Zhaoping Yang

Exploring the spatial patterns and associated mechanisms of Rural Tourism Demonstration Villages (RTDVs) and Potential Rural Tourism Villages (PRTVs) is crucial for rural tourism planning and regional coordination. This study focuses on the arid region of Northwest China. Based on national and provincial official directories, it selects villages listed under tourism-oriented categories as RTDVs, while designating other villages categorized for their ecological, cultural, and agricultural characteristics as PRTVs. Multiple geospatial analyses were conducted to identify spatial distribution characteristics and differences between RTDVs and PRTVs, while the optimal-parameter geographical detector model quantified the influences and interactions of natural, socioeconomic, locational, and cultural–tourism factors. Results show that rural tourism is concentrated in the Ili River Valley, the mid-Hexi Corridor, and the Urumqi–Turpan area. RTDVs follow this pattern but display stronger hierarchical differentiation. Cultural Potential Rural Tourism Villages (C-PRTVs) cluster in multi-ethnic areas. Ecological Potential Rural Tourism Villages (E-PRTVs) occur mainly in mountain oases, and agricultural Potential Rural Tourism Villages (A-PRTVs) agglomerate near provincial capitals and major transport corridors. Overall, influencing factors exhibit interactive enhancement, suggesting that spatial patterns are associated with multidimensional synergy. The findings provide empirical support for differentiated planning and sustainable development in arid regions.

Establishing nature reserves is fundamental to promoting ecological civilization and ensuring the ecological security of sustainable development, as well as a key strategy for maintaining the integrity of the national ecosystem. In recent years, with the enhancement in environmental awareness, the role of nature reserves in maintaining ecosystem stability, protecting biodiversity, and promoting sustainable development has become increasingly prominent. As a crucial ecological defense line in China, studying the spatial distribution and influencing factors of nature reserves in Xinjiang is vital for regional ecological protection and resource management. In this study, we focused on the nature reserves in Xinjiang and used kernel density and standard deviation ellipse analysis methods to examine data from 1980, 1990, 2000, 2010, and 2020 in order to reveal the dynamics of spatial distribution, clustering characteristics, and evolutionary patterns, providing a scientific basis for optimizing the spatial layout of nature reserves in Xinjiang. We also employed a geographical detector model to assess the main influencing factors. This study shows that the number, area, and types of nature reserves in Xinjiang have rapidly increased, forming an integrated system predominantly composed of nature reserves. Their spatial distribution exhibits a northeast–southwest orientation and a ring-centered clustering pattern. This spatial differentiation is the result of the interaction between natural and human factors, manifesting as an enhanced effect among these factors.

Adopting advanced e-commerce practices is essential for enhancing user engagement and business performance, particularly in tourism. This study evaluates the e-commerce adoption of Kazakhstan’s tourism websites using an innovative Integrated Multi-Criteria Decision Analysis (IMCDA) methodology. Traditional evaluation methods overlook the interplay between website functionality, user experience, and strategic objectives. To address this gap, the IMCDA framework integrates qualitative and quantitative approaches by combining advanced Multi-Criteria Decision-Making (MCDM) techniques, including SPOTIS, ESP-COMET, RANCOM, and SITW, with content analysis and logistic regression. The study assessed 77 tourism websites, categorized into Online Travel Agencies (OTAs), Official Tourism Websites (OTWs), and Attraction Websites (AWs), based on 34 e-commerce features grouped into dimensions such as product information, functionality, reservations, payment systems, and customer relationship management (CRM). The findings reveal that OTAs significantly outperform OTWs and AWs in most dimensions, especially in online booking and CRM functionalities. At the same time, AWs lag in key e-commerce features like reservations and payment systems. This research highlights critical gaps in Kazakhstan’s tourism e-commerce ecosystem. It provides actionable recommendations, including enhancing CRM tools, integrating advanced booking systems, and leveraging collaborations with local financial technology providers like Kaspi Pay. The IMCDA framework offers a robust, adaptable evaluation model with practical implications for digital transformation and competitiveness in the tourism industry. This study contributes to advancing digital maturity in Kazakhstan’s tourism sector by addressing these gaps. It sets the foundation for future research to explore innovative strategies in e-commerce adoption across various regions and industries.

