Qingyuan Yang

The social-ecological resilience of rural settlements refers to their ability to resist and mitigate the risks posed by internal and external disturbances, and to utilize the external environment to achieve a new equilibrium state. Amid rapid urbanization, it is of great significance for mountainous settlements to improve their risk resistance and development ability. Taking Dong’an Town in Chengkou County, located in the eastern part of Qinling–Bashan Mountains in southwestern China, as the research object, this study constructs an evaluation index system for rural residential resilience based on social-ecological resilience theory. It explores the resilience level of rural residences in mountainous areas from the dimensions of internal resilience and external environmental resilience and scientifically proposes an optimization path for the spatial layout of rural residences. This study provides a reference for optimizing the rural living environment, promoting spatial equity, and improving people’s livelihood according to local conditions. The results showed that: (1) The overall level of security resilience of rural settlements in Dong’an Town was relatively high, with 221 patches above the security level, accounting for 19.53% of the total area of the town. (2) The rural residents in Dong’an Town can be categorized into three types: core structure optimization, peripheral system upgrading, and relocation and withdrawal. Different types of rural settlements adapt to internal and external resource conditions and select optimal spatial layout paths according to local conditions.

The study investigates the intricate relationships between ICT and urbanization through the application of spatial panel data models. The analysis is based on data collected from 31 provincial cities in China over the period from 2012 to 2021. The emergence, diffusion, and influence of ICT exert dynamic and varied impacts on demographic, spatial, and economic aspects of urbanization. For estimation, a Spatial Durbin Model (SDM) is employed. The findings from the SDM indicate that ICT has both positive and negative effects on urbanization. Not all regions can swiftly reap the benefits of ICT, leading to an exacerbation of the digital divide and uneven development across regions. Nevertheless, less developed areas are actively seeking strategies to bridge the existing gap and leverage the advantages offered by ICT. Furthermore, the study reveals that the impacts of ICT on economic urbanization is significant. Key ICT indicators related to the ICT environment, application level, and achievement are crucial in driving urbanization development. The study serves as a valuable reference for policymakers assessing the multifaceted impacts of ICT on urbanization and formulating appropriate policies to enhance the positive effects of ICT.

An understanding of the evolution process of human habitats and their correlation with geographical elements, as well as an exploration of the evolution mechanism of habitats in arid zones, is essential for examining the interactions between habitat sustainability and the geographical environment comprehensively. The polycentric governance theory and synergy theory form the basis of this study, which proposes a polycentric synergistic development model and constructs an evaluation index system for the quality of the human habitat environment in Xinjiang in terms of social services and security, comprehensive economic level, ecological, livable environment and population and cultural environment. The TOPSIS model is utilised to assess the integrated valuation of the quality of the human environment, facilitating analysis of the spatial and temporal trends and spatial correlations of the quality of the human environment. The geodetector model is also employed to identify the influencing factors of the habitat environment. From the perspective of sustainable development, the interconnections and synergistic development processes within the habitat system were elucidated, as well as how the various elements interacted with each other in shaping the habitat system from multiple perspectives. Furthermore, the cumulative effects of the influencing factors on the human settlement environment in arid zones were further verified through the interaction of multiple factors. Furthermore, it verifies the cumulative effect of the influencing factors on the arid environment through the interaction of multiple factors. This study provides theoretical support and empirical evidence for the study of the global arid zone habitat environment, and provides a reference for decision-making on sustainable development paths in specific geographical conditions.

随着数字技术的不断发展及其在乡村生产生活中的应用，“数字乡村”已成为地理学研究的热点之一。论文在对数字乡村的文献成果进行总结分析的基础上提出了数字乡村的定义和内涵，对国内外的研究前沿进行述评，并从知识生产的角度进行对比。梳理发现：① 国内以规范研究为主，着眼解决乡村发展的现实问题，促进政策优化。将数字乡村建设作为推动乡村高质量发展的手段，研究关注点集中在如何利用数字乡村建设助力乡村振兴以及数字乡村发展引致的乡村重构等方面。② 国外以经验研究为主，更倾向解释微观社会现象。通过探讨城乡之间的“数字鸿沟”等具体现象，展现数字化在乡村转型发展过程中的不同面向，着重探讨城乡“数字鸿沟”的形成及其对城乡协调发展的影响。未来中国地理学视角下数字乡村的研究可进一步关注以下方面：人地关系视角下数字乡村概念的再认知、多空间尺度视角下城乡“数字鸿沟”的量化测度、微观主体视角下的数字乡村发展以及基于地理学综合效应研究范式的“数字乡村建设”正负外部性揭示。

By leveraging a multiscale geographically weighted regression (MGWR) model, this paper delves into the intricate factors that influence housing prices in the prototypical mountainous cityscape of Chongqing’s central urban area. The key findings are as follows: Firstly, the distribution of housing prices in the study region exhibits pronounced spatial heterogeneity, with the core area exhibiting a distinct “high-high” clustering pattern and manifesting characteristics of a multicenter group distribution. Secondly, the MGWR model effectively assigns an individual bandwidth to each feature quantity, allowing for a more nuanced portrayal of the varying influence scales exerted by diverse variables. Lastly, the study reveals that factors such as property cost, greening rate, building age, and proximity to rivers have a notable negative impact on housing prices, whereas, educational facilities exert a marked positive influence. Elevation, floor area ratio, and distance from the Central Business District (CBD) exhibit a more complex influence on housing prices.