A demand index for recreational ecosystem services associated with urban parks in Beijing, China. (1st December 2019)

• Record Type: Journal Article
• Authors: Sun, Ranhao; Li, Fen; Chen, Liding
• Is Part Of: Journal of environmental management. Volume 251(2019)
• Publication Date: 2019-12-01
• Subjects: Urban park -- Ecosystem service -- Landscape planning -- Recreation -- Urbanization -- Beijing; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2019.109612
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Good planning for urban parks requires an analysis of the quantitative relationship between the distribution of an urban population and the demand for recreational ecosystem services (RES). A barrier to RES quantification is the lack of connections between survey materials and spatial data. This study developed a logistic regression model for the demand for RES associated with urban parks based on the characteristics of individual visitor and their willingness to visit parks. The model was fitted by a questionnaire survey completed by 4096 park visitors and was used to predict the RES demand in 317 sub-districts of Beijing. Results showed that: (1) park visitors rated sightseeing as the most important, followed by jogging, boating, partying, cycling, and fishing in Beijing's parks; (2) high-income and older residents had higher willingness to visit the parks than did low-income and younger park visitors; (3) the fringe areas between the urban and rural regions showed a relatively low demand index for RES. This study exhibits a feasible method to predict RES demand based on surveys and statistical data. Our research suggests that improving park planning necessitates developing a diverse recreational infrastructure, a tradeoff among different stakeholders, and spatial optimization for sustainable urban development. The results provide a potential tool that can be used to assess the balance of RES in a scenario of urbanization and population growth. Highlights: 4096 park visitors were investigated on the demand for recreational ecosystem services (RES). Logistic regression model for RES demand was developed based on individual characteristics. High-income and older residents have higher willingness to visit the parks. Mapping of RES demand was based on demographic data in 317 sub-districts.