Compound erosion by multiple forces is the most significant feature of soil erosion on slope cropland in rolling hill regions with black soil in northeastern China. Compound erosion by wind and water is one of the important erosion types to aggravate the effects of soil erosion on slope cropland. In this study, on the experimental slope cropland in rolling hill regions, field observations of meteorological conditions, wind erosion and water erosion, and statistical methods were used to reveal the intra-annual alteration of erosion forces on compound erosion by wind and water and to analyze the intra-annual temporal succession characteristics of wind erosion and water erosion.Based on the threshold of wind speed for sand saltation (5 m/s) and erosive rainfall amount (12 mm/d) in rolling hill regions with black soil in northeastern China, the criteria for dividing the wind-dominated force and rainfall-dominated force of complex erosion on the experimental slope cropland was determined. The alteration of erosion forces of compound erosion by wind and water on the experimental slope cropland was divided into three stages: wind-dominated period Ⅰ(WDⅠ: Mid-March to Mid-July), rainfall-dominated period (RD: Mid July to Early October), wind-dominated period Ⅱ(WDⅡ: Early October to Mid-November). Surface creep erosion by wind accounted for about 92.95% of the total erosion amount by wind on the experimental slope cropland. Wind erosion rate in wind-dominated period was calculated at 432.9 g/m² in WDⅠ and 40.95 g/m² in WDⅡ. The rainfall erosion rate in rainfall-dominated period was estimated at 485.15 g/m².The wind erosion and water erosion on the experimental slope cropland showed temporal succession characteristics with the intra-annual alternations of erosion forces, following the order of water erosion rate in RD > wind erosion rate in WDⅠ>wind erosion rate in WDⅡ.

Based on the land use data of the Yihe River Basin from 1975 to 2020, the GIS technology was used to construct and analyze the land use change trajectories. It also used the FLUS (further land use simulation) model to simulate land use scenarios of the basin in 2030 and 2050 under the “production-living-ecological” space paradigm, and visualize development patterns of the land use under different management modes. The results showed that: 1) From 1975 to 2020, the land use was primarily characterized by the reduction of arable land (accounting for about 10% of the basin area) and the expansion of construction land (accounting for about 8% of the basin area). 2) The land use change the Yihe River Basin could be divided into two stages: the early stage (1975-1995) and the later stage (1995-2020). During the early stage, about 22% of the area suffered land use transfer, mainly manifesting as mutual change of arable land, forest, and grassland. In the later stage, about 46% of the total area changed to another land use type, with a major tendency of arable land transferring to construction land. Both the trajectory changes and the spatial pattern of land use were more complex and significant. 3) The land use pattern of the basin was transferring towards a focus on ecological construction. From 2020 to 2030, the natural development scenarios was more consistent with the ecological space priority scenarios, but this convergence declined by 2050. This study can serve as a reference for further optimization of the “production-living-ecological” space pattern and ecological construction in the basin.

The flood event has always been endangered high-quality development as for human society. Reconstructing and analyzing the impact-response process of the past flood events would be helpful to realize the mechanism and process of extreme climate events to human response, which could improve the adaptive capacity for natural disasters among human beings. In this study, archives and other historical documents were collected to reconstruct the spatial and temporal process of the flood event in 1811 Aksu. Furthermore, 26 points and 73 lines were extracted from above documents to reconstruct the impact-response process of this flood event, and social network analysis was applied to analyse the patterns of human interactions with climate change in the arid region. The main conclusions are as follows: 1) The flood event in 1811 Aksu was happened in the background of climate warming and humidification, and the interaction within the natural system among constant rainfall, ice and snow melt water, steep terrain exacerbated the impact of this flood event. 2) The main high-risk areas centralized in the Aksu city and adjacent villages, farmland. It was partly because the lower terrain and intense populations, various commodities near the city were prone to suffered by flood and waterlogging. 3) The flood affected the supporting system and population subsystem directly and indirectly affected the population subsystem, economic subsystem and social subsystem. In this process, there were 4 points (urban waterlogging, food production damaged, infrastructure damaged, famine) represented the main impacts of this flood event. 4) The human responses changed over time influenced by different disaster phases, including adjustment and adaption, which jointly effected to avoid the occurrence of post-disaster malignant events. And people constructed flood control engineering to prevent the occurrence of flood events that maintained the security and stability in northwestern frontier society during the middle and late Qing dynasty.

