The coordinated development of plateau tourism and ecological environment is an important content in balancing human-land relations. Under the influence of climate change and human behavior, grasslands in northwest Sichuan have experienced varying degrees of desertification, which severely restricts the sustainable development of local tourism economy. This paper takes Zoige County as the study area, uses remote sensing data and the alpine grassland desertification index (AGDI), to measure the grassland desertification situation from 2015 to 2021, analyzes the characteristics and patterns of tourists’ trajectory from 2015 to 2021 based on trajectory big data. Then the coupling coordination model was used to explore the spatiotemporal response between grassland landscape quality and tourists’ trajectories, and explores the temporal and spatial responses between the grassland landscape quality and tourists' trajectories with the help of the coupled coordination model. The results show that: (1) From 2015 to 2021, the area of sandy grassland in Zoige decreased by 14.91% overall, while the landscape quality of grassland increased by 2.87%. The severe and moderate sandy areas in the middle of Zoige were gradually reduced. (2) From 2015 to 2021, the number of tourism trajectories in Zoige showed a fluctuating upward trend. The research discovered three types of self-driving modes: G213 National Highway self-driving pattern, the Yellow River grassland self-driving pattern, the S217 Provincial Highway self-driving pattern; three types of hiking modes: the Namo Canyon hiking pattern, the S217 Provincial Highway hiking pattern, and the Huahu Lake Scenic Area hiking pattern. All six types of tourists’ trajectory modes were distributed along scenic areas and transportation arteries (national and provincial roads). (3) From 2015 to 2021, the coupling degree between the quality of grassland landscape and tourist trajectory in Zoige increased from 0.22 to 0.71, and the coupling coordination degree increased from 0.3 to 0.74, developing from intermediate dissonance to intermediate coordination. This study attempts to analyze the spatiotemporal response between tourists' spatial behavior and ecological environment with tourist trajectory data, providing a new idea for improving the research accuracy of tourism activities' environmental impact, and providing theoretical support for plateau grassland resource protection and tourism utilization management on the plateau.

Natural disasters are one of the impacts and threats to the sustainable development of tourism. In this study, 1268 Chinese and English literature were selected from the CNKI database and the Web of Science database, and the distribution of co-occurrence words was visualized through a knowledge graph to analyze the development context and research hotspots of tourism research in the context of natural disasters. The findings are as follows: (1) Destination risk assessment, tourist risk perception, emergency management, sustainable development, and resilience construction of tourism are hotspots of tourism research in the context of natural disasters. (2) International research areas in this field are mainly concentrated in countries and regions with developed island tourism, such as Japan, New Zealand, the Mediterranean Sea, and Southeast Asia, and the main types of disasters concerned are hurricanes, tsunamis, and volcanoes. Domestic research areas in China are mainly concentrated in southwest China, especially in Sichuan Province, where geological disasters are widespread. The Wenchuan and Jiuzhaigou earthquakes are classic research cases in this field. (3) Tourism research theme in the context of natural disasters presents a clear interdisciplinary feature. Based on the coupling research of natural disasters and tourism, the framework of “tourism research in the context of natural disasters” is proposed by integrating the characteristics of stakeholders in tourism activities and natural disasters and their impact on tourism. (4) Future research on the coupling of natural disasters and tourism should be combined with national strategies to expand new research directions, focusing on topics such as the innovation of travel insurance types, the application of big data, the construction of resilient tourism destinations, and the sustainable development of tourism, to provide guidelines for the tourism industry to improve its capacity to cope with disasters.

Haze pollution is a derivative of human modernity and has become a constraint on the sustainable development of tourism in many countries and regions around the world. This article systematically analyzes foreign literature on the impact of haze pollution on tourism based on 31 English papers published in international journals from 2000 to 2020. It is found that the research on the impact of haze on tourism has gone through four stages: slow start, brief stagnation, steady recovery, and accelerated development. The theories used by researchers are mainly risk perception theory, protection motivation theory, planned behavior theory and Foggy behavior theory. Research methods include econometric method, experimental method, content analysis, geographical spatial analysis, etc. The research theme follows the two logical lines of impact research and coping research, focusing on the impacts of haze pollution on tourism market demand, individual tourists, and tourism destinations, and proposing response strategies from the perspectives of information management, environmental regulation, tourism attraction innovation and technological innovation, and service quality improvement. In view of the deficiencies of the existing studies, this article proposes research prospects by broadening the boundaries of research content, expanding the application of diverse methods, and enriching the application of multidisciplinary theories, in order to provide theoretical references and practical references to maintain the sustainable development of China's tourism industry.

