基于因子分析法与k−means聚类的行道树安全风险评价

Safety Risk Assessment of Street Tree Based on Factor Analysis and k−means Clustering

  • 摘要: 以南京市法国梧桐行道树为例,通过分析行道树的生长状况、稳定性、健康状况、对交通的影响等各方面因素,建立涵盖8个评价指标的行道树安全风险评价指标体系,并基于因子分析法和k−means聚类对所有行道树进行安全风险评价。结果表明:南京市51.7%的法国梧桐行道树存在高、中风险,主要分布在秦淮区、玄武区和鼓楼区。其中莫愁路和三条巷为高风险路段,但中风险路段上的高风险法国梧桐行道树占高风险行道树总量的79.1%。因此,除了密切监测高风险路段外,还需要加强中风险路段的监测。本研究提出的行道树安全风险评价方法通过建立合理有效的行道树安全风险评价模型,能得到科学准确的行道树安全风险评价结果,反映行道树安全风险状况,为管理部门提供决策支持,且具有可迁移性,能推广应用到其他行道树安全风险评价研究。

     

    Abstract: Taking Platanus orientalis street trees in Nanjing as an example, the safety risk evaluation index system of street trees covering 8 evaluation indexes was established by analyzing the growth status, stability, health status, and influence on traffic of street trees, and the safety risk evaluation of all street trees was carried out based on factor analysis and k−means clustering. In Nanjing, 51.7% of the street trees with high or medium risk were located in Qinhuai, Xuanwu, and Gulou districts. Mochou Road and Three Lanes were high risk sections, and the number of high-risk street trees in middle risk sections accounted for 79.1% of the total number of high-risk street trees. Therefore, in addition to close monitoring of high-risk sections, it is also necessary to strengthen monitoring of medium-risk sections. The street tree safety risk evaluation method proposed in this study can obtain scientific and accurate street tree safety risk evaluation results by establishing a reasonable and effective street tree safety risk evaluation model, reflecting the street tree safety risk status, providing decision support for management departments, and is transferable and can be extended and applied to other street tree safety risk evaluation studies.

     

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