The data from the fifth to seventh national censuses was used to explore a grid based method for agricultural population based on land use types, 1.5 km of agricultural population grid density data in Shaanxi province was obtained to reveal the current characteristics and spatiotemporal evolution process of agricultural population distribution. Research found that in 2020, the agricultural population in Shaanxi province was densely distributed in the Guanzhong Plain and Hanzhong Basin, while the Northern Shaanxi Plateau and Qinba Mountains were relatively sparse. At the same time, the agricultural population is relative densely distributed in river valleys, while the density is extremely low in urban core areas, difficult to use land, and ecological protection and water conservation areas. From 2000 to 2020, the overall agricultural population density in Shaanxi province has generally decreased, but there are differences in the decline rates among different regions, leading to increased spatial heterogeneity. The reason may lie in the different changes in land use types and the slowdown in agricultural population size. The accuracy verification found that the agricultural population grid data has good consistency with the census data, and the fitting accuracy of the agricultural population grid dataset is relatively high. The research has alleviated the problem of plasticity area units, fully captured the detailed information of agricultural population distribution, and has policy reference value for accelerating the shaping of reasonably distributed modern agricultural human resources and achieving comprehensive rural revitalization.

As a driving force for new industries, the digital economy has emerged as a pivotal force in enhancing the efficiency of the tourism sector, critically contributing to the attainment of high-quality development in China’s tourism industry.Utilizing provincial panel data spanning from 2011 to 2020, this study employs the entropy weight TOPSIS and super efficiency SBM models to gauge the level of digital economy development and tourism industry efficiency. Furthermore, a comprehensive analysis is conducted using the two-way fixed effects model, adjustment effect model, and spatial Dubin model to explore the influence mechanism and effects of digital economy development on tourism industry efficiency. Findings reveal that digital economy development significantly boosts tourism industry efficiency, a conclusion upheld even after rigorous robustness tests. Analysis of regulatory mechanisms indicates that tourism intensity and the structure of the tourism industry positively moderate the relationship between digital economy development and enhanced tourism industry efficiency. Results from the spatial Dubin model demonstrate that the digital economy development within a province notably enhances its own tourism industry efficiency while exhibiting negligible spatial spillover effects on neighboring provinces’ tourism industry efficiency. Heterogeneity analysis further reveals that, compared with the eastern region, digital economy development in the central and western regions exerts a more pronounced influence on tourism industry efficiency.

Rural tourism is an important engine for achieving the strategy of rural revitalization. Exploring the spatio-temporal evolution laws of rural tourism destinations is of great significance for promoting high-quality development of rural tourism. Based on the theory of “production-living-ecological” function, 303 provincial-level key rural tourism villages in Shaanxi province are taken as research objects to study the temporal-spatial distribution characteristics and influence mechanism of rural tourism destinations in Shaanxi province by using the methods of GIS spatial analysis and geographical detector. The conclusions are as follows: 1)The spatial distribution of all rural tourism destinations in Shaanxi province is characterized by gathering in mid to low altitude terrain, near the main transportation line, along rivers and lakes, showing a developing trend of polarization and sheet diffusion. Rural tourism destinations with dominant function production have the greatest spatial dependence on transportation and hydrological conditions.2)There are certain differences in the spatial distribution and evolution of rural tourism destinations dominated by different functions. Rural tourism destinations primarily driven by production functions exhibit the highest degree of agglomeration, displaying a contiguous expansion trend, and are predominantly situated in areas with flat terrain and dense river networks.The distribution of rural tourism destinations driven by life functions is largely consistent with the overall distribution, and there is a noticeable increase in the agglomeration of the high-density core areas.Rural tourism destinations driven by ecological functions exhibit a clear trend of outward expansion. These destinations are predominantly located in the border regions between cities, forming a point-to-axis distribution pattern. Additionally, a high-density distribution area has emerged at the southern foothills of the Qinling Mountains.3)There are differences in the influencing factors of spatial differentiation of rural tourism destinations dominated by different functions. Relevant policies exert the strongest influence on the spatial distribution of rural tourism destinations dominated by production functions. Rural tourism destinations dominated by life functions have a high spatial dependence on population distribution and surrounding scenic areas, while rural tourism destinations dominated by ecological functions are significantly affected by climate conditions and air quality.4)Natural ecological environment determines the basic spatial distribution pattern of rural tourism destinations, economic development level is an important driving force for the formation and development of rural tourism destinations, social and political conditions are guiding factors. Resource endowment foundation plays a prominent driving role in the spatial distribution differentiation of rural tourism destinations across various functional types. Furthermore, the interactive enhancement effect with economic development level surpasses that with social and political conditions.

