Clarifying the relationship between tourism and green development is conducive to promoting the harmonious coexistence of tourism industry benefits and economic and environmental systems. The externalities of tourism on economies and the environment have sparked numerous fascinating academic research debates; however, few studies have considered the impact of tourism on green development that balances economic growth and environmental protection. This study selects the green development efficiency measured by the super-efficient SBM model with undesired output as a proxy indicator of green development and adopts the panel data regression model and dynamic panel threshold regression model to investigate the linear impact and non-linear characteristics of tourism on the green development efficiency for 284 cities in mainland China at the prefecture level and above. The main findings are as follows: (1) Although China’s green development efficiency showed an upward trend during the study period, the overall level was not high. (2) Tourism has significantly promoted the improvement of China’s green development efficiency, indicating that tourism has become an effective driver of China’s economic green transformation. (3) This type of positive promotion of green development by tourism has a non-linear threshold characteristic, which means that, with the continuous improvement of the development level of the tourism industry, after crossing a specific threshold value and entering a higher level of development, the tourism industry will have an increasing marginal impact on the green development efficiency.

The quantitative evaluation of the intensity of regional human activity can reflect changes in the relationship between people and the environment and provide a scientific basis for the formulation of land-use policy and for the construction of the ecological environment. This paper adopted the ratio of the area of construction land to the total area to calculate human activity intensity in Inner Mongolia at the league/city, banner/county, and pixel levels, respectively. On this basis, the overall change in human activity intensity and its spatiotemporal differentiation, geographical unit change, and spatial autocorrelation were analyzed. The results are as follows: (1) The intensity of human activity increased from 2000 to 2020. The intensity of human activity in Inner Mongolia was 8.71% in 2000, and it increased to 8.73% in 2010 and to 9.71% in 2020. The growth rate has accelerated since 2010. (2) The areas with high and medium intensity of human activities are mainly concentrated in the area south of the Hinggan–Yinshan–Helan Mountains. The intensity in the Hulunbeier grassland area and Alxa desert area is relatively low, and the diffusion effect gradually becomes prominent in the proximal local area. (3) The results for the detection of influencing factors indicate that the livestock density, multi-year average precipitation conditions, and population density have significant driving effects on the changes in intensity of human activity in Inner Mongolia.