Abstract

It is of great practical significance to identify service blind area, scientifically select park construction areas, and clarify the priority of parks' construction based on the co-ordination of supply-demand evaluation. With the urban parks within the Taiyuan Ring Expressway as the research subjects, we estimated the accessibility range and the service pressure of each park by using the application programming interface of Gaode map route planning and point of interest data to characterize their supply and demand levels. We identified the service blind areas of parks by overlay analysis, and used the location-allocation (LA) model to purposefully supply park green space. Results showed that the accessibility coverage rates of the parks by walking and bicycling within 15 minutes were 35.6% and 71.7%, respectively, indicating insufficient supply capacity of parks. The areas with large potential demand for park green space in Taiyuan were mainly concentrated in the business district of Qinxian-Changfeng Street and the Shuangta business district within Dongzhong ring road, which existed the obviously invisible blind areas. Finally, we proposed new park green space site selection proposal based on LA model. Optimization results indicated that the coverage rates of walking and bicycling within 15 minutes increased to 46.7% and 81.0%, respectively, and that the service pressure of parks was relieved. We combined the leisure demands of urban residents and the distribution of urban parks by utilizing network big data, which could promote the scientific nature and accuracy of the optimizing site selection and provide scientific method and theory basis for urban park construction.

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