Urban community parks are closely related to the health of residents, and have a positive effect on residents’ perception of nature, alleviating anxiety, and promoting physical health. Many previous studies have examined the impact of community parks on the health of the population, but few studies have investigated the potential of specific landscape elements in community parks to restore physical health. We conducted psychological questionnaires with 440 users of community parks in Shanghai through on-site surveys. Based on the psychological questionnaire, a structural equation model of the relationship between the community park landscape environment and users’ feelings was established. The model indicated that the natural environment, activity environment, and rest environment in the community park had positive effects on the physical, mental, and social health of users. At the same time, we recruited 50 participants to conduct laboratory experiments examining physiological changes while participants viewed different types of scene photographs showing the same landscape element. By measuring physiological indicators, including skin conductivity and heart rate, we sought to identify the types of landscape elements that help relieve the stress of users. The results revealed that flower clusters and waterscapes in the natural environment landscape, plastic fitness trails and fitness equipment places in the sports area, landscape elements such as benches with backrests, Chinese style pavilions, and green corridors with plants in the rest space, played positive roles in alleviating feelings of pressure and promoting relaxation among community park users. Based on these findings, we propose specific design strategies to improve the landscape health of community parks.

Ecosystem cultural services (CESs) are crucial for rural revitalization and sustainable development. As research on monitoring and mapping CESs continues to increase, there is a relative lack of research perspectives that effectively combine spatial modeling techniques with the local context of CESs in rural areas. Rural areas in China face challenges such as the encroachment of ecological service spaces and the displacement and relocation of their own cultural characteristics during the urbanization process. It is crucial to enhance our understanding of the relationship between CES characterization and rural locality. This paper established a framework for the quantitative research and spatial optimization of local CESs in rural areas. We selected the Ecological Green Integrated Development Demonstration Zone (EGIDZ) in the Yangtze River Delta as the research subject, considering its representativeness of the Jiangnan Water Network Area and the characteristics of integrated ecological development across regions. The Maxent model was utilized to integrate environmental variables with the locations of services, facilitating spatial mapping and quantitative evaluation of CESs, as well as determining the influence of each variable. Additionally, K-means clustering was employed to analyze CES combination patterns. The results indicated significant variations in mean values and spatial distribution within each CES category. The natural environment, spatial distance, and human activities factors all exhibited significant effects on shaping local CESs. Furthermore, the CES clusters were classified into three categories: CES-developed cluster, CES-developing cluster, and CES-potential cluster, accounting for 9.34%, 49.23%, and 41.44%, respectively. Based on these comprehensive findings, we provided insights into optimizing local CESs in the Jiangnan Water Network rural areas.

Commercialization often leads to a loss of authenticity in historic districts. While most research focuses on fixed spatial or psychological elements, few examine the cognitive processes that shape how people perceive landscape locality. This study uses dual-process theory to explore how intuitive (System 1) and analytical (System 2) thinking influence such perceptions. Results show that intuitive responses dominate in historic districts, whereas analytical reasoning compensates for the perceived inauthenticity of imitation sites. Sociocultural background exerts a stronger influence than demographic traits among individual-level factors. Analytical identification is best predicted by street spatial proportions, while vegetation density supports intuitive recognition through biophilic responses. By viewing landscape locality as a cognitive process rather than a fixed attribute, this study offers new insights into cultural heritage planning. Integrating psychological theory with urban design may help balance preservation and commercialization, supporting both the UNESCO bid for Jiangnan water towns and broader heritage policy worldwide.