基于地理空间分析的城镇绿地空间供需评价和布局优化

Geospatial analysis-based research on the evaluation of spatial supply and demand and layout optimization of urban green space

基于地理空间模型,采用改进两步移动搜索法对包头市达茂旗百灵庙镇城镇绿地空间进行供需评价。在此基础上,借助K-均值聚类算法和粒子群优化算法构建空间选址优化模型,优化了该镇的绿地空间布局。研究结果表明:包头市达茂旗百灵庙镇有39个小区绿地评价值低于规划标准,通过空间选址优化模型对研究区19个可行性地块进行搜寻,最终确定6个地块建设公园绿地,使得31个小区的绿地供给得到改善。研究提出的地理空间分析模型,可以为绿地资源选址与布局的相关决策提供参考,促进绿地空间资源均等化。

Based on the geospatial model,the improved two-step floating catchment area method was used to evaluate the supply and demand of urban green space in Bailingmiao Town,Darhan Muminggan Joint Banner,Baotou.On this basis,K-means clustering algorithm and particle swarm optimization algorithm were applied to build a spatial location optimization model,hence,the optimization of the green space layout of the town.The result shows that evaluations of the green spaces of 39 communities in Bailingmiao Town were lower than the planning standard.Therefore,through the spatial location optimization model,19 feasible plots in the study area were searched,and 6 sites were eventually identified for the construction of parks and green spaces.As a result,the ratio of green spaces of 31 residential areas has been improved.The geospatial analysis model proposed in this paper can provide a reference for relevant decisions on green space locations and layouts,and promote the equalization of green space.