Urban green spaces are vital for older people’s health. However, most studies have only focused on their relationship with single-dimensional health outcomes. This study introduced a theoretical model to explore how perceptions of green spaces influence older people’s multidimensional health, mediated by the use of these spaces. Using a literature review, interviews, and surveys, we developed and refined a measurement scale for older people’s perceptions of urban greenery. Using data from 513 seniors in Fuzhou’s urban parks, structural equation modeling was used to examine the relationships between their multidimensional health, usage, and perceptions of green spaces. The results showed that older people’s positive evaluations of green spaces, especially those with facilities, significantly increased their usage. This increased usage positively influences their physical, mental, and social health, with the most pronounced benefits for social health. The total impact of green space perception on multidimensional health was beneficial and significantly impacted social health, even though the direct impacts of quality perception on physical health and facility perception on social health were minimal. These findings enhance our understanding of the impact of green spaces on the health of older individuals and provide a theoretical basis for developing urban green spaces that maximize health advantages for older people.

The assessment of habitat quality is instrumental in preserving regional species diversity and ecosystem health, thereby forming the theoretical foundation for sustainable urban development. While the Invest model is a commonly employed tool for habitat quality evaluation, it fails to consider the terrain. This study, centered on Haitan Island, introduces the terrain diversity index to rectify the Invest model’s lack of terrain evaluation. The terrain diversity index, encompassing indices for terrain slope, undulation, and humidity, combined with the Invest model, was applied for a comprehensive assessment of the study area’s habitat quality. Furthermore, the distribution characteristics of habitat quality on Haitan Island, China, were examined using Moran’s I and LISA indices. The research indicates that forest land is the primary land cover type on Haitan Island, with blue-green space comprising forests, farmland, water bodies, and grassland, making up 66.8% of the island’s area, thus implying a positive overall ecological base. Habitat quality distribution within the study area displays spatial heterogeneity, with regions of superior habitat quality primarily found in the northeast areas such as Junshan. Compared to the standalone Invest model, the combined method considering terrain and vegetation cover types yields a more sensitive impact on habitat quality evaluation and improves the precision of identifying superior habitat quality by 56.7%. Spatial autocorrelation analysis revealed that the comprehensive habitat quality index in the study area exhibited clustered distribution. Hotspots were mainly identified in areas like Junshan and the western mangrove wetland, regions with a high concentration of habitat quality values, while low-value clusters were mostly found in the central city and southwestern plains. This study offers a novel methodology for habitat quality evaluation, compensating for the traditional Invest model’s neglect of terrain factors, and enriching the research on island habitat quality. It can provide fresh approaches and references for future habitat-related studies.

Understanding how people perceive landscapes is essential for the design of forest landscapes. The study investigates how design intensity affects landscape complexity, preference, and eye movements for urban forest settings. Eight groups of twenty-four pictures, representing lawn, path, and waterscape settings in urban forests, with each type of setting having two groups of pictures and one group having four pictures, were selected. The four pictures in each group were classified into slight, low, medium, and high design intensities. A total of 76 students were randomly assigned to observe one group of pictures within each type of landscape with an eye-tracking apparatus and give ratings of complexity and preference. The results indicate that design intensity was positively associated with subjective landscape complexity but was positively or negatively related to objective landscape complexity in three types of settings. Subjective landscape complexity was found to significantly contribute to visual preference across landscape types, while objective landscape complexity did not contribute to preference. In addition, the marginal effect of medium design intensity on preference was greater than that of low and high design intensity in most cases. Moreover, although some eye movement metrics were significantly related to preference in lawn settings, none were found to be indicative predictors for preference. The findings enrich research in visual preference and assist landscape designers during the design process to effectively arrange landscape design intensity in urban forests.

Individuals’ preferences for urban forest scenes are an essential factor in the design process. This study explores the connection between landscape design intensity, visual preferences, and eye fixations in urban forest scenes. Five pictures representing different urban forest scenes (plaza, lawn, garden path, pond, and rockery) were selected as stimuli, representing the original landscape design intensity. Three additional levels of design intensity (low, moderate, and high) were created by modifying the landscape elements of the original picture. A group of 50 participants was randomly assigned to observe the four levels of design intensity pictures within each type of landscape using eye-tracking technology. They also rated their preferences for each scene. In total, 250 participants took part in the study, with five groups observing five types of urban forest scenes. The results indicate that landscape design intensity has a positive impact on visual preferences, with moderate design intensity showing the strongest effect. However, the influence of design intensity and preferences also depends on the specific landscape scene. The fixation data did not show a significant relationship with design intensity but were associated with the type of landscape scene. In conclusion, this study suggests that moderate design intensity is recommended for urban forest design. However, it also highlights the importance of considering the specific landscape scene type. The research provides valuable insights into urban forest design and contributes to the understanding of eye-tracking technology in landscape perception studies.

Green infrastructure networks enhance the protection and improvement of urban ecological environments, augment the efficiency and quality of ecosystem services, and furnish residents with healthier and more comfortable living conditions. Although previous research has investigated the construction or optimization methods of green infrastructure networks, these studies have been relatively isolated and lacking in case studies for mountainous cities. In the development of green infrastructure, mountainous cities must specifically consider the impact of terrain on network construction. Taking Fuzhou, a mountainous city in China, as an example, this study constructs and optimizes the green infrastructure network by employing morphological spatial pattern analysis, connectivity analysis, the Minimum Cumulative Resistance model, and circuit theory. These methodologies increase the connectivity of the Green Infrastructure within the study area, thereby promoting the health of the local ecosystem and creating conducive circumstances for the city’s sustainable development. The findings reveal that: (1) Green infrastructure in Fuzhou takes up 5366.38 ha, constituting 21.76% of the study area, primarily situated in the northwest and south; (2) Fuzhou’s Green Infrastructure network comprises 10 hubs and 17 corridors with a hub area of 1306.98 ha, predominantly distributed in the mountains encircling the city, including Meifeng Mountain, Gaogai Mountain, and Qingliang Mountain; (3) Based on optimization, the circuit centrality index categorizes hub importance into three protection levels, pinpointing nine crucial protected areas in the corridors and 680 areas requiring enhancement, including 68 areas for first-level improvement, 149 areas for second-level improvement, and 463 areas for third-level improvement. This research offers a methodological reference for constructing and optimizing green infrastructure networks in mountainous cities, providing both theoretical and practical foundations for optimizing green infrastructure networks in Fuzhou City.