A demand index for recreational ecosystem services associated with urban parks in Beijing, China.

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.