Natural disasters are important influencing factors for the high-quality development of destination tourism. This paper takes 4, 102 tourism-related natural disasters in China from 2011 to 2019 as data source and uses the concentration index, spatial autocorrelation, standard deviation ellipse, and Markov chain to analyze the spatial differentiation and dynamic evolution process from the geographic spatio-temporal perspective. The study shows that: (1) China’s tourism-related natural disasters are characterized by concentrated distribution and a range of types, including typhoons, fog, rainstorms, snow and ice, thunder and lightning, and strong winds that pose high-frequency disaster events. (2) Tourism-related natural disasters exhibit seasonal characteristics in time, with July-September being the high-incidence month with a obvious regional agglomeration effect in space. The high-incidence areas of disasters are found in East China, South China, and Southwest China. (3) Spatial heterogeneity and regional agglomeration are observed for different types of tourism-related natural disasters, and the local spatial correlation characteristics of disasters such as typhoons, collapses, landslides, and waves are obvious. (4) The trajectory of the centre of gravity of China’s tourism-related natural disasters has changed considerably, and the overall distribution pattern is significantly impacted by the scale of disasters in the southeast and southwest regions. Moreover, the spatial pattern presents the “southeast-northwest” and “southwest-northeast” direction. The Markov chain transition probability matrix shows that the dynamic evolution of tourism-related natural disasters has a spatial locking effect and risk transfer effect. This study addresses the existing gaps in the analysis of the temporal and spatial dynamics of tourism-related natural disasters, providing theoretical support and a practical basis for preventing and managing natural disasters in tourist destinations.

Extreme heat and heat waves pose significant dangers to outdoor leisure activities. Revealing the risk pattern and sensitive activity to high temperature can provide scientific basis for public health well-being and sustainable development of tourism. Scholars have rarely addressed the heat exposure associated with outdoor activities in prior research, primarily because dependable data on outdoor activities is scarce. This article fills this research gap by mining trajectory data to reveal the distribution and heat exposure patterns of heat-sensitive outdoor activities. Specifically, this study examined the thermal spatiotemporal pattern of Chengdu during the summer season from 2010 to 2020, utilizing all-weather surface temperature products. By doing so, it identified typical regions characterized by elevated risks of heat exposure. Using trajectory clustering models and trajectory processing algorithms, we additionally unveiled the high temperature exposure risk of critical clusters and nodes of typical outdoor tourism activities. The findings indicate that the thermal pattern of the city of Chengdu is generally warm in the city's core and chilly in the northwest. High and sub-high temperature area encompass the central plain area along the Fourth Ring Road and exhibits an expansion trend to the east and north. Between 2010 and 2020, Chengdu experienced a sustained expansion of high-temperature and sub-high-temperature zones. Outdoor tourism pursuits, including mountaineering and hiking, became more susceptible to elevated levels of heat exposure, with mountaineering being less susceptible to high temperatures than hiking. The public is impacted by elevated temperatures throughout the entirety of their participation in outdoor leisure pursuits. The expansion of high-temperature zones has led to an increasing heat exposure risk of outdoor leisure activity in the northern and eastern Chengdu. Longquan Mountain in the eastern region may lose its climatic superiority in the future, and the areas that are appropriate for outdoor activities may undergo changes temporary and spatially. In light of the findings presented in this article, pertinent management departments may decide to give precedence to the optimization of service and infrastructure resource allocation in urban environments that are susceptible to high temperatures.

The Sichuan-Tibet section of National Highway 318 is a famous tourism corridor and a typical disaster prone area in China. Strengthening the study of heavy rainstorm and the risk of secondary derivative disasters triggered by it in this region is of great significance to comprehensively improve the ability of the tourism industry to cope with natural disasters along the route. In this paper, the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) model was used to extract the main tourism routes along the Sichuan- Tibet section of the National Highway 318 from 21 125 tourist trajectories from 2013 to 2021, and the rainstorm and flood hazard on the main tourism routes were analyzed. The results show that, (1) there are eight main tourism routes on the Sichuan-Tibet section of the National Highway 318. Route 2 (Gongga County, Shannan City to Dazi District, Lhasa City) and Route 5 (Shimian County, Ya’an to Kangding City, Ganzi Tibetan Autonomous Prefecture) are typical cross-city tourist routes. (2) The average annual precipitation along the Sichuan-Tibet section in 2019-2021 is 0.99 mm higher than that in 2013-2015, and the average precipitation in January-December is 6.3 mm higher. The cumulative frequency of rainstorm and flooding along the Sichuan-Tibet section is 5 times lower than that in the period of 991-1949, and the annual peak is reached in July (7.51 times), with January, February and December is the annual low value (0 times). (3) Route 3 has the highest risk of rainstorm and flooding hazard for 2013-2021, and Route 1 and Route 2 have the lowest level of rainstorm and flooding hazard. (4) Route 1 and Route 2 have the lowest rainstorm and flood hazard risk from January to December, and Route 3, Route 7, and Route 8 have the highest rainstorm and flood hazard risk in May.

