Promoting the green development of tourism industry is the due meaning of responding to the targets of "carbon peak and carbon neutrality" and achieving high-quality development in the new era. The super-efficiency SBM model and multi-spatio-temporal analysis methods were used to quantitatively explore the spatio-temporal pattern and dynamic evolution characteristics of tourism green development efficiency of cities along the Yellow River Basin from 2010 to 2020, and the the dynamic response relationship between the tourism green development efficiency and the driving factors was revealed by adopting panel quantile regression model. The main results show that: (1) With the passage of time, the green development efficiency of tourism industry in the Yellow River Basin showed a tortuous dynamic change trend, and the non-equilibrium between regions always existed, but there was a dynamic convergence trend in the differences of green development efficiency of tourism industry. In terms of spatial distribution, the number of areas with medium efficiency occupied the mainstream, showing a gradual differentiation pattern from the upper reaches to the middle and lower reaches of the Yellow River. (2) Regarding spatio-temporal dynamic characteristics, both the local spatial structure and the network of dependency relationships of tourism green development efficiency in the Yellow River Basin were relatively stable, but there was a situation of synergistic growth and spatial competition in the direction of migration. (3) In the process of spatio-temporal transition, most municipal units showed strong transfer inertia or spatio-temporal inertia, indicating that their local spatial states are difficult to change in a short period of time. (4) From the perspective of driving factors, tourism economy, industrial structure, science and technology, transportation convenience and urbanization level jointly affect the evolution of the efficiency pattern of green development of the tourism industry in the Yellow River Basin, but there are differences in the effects of each influencing factor in different quartiles. Specifically, the low-quantile units of green development efficiency in tourism industry were mainly influenced by the scale of tourism economy, the degree of opening to the outside world, and the level of urbanization; while for the units with high-quantile, the optimization of factors such as industrial structure, transportation convenience, and science and technology had a greater positive marginal effect on the efficiency improvement of such areas. Finally, according to the above research results, the relevant policy recommendations were put forward, which can provide some reference for optimizing the green development efficiency pattern of tourism industry in the Yellow River Basin and promoting regional ecological protection and high-quality development.