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红松人工林树皮因子预测模型
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  • 英文篇名:Prediction Model of Bark Factor in Pinus koraiensis Plantation
  • 作者:冯琳 ; 房家茹 ; 苏巴提 ; 丰绪霞
  • 英文作者:Feng Lin;Fang Jiaru;Su Bati;Feng Xuxia;Northeast Forestry University;
  • 关键词:红松 ; 树皮因子 ; 预测模型
  • 英文关键词:Pinus koraiensis;;bark factor;;prediction model
  • 中文刊名:林业科技情报
  • 英文刊名:Forestry Science and Technology Information
  • 机构:东北林业大学;
  • 出版日期:2019-05-15
  • 出版单位:林业科技情报
  • 年:2019
  • 期:02
  • 基金:东北林业大学大学生创新创业训练计划项目;; 林口林业局可持续经营试点项目
  • 语种:中文;
  • 页:8-10
  • 页数:3
  • CN:23-1287/S
  • ISSN:1009-3303
  • 分类号:S791.247
摘要
在森林调查中树皮因子是指树木的去皮直径与带皮直径的商。通过树皮因子可以利用带皮树干材积估算去皮材积,可以评估木材加工过程树皮残余量,可以预估树皮厚度,基于树皮厚度求算材种出材量等。树皮因子变化规律可以为实际生产提供理论支持,从而更好地进行木材生产和森林经营。研究树皮厚度和树皮系数的变化规律从而揭示树皮的变化规律,对提高林分蓄积生长量的精度有着重要的现实意义。
        In forest investigation,the bark factor refers to the quotient of the peeled diameter and the skin diameter of the tree. The bark factor can be used to estimate the volume of barked timber,the residual amount of bark,the thickness of bark,and the output of wood species. The change rule of bark factor can provide theoretical support for actual production,so as to better carry out timber production and forest management. Studying the bark thickness and bark coefficient to reveal the change rule of bark is of great practical significance for improving the accuracy of stand volume.
引文
[1]王君山,闫菁.树皮厚度和树皮系数变化规律的研究[J].河北林果研究,2011,26(3):235-237.
    [2]陆中二,马锁金,陈厚照.江苏成片林主要树种(组)树皮厚度的探讨[J].江苏林业科技,1991(1):21-22.
    [3]郭孝玉,孙玉军,马炜,等.适于FVS的长白落叶松树皮因子[J].东北林业大学学报,2011,39(10):28-31.
    [4]Stefan M.Stangle,Weiskittel A R,Dormann CF,etal.Measurement and prediction of bark thickness in Picea abies:assessment of accuracy,precision,and sample size requirements[J].Canadian Journal of Forest Research,2015,46(1).
    [5]Cellini J M,Galarza M,Burns S L,etal.Equations of bark thickness and volume profiles at different heights with easy-measurement variables.[J].Forest Systems,2012,21(1):págs.23-30.
    [6]Li R,Weiskittel A R.Estimating and predicting bark thickness for seven conifer species in the Acadian Region of North America using a mixed-effects modeling approach:comparison of model forms and subsampling strategies[J].European Journal of Forest Research,2011,130(2):219-233.

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