Low-carbon pilot policies are essential for the green transformation of resource-based cities, helping them mitigate the “carbon curse” and the “resource curse” while promoting sustainable socio-ecological development. Focusing on a panel of 114 resource-based cities in China, spanning from 2003 to 2022, this study employs a range of methodologies, including kernel density estimation, the Difference-in-Differences Model, Spatial Difference-in-Differences, Mediation Analysis, K-means Clustering, and Dual Machine Learning to assess the consequences of low-carbon pilot policies on socio-ecological resilience. The findings indicate that the socio-ecological resilience of the study area has generally improved, though there is noticeable polarization. Low-carbon pilot policies significantly enhance the resilience of resource-based cities by 0.4%, and they exhibit a positive spatial spillover effect of 1.1%. However, the long-term effects of the policies on economic resilience were not significant, and the policies did not have a direct impact on the social resilience of the pilot cities; however, they did promote social resilience in neighboring regions. Finally, the effectiveness of low-carbon pilots varies, with more pronounced benefits in declining and mature resource cities, particularly in those with medium ecological and economic resilience, and low social resilience. Green finance, industrial transformation, and carbon emission efficiency are identified as key strategies for improving socio-ecological resilience. The above findings provide insights for policymakers seeking to foster inclusive, resilient, and sustainable urban development in China.

Carbon emissions have a profound impact on the transformation goals and development paths of cities. In the context of carbon neutrality, it is of great significance to explore the coupling coordination level of the social–ecological systems in resource-based cities for realizing regional low-carbon and sustainable development. In this study, the entropy weighting method, coupling coordination degree model and geographical detector were used to measure the comprehensive development level and coupling coordination level of the social–ecological system in 116 resource-based cities in China from 2010 to 2020 and their spatial–temporal characteristics and influencing mechanism were analyzed. The results show the following: (1) The comprehensive development level of the social system in China’s resource-based cities has a significant upward trend, while the comprehensive development level of the ecological system has a gentle upward trend, and the coupling and coordination level of the social–ecological system has a fluctuating upward trend. (2) There is obvious spatial differentiation between the comprehensive development level and the coupling coordination level of the social–ecological systems in resource-based cities in China, and the relative difference is gradually increasing. (3) The digital economy index, urbanization level, science and education investment, and population density are important factors affecting the coupling coordination level, and the interaction between digital economy index, urbanization level, and population density has a strong explanatory power in the differentiation of the coupling coordination level. Based on the above conclusions, effective policy recommendations are put forward: formulate more refined and differentiated development paths, co-ordinate the spatial layout to give full play to the role of urban agglomeration, vigorously develop the digital economy, increase investment in science and education, rely on scientific and technological innovation to create development advantages, reasonably guide the population layout and take a new urbanization development route.

Understanding the spatial association network structure and carbon balance zoning of land-use carbon emissions (LUCEs) is essential for guiding regional environmental management. This study constructs a LUCE spatial association network for Hubei Province using a modified gravity model to uncover the spatial linkages in carbon emissions. Carbon balance zones are delineated by integrating LUCE network characteristics with economic and ecological indicators. To further examine the network dynamics, link prediction algorithms are employed to anticipate potential emission connections, while quadratic assignment procedure (QAP) regression analyzes how intercity differences in socioeconomic, ecological, and land-use attributes influence LUCE connectivity. The results reveal a pronounced core–periphery structure, with potential carbon spillover pathways extending toward both eastern and western cities. Based on the carbon balance analysis, six functional zones are identified, each aligned with targeted collaborative mitigation strategies. The QAP results indicate that intercity differences in innovation capacity, industrial structure, and economic development are positively associated with the formation of LUCE spatial networks, whereas disparities in urbanization level, government expenditure, and construction land use are negatively associated with LUCE connectivity. This study provides a differentiated governance framework to address the dual challenges of carbon emissions and land-use transformation in agro-urban regions.

Digitization plays a vital role in fostering economic and social development. This study empirically investigates the impact of digitization on urban industrial structures, technological innovation, public service levels, and social–ecological resilience. Various approaches, including the two-tier stochastic, spatial econometric, and panel threshold models, have been employed to analyze panel data from 287 cities from 2008 to 2023. These data are examined through a quasi-natural experiment analyzing the evolution of urban social–ecological resilience following China’s promotion of the national comprehensive pilot zone for big data. The findings are as follows. (1) The positive effects of digitization on urban social and ecological resilience substantially outweigh the negative effects, with an overall increasing trend in the positive net effect, albeit with significant regional differences. (2) Digitalization exhibits a significant spatial spillover effect, enhancing local social–ecological resilience while inhibiting improvements in neighboring cities. (3) Technological innovation and public service levels positively affect social–ecological resilience, whereas industrial structure upgrading has a negative indirect effect. Both industrial structure upgrading and public service levels demonstrate nonlinear effects under the threshold constraints of the intermediary mechanism. (4) In terms of policy mechanisms, regional differences in the urban industrial structure, innovation capacity, and public service levels must be considered. This approach is essential for promoting the organic integration of digitization across regions, mitigating the polarization effect, and enhancing the diffusion effect.