摘要
选取福建将乐地区主要造林树种杉木为研究对象。在福建省将乐林场杉木人工林中,选取杉木36株,对衫木枝进行数据解析,运用SPSS20.0对杉木枝条基径数据进行分析,建立平均枝条基径预估模型。对枝条基径预估理论模型进行比较,选择改进的单分子Mitschelich模型为最优基础模型;对线性模型、理论模型、复合模型(改进的理论模型)的拟合效果做出了比较。结果表明:以枝条着枝深度、胸径、冠长为变量的复合模型为预估枝条基径最优模型,模型的估测精度达到了91.33%。
By selecting Cunninghamia lanceolata in the main afforestation tree species in Fujian Province, we analyzed the bran- ches diameter data by SPSS20.0, established the prediction models of average branch diameter with 36 trees in Jiangle State-owned Forest Farm, Sanming City, Fujian Province. Branches of the theoretical model of base diameter forecast model improved the single molecule Mitschelieh model as the optimal foundation model. We made a comparison of linear model, theoretical mode] and complex model （improved theoretical model）. The result shows that the complex model with the depth of the branches, the diameter at breast height and crown long is the optimal model to estimate the branch diameter, with the accuracy of the prediction model of 91.33%.
出处
《东北林业大学学报》
CAS
CSCD
北大核心
2014年第9期23-27,共5页
Journal of Northeast Forestry University
基金
中央高校基本科研业务费专项资金资助(BLJD200907)
关键词
杉木
枝条平均基径
枝解析
复合模型
Cunninghamia lanceolata
Average branch diameter
Branch analysis
Complex model
