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

机译:中国北京城市公园休闲生态系统服务需求指数

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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.
机译:要对城市公园进行良好的规划,就需要分析城市人口分布与休闲生态系统服务(RES)需求之间的定量关系。 RES量化的一个障碍是调查资料和空间数据之间缺乏联系。这项研究基于个人游客的特征和他们对公园的访问意愿,为与城市公园相关的RES需求建立了Logistic回归模型。该模型通过对4096位公园游客的问卷调查进行拟合,并用于预测北京317个街道对RES的需求。结果表明:(1)公园游客认为观光是最重要的,其次是在北京公园的慢跑,划船,聚会,骑自行车和钓鱼; (2)高收入和年长的居民比低收入和年轻的公园游客有更高的公园参观意愿; (3)城乡边缘地区对可再生能源的需求指数较低。这项研究展示了一种基于调查和统计数据来预测RES需求的可行方法。我们的研究表明,改善公园规划需要开发多样化的娱乐基础设施,在不同利益相关者之间进行权衡,并为可持续城市发展进行空间优化。结果提供了一种潜在工具,可用于评估城市化和人口增长情况下的RES平衡。

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