Landscape aesthetic quality (LAQ) evaluation is vital in territorial spatial planning. It helps to achieve the rational development and protection of territorial space and ensures the harmonious coexistence of developments and the ecological environment. Based on mapping and quantification, this paper took LAQ evaluation as the object, established a methodological framework for large-scale natural LAQ evaluation, excavated and identified key areas with outstanding landscape aesthetics service supply capabilities, and supported regional landscape planning and protection management. This paper took the Hengduan Mountains in China as an example to evaluate and identify the spatial distribution of the LAQ in mountainous areas. The results showed that the high-value LAQ areas are located east and south of the Hengduan Mountains, where high-quality natural landscapes are concentrated and have significant potential for establishing national parks. The evaluation results of the LAQ can provide a good reference for the spatial identification of future national parks in the Hengduan Mountains. Moreover, our research can provide a scientific basis for large-scale landscape spatial planning and decision-making for the classified protection and rational utilization of landscape resources and other mountain ecosystems.

This study, leveraging search engine data, investigates the dynamics of China's domestic tourism markets in response to the August 2022 epidemic outbreak in Xinjiang. It focuses on understanding the reaction mechanisms of tourist-origin markets during destination crises in the post-pandemic phase. Notably, the research identifies a continuous rise in the potential tourism demand from tourist origin cities, despite the challenges posed by the epidemic. Further analysis uncovers a regional disparity in the growth of tourism demand, primarily influenced by the economic stratification of origin markets. Additionally, the study examines key tourism attractions such as Duku Road, highlighting its resilient competitive system, which consists of distinctive tourism experiences, economically robust tourist origins, diverse tourist markets, and spatial pattern stability driven by economic factors in source cities, illustrating an adaptive response to external challenges such as crises. The findings provide new insights into the dynamics of tourism demand, offering a foundation for developing strategies to bolster destination resilience and competitiveness in times of health crises.

Introduction and aim: Ensuring the protection and restoration of forest ecosystems is vital to maintaining and restoring ecological balance in deforested or degraded landscapes. However, sustainable development faces challenges from high human impacts on natural forest ecosystems, insufficient advanced conservation measures, and limited engagement of local communities in developing nations. The aim of this study was to explore the utility of spatial remote sensing datasets in examining the landscape pattern changes within the transboundary Nyungwe-Kibira Forest from 2000 to 2019. This aimed to emphasize the necessity of understanding the intricate dynamics of this ecosystem and its susceptibility to human activities in order to bolster diverse restoration initiatives throughout the region.Methods: The landscape pattern change in the Nyungwe-Kibira between 2000 and 2019 was analysed using high-resolution Landsat data. This analysis encompassed an evaluation of the dynamics of changes in built-up, cropland, and forest areas within the region. Especially, primary data derived from the Landsat dataset and secondary data from reports such as the Outlook Report were employed to elucidate the ongoing landscape transformation within and surrounding the transboundary forest.Results and discussion: The analysis revealed a net change of +62.3% and +18.07% in built-up and cropland areas, resulting in a gross change of 14,133 ha and 6,322 ha in built-up and cropland areas, respectively. Furthermore, the forest experienced an overall gain of 9.11%, corresponding to a net loss of 6.92% due to deforestation, estimated at -14,764 ha. The analysis also indicated that built-up areas accounted for approximately 33.02% of the net forest loss, primarily affecting the northern edge of the Rwanda region, while cropland expansion contributed to a net loss of forest (-9.48%), predominantly impacting the southeast portion of the forest in Burundi. Additionally, the forest is predicted to decrease by 0.74% by 2030, with current findings showing aggregated forest and cropland at 66% and 7%, dissected rangeland at 24%, and created built-up areas at 3%. The findings indicate that the Nyungwe-Kibira Forest is undergoing notable transformations, highlighting the necessity of land-based projects and mitigation plans to facilitate the restoration of the forest from its historical changes. Without proactive measures, an ongoing decrease in forest area by 2030 is anticipated.

