Promoting the high-quality development of the tourism economy has become an important challenge. Based on panel data on 31 provinces in China during 2009–2019, this study uses spatial econometric and threshold regression models to analyze the spatial spillover effects and threshold characteristics of tourism industry agglomeration on the high-quality development of the tourism economy. The results show that the overall level of high-quality development of China's tourism economy shows an upward trend, with differences between different regions. The agglomeration of tourism industry has a significant positive impact on the high-quality development of the tourism economy and shows strong spatial spillover effects. Further, the level of agglomeration has a double-threshold effect on the high-quality development of the tourism economy. Based on these results, we propose countermeasures to promote the coordinated and linked development of the tourism industry in different regions, providing important insights for further enhancing the high-quality development of the tourism economy in China.

Achieving resilient development is an important way for tourist attractions to cope with the negative impacts of major public health events, and an accurate assessment of the existing resilience level is the basis for improving the resilience of tourist attractions. Based on resilience theory, the impacts of major public health events on tourist attractions and the relationship between the impacts and the development resilience of the tourist attractions, this study uses the composite index method and DEMATEL method to construct an index system for evaluating the development resilience of tourist attractions. This evaluation index includes 20 indicators in the four dimensions of prevention ability, resistance ability, recovery ability and renewal ability, and the weight of each indicator was determined. The results show three important aspects of tourist attraction resilience. (1) Resistance ability is the most important dimension that reflects the resilience level of tourist attractions, followed by renewal ability and recovery ability, while prevention ability is relatively less important. (2) Tourism revenue reconstruction, mechanism innovation, marketing flexibility and financing ability have large positive correlations with the resilience level of tourist attractions. (3) Market flexibility, management decision-making level, financing ability and intelligent construction level are susceptible to other indicators, so that more attention should be paid to them in the process of improving the resilience level of tourist attractions. The index system developed in this study can provide scientifically valid guidance and a useful reference for tourist attractions to accurately examine their own issues and improve their development resilience.

Despite the rapid development of flower-viewing tourism in China in recent years, there is almost no systematic research on it. Therefore, this study analyzes the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China using the spatial statistical analysis methods and the geographic detector method. The study uses the Point-of-Interest data of flower-viewing tourist attractions from networks such as Qunar and Ctrip, the flower observation data from China Phenological Observation Network, Chinese network news, and Weibo, and the statistical data from yearbooks. The results are as follows: 1) The spatial attribution type of flower-viewing tourism in China is aggregated into areas, including two high-density aggregated areas, three medium-density aggregated areas, and one general-density aggregated area. Furthermore, five major types of flower-viewing tourist attractions have formed several aggregated areas. 2) The time of flower viewing in China starts from about February and lasts about eight months till October each year. Florescence and flowering time of different ornamental flowers in different regions are different. 3) The spatial and temporal distribution characteristics of flower-viewing tourism in China are mainly affected by ornamental flower phenology, spatial distribution characteristics of flower-viewing resources, regional permanent population size, youth population size, female population size, regional GDP, and added value of the tertiary sector. These conclusions clarify the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China. They could provide a scientific basis and useful reference for the coordination and sustainable development of regional flower-viewing tourism in China.

The dynamic change in land use can reflect the change in the ecological environment and social economy. Zhangjiajie is the famous mountain tourist city in China having a dual core central structure constituting the urban central area and Wulingyuan Scenic Area (referred to as DCC). This study is based on the land use data of Zhangjiajie in 2000, 2010, and 2020. It analyzed the dynamic change in the pattern of land use, its cause and effects using the method of human-computer interaction for remote sensing image interpretation. The study revealed: (1) the growth of construction land is the maximum, while cultivated land and grassland are mostly transformed into construction and forest land. (2) The reasons why Zhangjiajie with limited cultivated, and idle industrial land was mainly transformed into tourism construction land, especially the townships around DCC. (3) The development of townships around DCC should build industrial belts for coordinated development. This study attempts to analyze the development dilemma and outlet of Zhangjiajie’s DCC on its surrounding 12 townships using the results of land use change aiming to realize the integrated development of DCC and township area, to provide practical experience for green development of township industry around mega-tourist attraction.