Understanding spatiotemporal changes in landscape ecological risk is essential for regional ecological security and sustainable land management, particularly in environmentally sensitive areas. Using land-use data from five time points (2000, 2005, 2010, 2015, and 2020) together with topographic, climatic, vegetation, and socioeconomic data, we assessed landscape ecological risk dynamics in Xinzhou City, a typical ecologically sensitive region in the middle Yellow River Basin. We integrated a landscape ecological risk assessment model, spatial autocorrelation analysis, and an optimal-parameter geographical detector (OPGD) to identify the spatiotemporal patterns and key drivers of ecological risk. Built-up land expanded by 131.47% over the study period, while cropland and grassland both contracted. Land-use change was dominated by bidirectional conversion between cropland and grassland, alongside a net shift of both to built-up land. Overall, ecological risk declined: high- and relatively high-risk areas decreased by 1354.15 km². Spatially, the pattern remained stable, with higher risk in basins and lower risk in mountainous regions, although the trend varied across phases. Risk exhibited significant spatial clustering: low–low clusters remained stable in mountainous ecological source areas, whereas high–high clusters persisted in basin agricultural areas. Elevation was the dominant factor in spatial risk differentiation. Combined natural and anthropogenic factors shaped the overall risk pattern. Despite the regional decline, urbanization-induced disturbance remains the principal driver of local risk increases. Our findings demonstrate the value of coupling long-term land-use data with OPGD to evaluate the relative and interactive contributions of terrain constraints and anthropogenic drivers in complex mountain–basin systems, with implications for spatially targeted ecological restoration and sustainable land management in ecologically sensitive transition zones.

Urban expansion exerts substantial pressure on regional ecosystems; however, how these effects propagate through direct and indirect pathways at the urban agglomeration scale remains insufficiently understood. Using nighttime light (NTL) and statistical yearbook data, we extracted the built-up areas across the Beijing–Tianjin–Hebei (BTH) region using a threshold-based approach to characterize expansion dynamics from 1992 to 2022. Furthermore, we applied the PKU GIMMS NDVI dataset within a conceptual framework to quantify the direct and indirect effects of built-up area expansion on vegetation. Expansion patterns varied markedly among cities: Beijing demonstrated concentric outward growth, Tianjin exhibited dual-core development, and cities in eastern and southern Hebei followed a leapfrog, dispersed pattern. Expansion rates and intensities also diverged considerably: Beijing and Tianjin sustained prolonged, high-intensity growth, whereas cities in northern and western Hebei expanded more gradually. The centroid of built-up areas remained relatively stable in Beijing and Tianjin but shifted in other cities, where expansion concentrated along one or two primary axes. Direct negative effects, driven by impervious surface expansion, intensified with increasing urbanization pressure, reaching approximately −54% in rapidly expanding urban agglomerations by 2007 and peaking at −67.43% at the city scale in Beijing by 2022. In contrast, indirect effects exhibited pronounced spatiotemporal heterogeneity: they fluctuated in rapidly expanding urban agglomerations but increased markedly in other areas after 2012. The strongest indirect positive effect peaked at the city level (64.85% in Handan in 2022), suggesting gradual vegetation recovery toward the end of the study period. These findings suggest that moderate-growth cities with remaining green space may exhibit relatively stronger ecological compensation potential, but this pattern requires further validation across broader urban agglomerations. This underscores the need for spatially differentiated planning to balance urban growth and ecological sustainability.