In Kibira National Park, Burundi, socioeconomic and demographic factors lead to environmental performance challenges that impede biodiversity; thus, understanding the impact of these determinants on land use and land cover change is important to address these challenges. In this study, a multivariate analysis of variance (MANOVA) model was used to quantify the impact of socioeconomic and demographic factors on land cover/land use (LCLU) changes using Landsat images captured between 1990 and 2021. In addition, the impact of the environmental performance index (EPI), particularly ecosystem vitality (ECO), on landscape fragmentation was examined using a Spearman correlation analysis. A Pearson correlation analysis and a principal component analysis (PCA) were used to investigate the connections between the indicators of relevance in this study. The results reveal a decrease in forestland from 86.1% to 81.32%, a decrease in water bodies from 0.352% to 0.178%, and a decrease in open land from 2.124% to 1.134%, whereas grassland increased from 11.43% to 17.37% between 1990 and 2021. The landscape fragmentation in the edge density, contagion (CONTAG), largest patch index (LPI), number of patches (NP), and patch density (PD) was reduced in 2011 but increased again from 2016 to 2021, when only the ED fragmentation continued to decrease. The MANOVA results show that the rural population had a significant impact on LCLU changes at the 5% level of significance. Demographic factors significantly contributed to changes in grassland and forestland at a probability of 5%. In addition, moderately significant connections were observed between population growth per year and water and between gross domestic product (GDP) and grassland at the 10% level. ECO issues in ecosystem services (ECSs) were statistically significant for the increased fragmentation metrics, while biodiversity and habitat (BDH) were important for reducing the edge density (ED) at a 5% level of significance. The Pearson correlations showed a substantial positive relationship between the socioeconomic and demographic components, whereas a negative connection was found between the forestland and BDH indicators. These findings are essential for understanding the significant drivers of LCLU changes and the influence of environmental performance on the landscape pattern.

Xinjiang is one of the world’s most sensitive and vulnerable regions to climate change. However, little is known about the current status and changes in thermal comfort conditions in this area. Using the Universal Thermal Climate Index (UTCI) derived from the newly available high-resolution dataset HiTiSEA, the spatial–temporal pattern and changes thereof over annual and seasonal scales across Xinjiang from 1981 to 2019 were evaluated. The results reveal that the distribution and change of thermal comfort in Xinjiang have apparent regional heterogeneity and seasonal characteristics. Across all scales, 7 of 10 UTCI thermal stress categories were observed, from slight cold stress to strong heat stress. Annually, the mean UTCI is 3 °C and has significantly increased at 0.37 °C decade⁻¹. The mean number of comfortable days (CDs) is 114 days, with a range from 0 to 189 days. On the space scale, the Tarim Basin experiences the highest UTCI value, while the Ili River Valley, the north side of the Tianshan Mountains, and the peripheral areas of the Tarim Basin have a higher number of CDs. Seasonally, summer has the highest UTCI value, while winter is the lowest. The trend for all seasons is upward, and spring increases fastest. Results also indicate that air temperature has a positive correlation with climate comfort, and the influence of air temperature on climate comfort is most significant. Further research indicates that the range and intensity of population exposure to uncomfortable climates in Xinjiang have increased. The distribution and expansion of population exposure are similar to the population density. These findings contribute to a systematic understanding of the local climate environment and can be helpful for the assessment of the impact of climate change and optimize tourism development.

Geodiversity is considered a new tool to exploit the resources of regional and local geotourism. Hitherto, few assessments of geodiversity have been conceived for huge geographic units. The spatial pattern of geodiversity in the Tibetan Plateau (TP) is the purpose of this study. A total of 96 abiotic units in six geo-groups of hydrology, pedology, landform, elevation, geology, and geosites were quantified and normalized to assess the geodiversity index. Geosites that represent interdisciplinary and specific abiotic elements are included as an independent component in the parameters of geodiversity assessment. The TP was divided into 1145 areas by fishnet, for counting of abiotic units, geodiversity calculation, and visualization of findings. The results indicated that the Pamir Plateau, Mt. Kunlun, the Delingha area, Mt. Qilian, the Xining area, Langmusi Town, Mt. Siguniang, Mt. Hengduan, the Nyainqentanglha Range, and the Lhasa area are the zones with very high geodiversity. The low geodiversity areas are mainly concentrated in the Qaidam Basin, the Qingnan Plateau, and the South Tibet region. In the TP, international tourist destinations such as UNESCO World Natural Heritage Sites and Global Geoparks, are developed in areas of high geodiversity. The spatial pattern of geodiversity could be indicative of geotourism potential, and be used to guide the development planning of geotourism in the TP. The quantitative assessment of geodiversity also provides a new parameter for geoconservation in China.