Chen Xiao-Ping, Deng Ya-Yu, He Jin-Yu, Han Meng, Liu Yan-Hong, Wu Xiao-Gang, Zhen Zhi-Lei
College of Urban and Rural Construction, Shanxi Agricultural University, Jinzhong 030801, Shanxi, China.
College of Forestry, Shanxi Agricultural University, Jinzhong 030801, Shanxi, China.
Ying Yong Sheng Tai Xue Bao. 2023 Oct;34(10):2739-2746. doi: 10.13287/j.1001-9332.202310.019.
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.
基于供需评价的统筹协调，识别服务盲区、科学选择公园建设区域并明确公园建设优先级具有重要的现实意义。以太原环城高速公路范围内的城市公园为研究对象，利用高德地图路线规划应用程序接口和兴趣点数据来表征各公园的供需水平，估算每个公园的可达范围和服务压力。通过叠加分析识别公园的服务盲区，并利用定位分配（LA）模型有针对性地供给公园绿地。结果表明，公园在15分钟内步行和骑行的可达覆盖率分别为35.6%和71.7%，表明公园供给能力不足。太原对公园绿地潜在需求大的区域主要集中在亲贤—长风街商业区和东中环内的双塔商业区，存在明显的隐形盲区。最后，基于LA模型提出了新的公园绿地选址方案。优化结果表明，15分钟内步行和骑行的覆盖率分别提高到46.7%和81.0%，公园的服务压力得到缓解。利用网络大数据将城市居民的休闲需求与城市公园的分布相结合，能够提高优化选址的科学性和准确性，为城市公园建设提供科学的方法和理论依据。
