As urbanization and industrialization have advanced in leaps and bounds, the territorial spatial pattern of Qinghai has experienced profound transformation and reconstruction, which has been directly reflected in land-use changes and affected the eco-environment. In this context, we constructed a functional classification system of “production-living-ecological” (PLE), used remote sensing data for six periods from 1980 to 2020, and employed the land transfer matrix, eco-environmental quality index, ecological contribution rate of land-use transformation and geographical detectors to analyze the changes in the territorial spatial patterns, eco-environmental effects and driving forces of eco-environmental quality. The results revealed that (1) the spatial distribution of the province was characterized by the relative agglomeration of the production and living spaces and the absolute dominance of ecological spaces; (2) The eco-environmental quality of the region portrayed a steady improvement, with a significant reduction in the medium–low and low-quality areas; and (3) the annual average precipitation, proportion of non-agricultural area, and socio-economic factors had a significant impact on the eco-environmental quality of the region, meanwhile, national economy and ecological policies are important indirect driving forces of eco-environmental quality. Our findings will provide guidelines for territorial spatial management and serve as a reference for eco-environmental protection in Qinghai.

Exploring the complex dynamic relationship between urban–rural integrated development and land-use efficiency can contribute to most efficient urban–rural land-use and the rational promotion of urban–rural integrated development. This study established an evaluation model of urban–rural integrated development, adopted the super-efficiency SBM model to measure land-use efficiency, and studied the evolution of the spatial–temporal patterns of urban–rural integrated development and land-use efficiency coupling in the Yellow River Basin. We also examined the factors affecting them with the help of the coupling coordination degree model, non-parametric kernel density estimation, and geographic probes. The results indicate the following: (1) Within the study period, the coupled coordination of urban–rural integrated development and land-use efficiency was similar to the spatial distribution characteristics of land-use efficiency, both showing a “high at both ends and low in the middle” trend. (2) The coupled coordination increased over time; however, a lagging land-use efficiency was a crucial impediment to improving the coupling coordination degree. (3) Carbon emissions, urbanization rate, and per capita GDP were key drivers. The results of this study can provide a reference for local governments in the Yellow River Basin and other similar areas to propose paths to optimize the allocation of urban and rural land-use.