The successful bidding and hosting of the Beijing Winter Olympics have promoted the rapid development of the domestic ice and snow sports industry. Although China has become the world’s largest emerging market for skiing tourism, the academic community lacks due attention to the injuries that Chinese tourists encounter during skiing. This article is based on 823 domestic tourist skiing injury insurance cases, and explores the characteristics and mechanisms of tourist skiing injuries using the Apriori association rule algorithm. The results show that: (1) there are 22 strong association rules with practical significance between population characteristics, external environment, and tourist injury variables. The formation of specific skiing injury mechanisms is influenced by tourist gender, age, source area, temperature, wind, weather conditions, skiing slopes in combination of other factors. (2) There are 14 effective strong correlation rules between the variables of tourist skiing injury, and there are complex and diverse correlation relationships between the cause, type, location, and degree of tourist skiing injury. (3) The injury situation of skiing tourists in mature international markets can serve as an important reference for studying skiing injuries among Chinese tourist groups, but it is also necessary to consider the uniqueness and differences exhibited by Chinese skiing tourists in terms of injury causes, population characteristics, and other aspects. This study has practical guidance significance for the prevention and control of skiing injuries among Chinese tourists in the post-Olympic era.

Plateau tourism risk management is of great significance to the healthy development of plateau tourism. Methods of seasonal index, spatio-temporal differentiation measure and other methods are applied to reveal the spatio-temporal differentiation of tourism safety events in plateau areas from 2010 to 2019, and identify the driving factors and the effect intensity of spatio-temporal differentiation pattern. The results show that: (1) the number of tourism safety events in plateau areas is increasing year by year, and the temporal variation of them with the seasonal characteristics of “high occurrence in summer and low occurrence in winter”, and the types of those events are complex, but the frequency of accidental injury is the highest; (2) the spatial and temporal distribution of travel-related safety events in the plateau region presents the pattern of agglomeration and differentiation, and the hotspot areas of tourism safety events show an expanding trend year by year, forming multiple high-density areas in the Yunnan-Guizhou Plateau, Yunnan and Sichuan, Qinghai-Tibet Plateau, Xinjiang and Loess Plateau, Henan; (3) tourism safety events in plateau areas show significant spatial positive correlation and spatial high value clustering phenomenon in general, and obvious spatial polarization phenomenon exists in the Yunnan-Guizhou Plateau, Qinghai-Tibet Plateau and Loess Plateau locally, and the clustering scale decreases and the clustering intensity increases; (4) the coupling effect of personnel, facility, environment and management factors leads to the spatio-temporal differentiation of tourism safety events in plateau areas, among which, the number of tourism practitioners, medical security facilities, average gradient, natural ecological environment and tourism resource endowment are the dominant factors, and the two-by-two interaction of those factors will enhance the spatio-temporal differentiation of tourism safety events in plateau areas.

Natural hazards are significant factors affecting the sustainable development of the tourism industry. Under the pressure of global climate change, strengthening the resilience assessment of the tourism industry and its community components constitutes a critical foundational work for promoting the healthy development of tourism. This study constructs a resilience assessment index system for tourism communities in response to natural disasters based on the DPSIR (Driver-Pressure-State-Impact-Response) model, encompassing nine secondary indicators and twenty tertiary indicators. The analytic hierarchy process (AHP) group decision-making method is employed for weighting these indicators. Taking the Hailuogou tourism community after an earthquake as a case study, this research evaluates its resilience from 2020 to 2022 through analysis and empirical investigation, thus testing the applicability of the index system. The results indicate: (1) The analysis of indicator weights shows that the factors that have the greatest impact on the natural disaster resilience of tourism communities include the number of casualties caused by disasters, the completeness of disaster precautions, the perfection of disaster emergency plans, and the number of disaster warning devices. (2) The resilience of the Hailuogou tourism community has shown continuous improvement from 2020 to 2022 and the level of resilience rises year by year. The Ms 6.8 Luding earthquake on September 5, 2022, negatively impacted the driving and pressure system scores that year, but resilience scores for the state, impact, and response systems increased. (3) Fluctuations in the indicators reveal that economic decline is a primary cause for the reduced community resilience of Hailuogou, while the enhancement of emergency capabilities is a key factor for its improved resilience. The index system developed in this study for assessing the resilience of tourism communities facing natural hazards has a solid theoretical and methodological foundation and is applicable to various types of tourism communities. It aids in evaluating their capacity to respond to natural disaster risks and improves disaster risk coping governance.