Spatiotemporal Dynamic Analysis of A-Level Scenic Spots in Guizhou Province, China

Spatiotemporal characteristics and influencing factors of network attention to resort hotels in China

An increasing number of people are gathering travel information online prior to their trips as a result of the Internet's rapid expansion. The amount of network attention receives can indicate how many people are looking for something. The orderly development of Chinese resort hotels can be guided by research on the spatiotemporal characteristics of their network attention. Using Chinese resort hotels as the study subject, everyday information about resort hotels in 31 Chinese provinces was gathered via the Baidu Index platform between 2018 and 2022, and mathematical statistics and other methods were used to study the spatiotemporal distribution characteristics and influence of Chinese resort hotels network attention. Findings reveal that, from 2018 to 2022, network attention to resort hotels across the country fluctuated significantly across seasons, and there was a "precursor effect" reaction before the week of network attention. Moreover, the spatial distribution of network attention to Chinese resort hotels was uneven, showing an overall trend of "east-central-west" decline. Level of economic development, degree of network development, leisure time, and population size are the main factors affecting the spatiotemporal distribution of Chinese resort hotels network attention.

Spatial and temporal distribution characteristics and geographic contexts of civilized villages in China

Rural civilization is the soul of rural revitalization strategies. As a booster of rural civilization, the civilized village is an indispensable force to promote the modernization of rural areas, in the meanwhile, the study of its spatial distribution has important theoretical significance and practical value in deepening the theory of rural geography, promoting the development of rural civilization, and helping rural revitalization. Considering civilized villages as the study topic, the spatial and temporal distribution characteristics and geographic context were discussed using spatial analysis methods. The number of civilized villages in the country has shown a clear upward trend since 2005. The spatial distribution pattern of civilized villages in China shows unbalanced patterns with a higher concentration in the east and south. Civilized villages in China present significant patterns of clustering with an increasing degree of spatial clustering, showing a multi-core spatial distribution pattern. Civilized villages in China demonstrate clear spatiotemporal clustering characteristics. A spatiotemporal hot spot cluster formed in the northwestern region from 2005 to 2011, and a spatiotemporal cold spot cluster formed in the southeastern region from 2005 to 2008. The spatial distribution of civilized villages in China has obvious geographical differentiation laws, and factors such as topography, climate, economy, transportation, and policy significantly affect their spatial distribution.

Revisiting tourism in the post-pandemic era: An evaluation study of China's 5A-Class scenic spots

The emergence of the COVID-19 in 2019 has unquestionably had a profound and transformative effect on the tourism industry. Following the easing of COVID-19 prevention and control measures in China, there has been a significant increase in travel demand. Representing the epitome of excellence in Chinese scenic spots, 5A-class scenic areas are primary destinations for travelers. The assessment of these scenic spots plays a crucial role in shaping their tourism reputation. Currently, there is a regional focus in research on the evaluation of 5A-class scenic spots exhibits regional characteristics, with limited attention given to a nationwide assessment. In this study, we collected over 410,000 online comments were gathered from 256 scenic spots classified as 5A-class. Employing the Latent Dirichlet Allocation (LDA) topic model, this study conducted a thematic exploration and applied Grounded Theory for qualitative analysis of evaluation themes. This study focused on analyzing scenic spot evaluations by examining three dimensions: the scenic spot itself, the surrounding facilities, and the perspective of tourists. Study findings reveal: (1)Tourist evaluations of 5A-class scenic spots by tourists undergo changes from the inception of the journey to its conclusion. (2)Tourist assessments of these scenic spots are not confined solely to the attractions themselves, the quality of peripheral amenities also has a significant impact on their assessments. This study differentiates itself from traditional regional analysis and perceptual image perspective analysis by employing a process-oriented approach from the perspective of the tourist. The utilization of text-mining techniques enables the identification of coexisting universal and regional tourism evaluation indicators. The present study makes a valuable contribution to the existing body of knowledge by providing insights into the intricate nature of the tourist evaluation process and the interrelationships among different factors.

Spatial Pattern and Influencing Factors of Tourism Resources in Northwestern Ethnic Areas in China-A Case Study of Longde County

With the in-depth development of the Western Development Strategy and Rural Revitalization, the tourism industry has become an important economic sector to drive local development in northwestern minority areas of China. This study established a database of tourism resources in Longde county and analyzed the spatial pattern of these tourism resources by using the scale index and kernel density. From the perspective of the natural and social environment, this paper quantitatively discusses the influencing factors of the spatial pattern of tourism resources in the county based on a multiple linear regression model. The results showed that: (1) There were 2049 tourism resources distributed in Longde County, and building and facility resources were the most prevalent. (2) The hierarchical structure of tourism resources in the county showed a "pyramid" distribution, where excellent tourism resources accounted for 22.60% of the total resources. (3) The spatial pattern showed an agglomeration distribution, and the spatial differences of all kinds of resources were significant. The resources were mainly distributed in Chengguan Town and Wenbao Township. (4) Topographic conditions, convenient transportation, population density and water system distribution were important factors that affected the spatial pattern of tourism resources. It was suggested that the government issue corresponding policies to optimize the spatial pattern of tourism resources; balance the relationship between the exploitation of tourism resources, tourism development and local economy, and the social and ecological environment; and promote the sustainable development of tourism in the northwestern ethnic areas in China.

Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces

In the context of green and high-quality development, effectively enhancing industrial carbon emission efficiency is critical for reducing carbon emissions and achieving sustainable economic growth. This study explored this research area using three models: the super-efficient SBM model was used to measure the industrial carbon emission efficiency of 48 cities in the Pearl River Basin from 2009 to 2017; the exploratory spatiotemporal data analysis method was used to reveal the spatiotemporal interaction characteristics of industrial carbon emission efficiency; and the geographical detectors and geographically weighted regression model were employed to explore the influencing factors. The results are as follows: (1) The Pearl River Basin’s industrial carbon emission efficiency steadily increased from 2009 to 2017, with an average annual growth rate of 0.18 percent, but the industrial carbon emission efficiency of some sites remains low; (2) The local spatiotemporal pattern of industrial carbon emission efficiency is solitary and spatially dependent; (3) The spatial variation of industrial carbon emission efficiency is influenced by a number of factors, including the industrialization level, openness to the outside world, the science and technology level, energy consumption intensity, and productivity level, with the productivity level, industrialization level, and openness to the outside world being the most important. Among these factors, the productivity level, science and technology level, openness to the outside world, and industrialization level all have a positive correlation with industrial carbon emission efficiency, but energy consumption intensity has a negative correlation. This study provides an integrated framework using exploratory spatiotemporal analysis and geographically weighted regression to examine carbon emission efficiency among cities. It can serve as a technical support for carbon reduction policies in cities within the Pearl River Basin, as well as a reference for industrial carbon emission studies of other regions of the world.