地被植物引种气候指标相似性度量

为提高园林绿植地被植物引种成功率，在高维数据聚类中采用相似性度量算法分析地被植物引种气候指标间相似度。选取原产于我国新疆维吾尔自治区的皱叶剪秋罗作为地被植物引种品种，新疆哈密地区为引种源地，兰州、武汉、北京、广州等市为目标引种地。以 5 座城市 2015 年气候年值数据中的 8 项气候指标作为分析指标，采用高维数据聚类分析相似性度量算法计算引种地和引种源地间气候环境相似度，依据相似度大小次序，分析遴选出与哈密地区气候环境接近的目标引种地。实验结果表明，基于高维数据聚类分析的相似性度量算法在地被植物引种气候相似性分析中可较好体现引种源地与目标引种地气候相似度，实验结果与实际情况相符。相似性度量算法可为地被植物异地引种提供辅助决策分析，使园林绿植引种更科学。

The Similarity Measure of Climatic Indexes in the Introduction of Ground Cover Plants

In order to improve the success rate of introduction of ground cover plants in garden green plants，the similarity measure algorithm in high-dimensional data clustering is used to analyze the similarity between introduced climate indicators of ground cover plants. The Lychnis chalcedonica，which is native to the Xinjiang Uygur Autonomous Region of China，is selected as a ground cover plant. The Hami area in Xinjiang is the source of introduction，and the cities of Lanzhou，Wuhan，Beijing and Guangzhou are the target introduction sites. Eight climate indicators in the 2015 annual climate data of five cities are used as analytical indicators. The similarity measure algorithm of high-dimensional data clustering analysis is used to calculate the similarity between the climate of the introduced and introduced sources. According to the order of similarity，the target introduction sites close to the climate of Hami are analyzed. The experimental results show that the similarity measurement algorithm based on high-dimensional data clustering analysis can better reflect the climate similarity between the introduced source and the target introduction area. The actual situation is consistent.The similarity measure algorithm in this paper can provide auxiliary decision analysis for ground cover plants in different places to make the introduction of garden plants more scientific.