Landscape preference and cognition are essential in determining the external environment’s subjective reflections. Although much research has been conducted on landscape preferences, there is still a lack of information on landscape perceptions and preferences among residents of disadvantaged neighbourhoods, especially in Chinese cities. Taking old residential neighbourhoods of Shijiazhuang as an example, this paper used a large-scale questionnaire survey and semi-structured interviews to determine the landscape preference of the residents of old residential neighbourhoods for the community green spaces using the virtual model method. The chi-square test method is used to explore the inner logic of aesthetic preference from two aspects: landscape characteristics and socio-demographic characteristics. The respondents are 668 residents of old residential neighbourhoods (300 males, 368 females) distributed in four larger communities in the main urban area of Shijiazhuang. Random sampling and volunteer sampling were used to choose the survey respondents. The results showed this: (1) In terms of soft landscapes, respondents prefer natural planting, spaces with very high plant richness and high green coverage. In terms of hard landscapes, there is a preference for fitness and leisure facilities, rubber floors and a slight preference for water features and decorative landscape elements. (2) From the chi-square results, age significantly affects landscape preference, gender and education level. In contrast, marital status and occupation have no significant effect on landscape preference. The expression of the landscape preference of the residents of old residential neighbourhoods reflects the needs for functionality, reality and local concept. The main aim of this study is to fully understand the landscape preferences of residents in old residential neighbourhoods when using green space, and to find out what factors will affect residents’ landscape preferences. The research results have guiding significance for rationally improving the landscape planning, design and management of old residential neighbourhoods, and at the same time make up for the lack of international research on landscape preferences of disadvantaged communities. Improving the environment of old residential neighbourhoods can develop a higher sense of security, happiness and satisfaction among the residents.
Studies have shown that disadvantaged neighborhoods have fewer green spaces, resources, and facilities, resulting in residents facing more barriers to using green spaces. This study aims to quantify green space usage patterns and constraints in old residential neighborhoods in a large city in northern China. A questionnaire survey and semi-structured interviews were conducted with 668 residents. Results showed that most residents visited their local green spaces daily, often in the evenings, and spent between 30 and 60 min there. The number of visits on weekends is higher than on weekdays, with no difference in visiting alone or in groups. The main reason for visiting green spaces was to relax and enjoy nature, followed by spending time with family. Limitations to usage included poor physical environments, such as inadequate facilities, lack of maintenance, overcrowding, poor accessibility, limited activities, and pet restrictions. This study provides insights into the current state of green space utilization in old residential neighborhoods, as well as a discussion of the limitations, which could inform future renovations and designs of green spaces in these areas.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.