Investigating the distribution characteristics of earthquake disaster risks in the Sichuan–Yunnan region is of great importance for enhancing government emergency response capabilities and achieving sustainable regional development. This study, based on disaster systems theory, constructs a seismic risk evaluation index system for the Sichuan–Yunnan region and employs the entropy method to determine the comprehensive risk index for earthquake disasters across 37 prefecture-level cities. The findings reveal the following: (1) High-risk areas for disaster-causing factors are located in the Hengduan Mountain region and the North–South Mountain Range Valley Region; medium-risk areas are distributed along the northwestern edge of the Sichuan Basin; low-risk areas are situated in the eastern part of the Sichuan Basin and the Yunnan Plateau. (2) High-risk disaster-prone environments are found in the Hengduan Mountain region; medium-risk areas are present on the Yunnan Plateau and the western part of the North–South Mountain Range Valley Region; low-risk areas are in the Sichuan Basin. (3) High-vulnerability areas include the central Sichuan Basin and Kunming on the Yunnan Plateau; medium-vulnerability areas are located in the eastern and western parts of the Sichuan Basin; low-vulnerability areas are in the less developed parts of the Yunnan Plateau, the North–South Mountain Range Valley Region, and the Hengduan Mountain region. (4) High-risk seismic disaster areas are concentrated in the developed regions of the Sichuan Basin and the Yunnan Plateau; medium-risk areas are concentrated in the western part of the North–South Mountain Range Valley Region; low-risk areas are sporadically distributed in the eastern parts of the Sichuan–Yunnan region. (5) The vulnerability of the population, economy, and lifeline systems significantly explain the variation in seismic risk levels, all exceeding 0.70; the synergistic effects of disaster-causing factor danger, disaster-prone environment stability, and disaster-prone environment sensitivity are the most pronounced, with explanatory power exceeding 0.85 after factor interaction.

Resource-based cities are the key carriers of China’s energy security and the goal of “dual carbon”, and they are also sensitive areas of the evolution of human-land relationship. It is of great significance to clarify the mutual feedback mechanism between land use and ecosystem services (ESs) to break the high-carbon lock and realize the synergy of ecological development. Based on the land use data from 2003 to 2023, this study takes Hohhot-Baotou-Ordos-Yulin urban agglomeration as the research object, coupled with PLUS-InVEST model, analyzes the temporal and spatial evolution characteristics of carbon stock, habitat quality, water yield and soil conservation, and weighs the synergistic relationship. Further set four scenarios of natural development, economic priority, green low-carbon and high-quality development to simulate the land use pattern and ESs response in 2033. On this basis, the driving factors of ESs are identified by using the geographical detector model based on the optimal parameters. The results show that: (1) The area of construction land increased sharply from 2003 to 2023, and the transfer effect between grassland, cultivated land and unused land was significant; (2) ESs is differentiated in stages, with carbon stock, habitat quality and soil conservation evolving in an inverted“U”shape, and the water yield continues to decline. The high-value areas are concentrated in ecological restoration areas, and the low-value areas are highly overlapped with industrial, mining and urban construction areas; (3) In the historical period, ESs was dominated by synergy, and soil conservation was significantly coordinated with carbon stock and habitat quality, while the negative balance between habitat quality and water yield was a typical feature of the study area, and it only showed a weak mitigation trend with the promotion of ecological restoration; (4) Scenario simulation shows that high-quality development scenarios can achieve ESs collaborative promotion, which is the best way to give consideration to ecological protection and double carbon targets; (5) Natural factors (precipitation, slope, evapotranspiration) determine the basic pattern of ESs spatial differentiation, and human factors such as GDP and population strengthen the trade-off/synergy effect between services through land development and urban expansion. This study reveals the high sensitivity of ESs in resource-based cities to land use change, which can provide scientific basis for land space optimization and ecological restoration policy formulation under the goal of “dual carbon” in similar areas.

The high-quality development of resource-based cities is critical to achieving the United Nations Sustainable Development Goals (SDGs), yet the traditional resource-dependent model tends to cause conflict among economic, social, and ecological systems. China's concept of new quality productive forces offers a way to break through resource lock-in. This study builds an SDG-oriented indicator system and measures the high-quality development level of 103 Chinese resource-based cities from 2013 to 2023 using the CRITIC objective weighting method. Drivers are identified across scientific and technological, digital and intelligent, and green productive forces, and an interpretable XGBoost-SHAP framework is used to quantify their marginal contributions, threshold effects, and interactions. Results show that (1) the overall level rose with fluctuations, and the spatial pattern evolved into a polycentric configuration of an eastern lead, a rising central region, and breakthroughs in the west; (2) the principal predictors are digital factor allocation, technology transfer activity, and industrial restructuring, with digital and intelligent productive forces mainly having independent main effects, scientific and technological productive forces relying on research commercialization, and green productive forces imposing baseline constraints; and (3) the drivers have significant nonlinear thresholds. Digital factor allocation, digital infrastructure, and technology transfer activity show accelerated enabling effects after crossing their thresholds, while labor quality, digital application, and scientific and technological innovation investment follow inverted-U trajectories. The strongest interaction occurs between digital factor allocation and basic accessibility. These findings offer quantitative evidence and governance implications for resource-based cities seeking to advance the SDGs.