Tourism-related carbon emission efficiency is an important indicator that reflects the sustainable development of tourism and can better balance the relationship between negative environmental impact and economic value. According to panel data of 30 provincial regions, “the tourism value added coefficient” (not including the Tibet Autonomous Region) in mainland China from 2000 to 2019, we estimate the tourism of each provincial administrative unit carbon emissions, measure the tourism carbon efficiency value, and analyze the measurement results of the change trend, spatial differentiation characteristics, and influencing factors. The results show that (1) the carbon emission efficiency of regional tourism in China increased significantly from 2000 to 2019, but there was a significant difference in the carbon emission efficiency of tourism among regions, and the sustainable development level of regional tourism was still unbalanced. (2) The spatial pattern of provincial administrative units in China has the adjacent characteristics of High-High agglomeration and Low-Low agglomeration, the difference in the tourism eco-efficiency development level among regions gradually decreases with time, and there is a dynamic convergence characteristic. (3) The q value represents the intensity of the impact factor on tourism carbon emission efficiency. According to the q value, the factors affecting tourism carbon emission efficiency were divided into dominant factors (0.5 ≤ q ≤ 1), inducing factors (0.2 ≤ q < 0.5) and driving factors (0 ≤ q < 0.2), among which the level of technological development was the dominant factor. The level of opening-up to the outside world is the inducing factor; environmental regulation intensity, urbanization level, regional economic development level, tourism industry environment, and tourism infrastructure are the driving factors. (4) The influence degree of influencing factors on the spatial differentiation of tourism carbon emission efficiency is significantly different in different periods. The degree of influence of the urbanization level and tourism industry environment shows an upward trend over time, and the influence degree of other factors shows a “V-shaped” trend. (5) The two-factor interaction will significantly enhance the spatial differentiation of regional tourism carbon emission efficiency, and the interaction between the level of scientific and technological innovation and other influencing factors has a deeper impact on tourism carbon emission efficiency.

The study analyzed the spatial distribution characteristics, evolution rules, and driving factors of 138 China’s national agricultural cultural heritage sites from 2013 to 2021 at the overall and regional levels, using kernel density analysis, Centres for standard deviation ellipse analyses, spatial autocorrelation analysis, and geographical detector analysis.The results showed that: ①From an overall perspective, the spatial pattern of China’s national agricultural cultural heritage changed greatly from 2013 to 2021, with a highly uneven spatial distribution, gradually showing a distribution pattern of "widely distributed, locally concentrated". The spatial distribution of China’s national agricultural cultural heritage is increasingly evident, and the spatial distribution type has evolved from discrete to clustered. The spatial distribution center of gravity shows a shift trajectory of "north-east, then south-east". During the study period, the X axis of the standard deviation ellipse was always greater than the Y axis, but the difference between the X and Y axes was small, indicating that the spatial distribution direction was northeast-southwest, but the directionality was weak. The types of national agricultural cultural heritage are diverse and rich, involving farmland landscapes, composite systems, crop varieties, vegetables and melons, tea, forest fruits, special products, farmland irrigation, and animal breeding, in which forest and fruit class heritage site dominate. ②From a regional perspective, the spatial distribution of China’s national agricultural cultural heritage varies greatly, with strong national and regional characteristics. The high-density core area of the national agricultural cultural heritage in 2013 was located in the intersection of Fujian, Zhejiang and Jiangxi. After 2017, the high-density core area moved northward to the Yangtze River Delta region, which was caused by a combination of economic, cultural, and geographical factors. In addition, the agglomeration of the intersection edge area of Guizhou, Hunan and Yunnan provinces has emerged in 2021. In analyzing spatial autocorrelation, drawing on existing relevant research results, the study selected county-level administrative districts as the research unit. The analysis results show that there is a positive spatial correlation between China’s national agricultural cultural heritage sites in 2017 and beyond, with the spatial distribution types mainly being LL and LH. During the study period, the number of LL and HH type areas has been increasing, indicating that the positive spatial correlation between China’s national agricultural cultural heritage sites is gradually strengthening.③In terms of influencing factors, the spatial pattern of China’s national agricultural cultural heritage is affected by factors such as regional economic development level, policy guarantee, transportation accessibility, cultural environment, per capita economic development level, population status, primary industry economic development level, secondary industry economic development level, tourism resource endowment, temperature, precipitation, terrain, and rivers. Among them, the impact of tourism resources, regional economic development level, and policy guarantees are more significant. The explanatory power of the interaction between any two factors is greater than that of a single factor, and there are differences in the strength of the interaction between each influencing factor.

The healthy development of the ecosystem and tourism in destinations plays an essential role in sustainable development. Taking Shennongjia as an example, we analyzed the spatial–temporal variation in the ecosystem services value (ESV) and investigated the impacts of tourism on ESV and their spatial heterogeneity using the geographically weighted regression (GWR) and boosting regression tree (BRT) models. The results showed that (1) the types of ecosystem services (ESs) were dominated by climate regulation and biodiversity. The ESV increased from 3.358 billion yuan to 8.910 billion yuan from 2005 to 2018 and showed significant spatial divergence, maintaining a long-term distribution pattern of high in the center and low at the border. (2) The GWR and BRT results showed that the Distance to Scenic Spots (DSS) and the Distance to Residential Areas (DRA) are important factors influencing ESV, with the Distance to Hotels (DH) and the Distance to Roads (DR) having a relatively weak influence on ESV. (3) The influencing factors presented positive and negative effects, and the degree of influence has spatial heterogeneity. The DRA and DH inhibited the increase in ESV in nearby areas, while DR was the driving factor for increasing ESV. The assessment results of DSS vary according to the models.