Taking all cities in Hunan province as the research object, the theoretical analysis framework of the integration level of cultural tourism industry was defined and the evaluation index system of the integration level of cultural tourism industry was constructed. The coupling coordination degree model, temporal evolution characteristics and spatial pattern characteristics visualization methods were used to measure the spatio-temporal evolution trend of the level of the cultural tourism industry, and the PVAR model was used to analyze the dynamic coupling relationship among the subsystems of the integration level of cultural tourism industry. The geo-detector model was used to explore the dominant factors affecting the integration level of cultural tourism industry and to detect the interaction effects among the factors. The main conclusions are as follows: 1) In 2009-2021, the integration level of culture tourism industry of cities in Hunan province can be divided into three types, the overall level shows an upward trend, but the differences within the region are also widened, and the expansion trend is significant. 2) During 2009-2021, the overall coupling coordination level of cities in Hunan province is still mainly in dysfunction class, with Changsha demonstrates a high degree of coordination class, Yueyang, Zhuzhou, Hengyang and Changde exhibit basic coordination class, and the remaining 9 cities are still in basic dysfunction class. 3) There exists an obvious dynamic coupling relationship among the subsystems of the industrial integration foundation, industrial integration support, and industrial integration volume in each city during the study period. 4) The 7 driving factors led by fiscal policy are the dominant factors influencing the integration level of cultural tourism industry of cities in Hunan province, and the factor interaction effects of fiscal policy, science and technology innovation and consumption capacity are strong.

To establish a tourism-friendly bay area, it is essential to assess the cross-sea accessibility of the Pearl River Estuary, thereby effectively addressing the connectivity issues between the eastern and western shores of the bay area. Utilizing the cost-weighted grid method, this study examines the impact of newly built cross-sea channels on the accessibility of tourist attractions in the Greater Bay Area (GBA) from four aspects: changes in isochrone area, daily accessibility, weighted average travel time, and tourism economic linkage intensity. Taking the Hong Kong-Zhuhai-Macao Bridge and the Shenzhen-Zhongshan Channel (hereinafter referred to as “B&C”) as examples, the study analyzes their influence. The conclusions are as follows: 1) Within a certain spatial scope, there is a marginal diminishing effect on the improvement of tourist attraction accessibility, and the enhancement effect declines with distance from the starting and ending points of the cross-sea tunnels. The main contradiction in improving GBA accessibility has shifted from absolute value enhancement to controlling the expansion of regional disparities and structural imbalances. 2) The impact of B&C on tourism accessibility is concentrated mainly on the eastern and western shores of the Pearl River Estuary, with insignificant effects on the central region. Specifically, the HKZMB primarily enhances the area of the 2-hour traffic circle in the GBA, while the Shenzhen-Zhongshan Channel mainly expands the 1-hour traffic circle. 3) In terms of attraction accessibility, B&C significantly increase the number of attractions reachable within 1 hour on both shores of the Pearl River, enabling the areas around the Pearl River Estuary in the GBA to form a relatively close tourism circle. The overall attraction accessibility is compressed from 1.20 hours to 1.12 hours, with Zhaoqing, Jiangmen, and Huizhou representing weaknesses. 4) Measuring the changes in the tourism economic landscape of the GBA based on tourism economic linkage intensity reveals that B&C have not altered the three core clusters of Guangzhou-Foshan, Shenzhen-Hong Kong, and Zhuhai-Macao, but rather further consolidated their agglomeration trends.

Though online reviews on social media platforms have been widely used in tourism research as data analytical sources in recent years, how they can be applied to destination recommendation needs further investigation.The review data of 239 5A scenic spots in China was retrieved from ctrip.com by Python programming and web-crawling technology. Natural language processing and deep learning technologies including BERT (Bidirectional Encoder Representations from Transformers) and word embedding were then imported to build a destination recommendation system for tourist destinations. The model was trained and validated on a dataset containing 57 360 reviews, with a classification accuracy of around 78% reached on 14 340 pieces of test data. Experimental results show that, with the aid of other tourists’ travel experiences and image perception, the proposed model can facilitate potential tourists in finding their ideal destinations to explore the first step of itinerary planning. The findings of this study extend the research scope of online reviews within tourism and hospitality and provide new insights into pre-trip travel counseling.

Based on the panel data of 30 provinces in China from 2006 to 2020, the article constructs an index system for evaluating the development efficiency of rural public cultural services, uses the super-efficient SBM model and Malmquist index model to conduct static and dynamic analyses of the development efficiency in the east, west and national regions. The study also analyzed the spatial distribution of the development efficiency through ArcGIS, and analyzed the drivers and threshold effects of the development efficiency of rural public cultural services with the help of fixed-effects and threshold models. The study found that:during the study period, the efficiency of rural public cultural services in China was generally on the rise, and the growth rate of total factor productivity continues to slow down.The efficiency of rural public cultural services among regions shows an imbalanced state, forming a regional pattern of “east>west>central”.Analysis based on a panel data fixed-effects model shows that residents’ demand for cultural consumption, the degree of government attention and the scale effect all significantly affect the efficiency of rural public cultural services. In addition, there are single and double threshold effects on the efficiency of rural public cultural services based on the input of rural public cultural services in the national and east-central regions respectively.