Assessing landscape ecological risk (LER) is vital for sustainability in ecologically fragile regions. However, LER in cultural heritage sites remains insufficiently explored. Using Guyi Basin as a case study, this study analyzes LER dynamics under land-use change and its driving factors. The PLUS model was applied to simulate land-use changes from 1990 to 2060 under three scenarios, while GeoDetector was used to identify key drivers of LER. Results show a marked expansion of construction land in urban areas and traditional villages and a continuous decline of cultivated land. LER exhibits an “internally high–externally low” pattern characterized by “high–high” and “low–low” clusters. The ecological protection scenario presents a significantly lower risk Interactions such as DEM∩population density exerted the strongest combined effect on LER, with natural factors showing greater influence than social factors. This study provides methodological insights and practical implications for LER management and sustainable development in cultural heritage sites.

China stands out as one of the countries with the largest and fastest-growing elderly populations. Elderly requirements for the quality of high-speed railway stations environment are increasing. The relationship between the built environment of high-speed railway stations and elderly health has become an urgent problem to be solved. The challenge necessitates a systematic approach to age-friendly design. Based on the practical experience of the authors in an age-friendly design of an indoor environment at Nanjing South Railway Station, questionnaire surveys and user interviews were employed to profile four types of typical elderly passengers. Data collection methods were used to create behavior maps. (1) This study identifies the age-friendly needs of elderly passengers, pinpointing the key environment issues. (2) It proposes age-friendly design strategies for various functional areas of Nanjing South Railway Station. (3) It introduces an age-friendly module combination design system, which including basic type I, enhanced type II, and optimized type III, in order to meet the demands for six levels of high-speed railway stations in China. This study promotes the age-friendly transformation of environments at a high-speed railway station, offering theoretical foundations and methodological references for constructing an age-friendly environment from a healthy ageing perspective.

Museum architecture is essential for preserving cultural heritage. Understanding the spatio-temporal evolution of visitor preferences, image perceptions, and driving factors is vital for promoting cultural development. However, traditional methods such as questionnaires and interviews face challenges in elucidating how exhibition layouts, environmental facilities, and service quality affect visitor experience and satisfaction. In this study, 30 museums in 6 categories were selected as samples, and over 64,000 public online reviews from Dianping and Ctrip were selected as data sets. Kernel density and standard deviational ellipse methods revealed the spatio-temporal evolution of museum space preferences (2016–2024). TF-IDF and LDA algorithms identified key image perception themes. Visitor satisfaction was then evaluated with SnowNLP sentiment analysis to examine the dynamic correlation between the perception themes and satisfaction. The findings showed: 1) Museum visitors were highly concentrated in eastern coastal regions, with spatial distribution evolving from single-core to multi-core clusters, gradually expanding into central areas (e.g., Henan, Hubei, Shaanxi). 2) Museum image perception has shifted from object-centered to more human-centered experiences, with significant differences across the various categories. 3) Over 75% of visitors reported positive experiences, with ethnography museums showing the highest satisfaction in 2024 (Pro = 0.922), whereas history museums consistently had the lowest. 4) Satisfaction drivers were dynamic, with 85.26% of perception themes significantly correlated with satisfaction (p < 0.01), with rich collections, distinctive features, immersive experiences, and diverse visitation forms identified as the primary contributors to positive visitor experiences. Based on the comprehensive perspective of typology and spatio-temporal dynamic evolution, this study not only provides empirical support for museum space optimization, but also provides new ideas and strategies for functional research and methodological insights of public spaces.

Constructing ecological networks in urban areas improves ecosystem stability and biodiversity protection. However, most studies focus on optimizing ecological environments through objective assessments, often neglecting species diversity. This study developed a biodiversity grading framework for the Jianghan Plain using species observation and ecosystem diversity data. Supported by ArcGIS, ecological sources were identified via MSPA and graded using the Guidelines and MaxEnt model. The MCR model was used to simulate connectivity barriers between ecological sources and calculate the minimum cumulative resistance distance, thereby generating corridors and ultimately constructing a hierarchical biodiversity conservation network for the Jianghan Plain. Our findings indicated the following: (1) The Jianghan Plain hosts 21 major ecological sources, primarily natural water bodies at the plain’s edge, which can be classified into five primary and 16 secondary sources based on biodiversity grades. (2) The recessive corridors, comprising 10 primary and 95 secondary ones, are mainly concentrated in the central Jianghan Plain, with primary corridors located centrally and westward, characterized by a large overall span. (3) Changhu Lake and Honghu Lake, two critical water bodies with high-quality habitats and significant biodiversity, were identified as key ecological nodes from the ecological sources, bridging and guiding the central and southern corridors. (4) Based on the ecological network distribution and key nodes and corridors, a “three zones, three belts, and two points” strategy was proposed for optimizing the Jianghan Plain’s ecological network. This study provides a novel framework and theoretical support for regional habitat, biodiversity conservation, and sustainable development.

Air pollution, particularly fine particulate matter (PM_2.5), poses a significant health risk, especially in high-density urban areas. Urban green space (UGS) can effectively mitigate this pollution. Despite their potential, strategies for effectively leveraging Land Use/Land Cover (LULC) optimization to combat PM_2.5 remain largely unexplored. Ordinary least squares (OLS), geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) were employed to investigate the spatial heterogeneity relationship between UGS conversion and PM_2.5 fluctuations across various scales and evolutionary stages, developing a multiscale practical framework for LULC synergy in combating air pollution. The areas of UGSs to/from other LULCs, PM_2.5 concentrations and corresponding variation zones exhibited significant spatial clustering. These UGS conversions explained more than 65% of the PM_2.5 changes in the study area, peaking at 76.4% explanatory power in the fourth stage. Compared to global spatial analysis (OLS: 0–0.48), local spatial regression analysis significantly improved the R² value (GWR: 0.32–0.75, MGWR: 0.48–0.90), but the fitting quality of local spatial regression analysis decreased with increasing scale, highlighting the importance of scale diagnosis. A 2 km scale was identified as optimal for assessing the spatial heterogeneity impact of UGS and other LULC conversions on PM_2.5 changes. Conversion areas from water bodies and bare land to UGSs maintain stable local spatial properties at this scale (bandwidths: 44–99). Our research provides new insights into LULC management and planning, offering a coordinated approach to mitigating urban air pollution. Additionally, a practical framework was established for addressing spatially continuous variables such as PM_2.5, revealing effective approaches for addressing urban environmental issues.