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基于主成分分析与系统聚类的森林健康评价研究
罗鹏飞1, 江海斌1, 谭尹豪1, 龙时胜2
1.湖南天楚资源科技有限公司;2.中南林业科技大学
摘要:
森林健康的合理评价是指导森林管理者分类经营,精准提升森林健康活力的必要前提。以肇庆市森林资源二类调查的 25 130 个森林小班为基础,运用主成分分析对单位面积蓄积、林分郁闭度、天然更新状况等 12 个指标因子进行降维分析,构建评价森林健康的综合健康指数,并采用系统聚类方法划分各森林小班的健康等级,对肇庆市森林进行健康评价。结果表明,5 个主成分累积贡献率达到88.1%,可以充分反映原变量的信息;依据综合健康指数可将森林健康等级划分为健康 (0.29,1.35]、亚健康 (-0.45,0.29]、中健康 (-1.35,-0.45] 和不健康 [-2.01,-1.35] 共 4 类;肇庆市的森林健康状况为,天然林优于人工林,阔叶林优于针阔混交和针叶林。主成分分析和系统聚类方法的结合,能全面且准确地对森林健康进行评价,有助于提出相应的经营措施,精准地改善森林的健康状况。
关键词:  综合健康指数  森林健康  主成分  天然林
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基金项目:中南林业科技大学研究生创新基金项目(20181001)
Forest Health Evaluation Based on Principal Component Analysis and System Clustering
LUO Pengfei1, JIANG Haibin1, TAN Yinhao1, LONG Shisheng2
1.Hunan Tianchu Resources Technology Limited Company,Changsha;2.Central South University of Forestry and Technology,Changsha
Abstract:
Evaluating forest health is a necessary precursor to guide classified management and accurately improve the vitality of forest. Based on the 25130 forest samples in the new round of secondary survey of the forest resources in Zhaoqing, Dimensionality reduction of 12 index factors, such as unit area volume, stand canopy density and natural regeneration status was performed with principal components analysis (PCA). And a comprehensive health index was constructed to evaluate forest health. Then, health grades of each sample were classified using the systematic clustering method to evaluate the forest health of Zhaoqing city. The results showed that five principal components explaining 88.1% cumulative variance. The health grades were classified as four categories: health (0.29,1.35], sub-health (-0.45,0.29], mid-health (-1.35, -0.45] and unhealth [-2.01, -1.35]. The forest health of the natural forest was better than the artificial forest, the broad-leaved forest was better than the coniferous and broad-leaved mixed forest. The combination of PCA and systematic clustering can comprehensively and accurately evaluate the forest health, and help to put forward corresponding management measures to accurately improve forest health.
Key words:  Comprehensive health index  forest health  principal components  natural forest