and consumption demand exhibit dynamic diversification, with prominent regional disparities and spatial autocorrelation characteristics. Commercial land in Gansu faces a severe mismatch, with demand exceeding supply and supply exceeding demand occurring simultaneously, and the former holding absolute dominance. The formation of mismatched relationships is influenced by many factors, exhibiting significant path nonlinearity, spatial non-stationarity, and relational interactivity. It is suggested that strategies of planning zoning and regional coordination be developed for mismatch governance, and differentiated management measures be implemented based on local conditions. This will provide a scientific basis for commercial territorial space planning and consumption policy design.