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林业资源管理 ›› 2015, Vol. 0 ›› Issue (1): 38-43.doi: 10.13466/j.cnki.lyzygl.2015.01.007

• 科学研究 • 上一篇    下一篇

基于抽样固定样地的总体进界木株数模型研建

吴雨峰1, 葛宏立1, 邹奕巧2   

  1. 1.浙江农林大学 环境与资源学院,浙江省森林生态系统碳循环与固碳减排重点实验室,浙江 临安 311300;
    2.天台县林业特产局,浙江 台州 317200
  • 出版日期:2015-02-28 发布日期:2020-12-01
  • 通讯作者: 葛宏立,男,教授,主要研究领域为森林资源监测。
  • 作者简介:吴雨峰(1990- ),男,四川井研人,在读硕士,从事森林资源可持续技术与理论研究。Email:wyf4111@sina.com
  • 基金资助:
    “十二五”国家科技支撑计划团队任务“低效公益林更新改造和健康维持技术研究与示范”(2012BAD22B0503)

In-growth Tree Number Model in Population Level Based on Continuous Forest Inventory

WU Yufeng1, GE Hongli1, ZOU Yiqiao2   

  1. 1.Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration,School of Environmental & Resource Sciences,Zhejiang A & F University,Lin' an, Zhejiang 311300,China;
    2.Tiantai Forestry Bureau,Taizhou,Zhejiang 317200,China
  • Online:2015-02-28 Published:2020-12-01

摘要: 进界生长是森林资源动态变化的重要过程。在临安市1999年和2004年两期固定样地数据的基础上建立进界木株数模型,该模型实际由两个模型组成,分别是进界株数-样地前期活立木株数和进界株数-样地前期活立木平均胸径模型,然后用这两个模型各自建模时的相关指数作为权重,加权得到样地进界木株数模型。结果显示两个模型建模数据的相关指数分别为0.892 1和0.682 5,检验数据的相关指数为0.713和0.807 7。2004年临安市固定样地内进界木总株数模型估算的相对误差为0.69%,可以看出该模型在建模总体上应用具有较好的预测精度。

关键词: 进界生长, 进界木株数, 固定样地

Abstract: In-growth plays an important role in forest growth.This paper proposes a new in-growth tree number model using data of the years of 1999 and 2004 of Continuous Forest Inventory(CFI)in Lin' an county,Zhejiang province,China.The model actually consists of two partsone is based on the relationship between the number of in-growth trees occurred during the period and the number of trees at the former time,the other is based on the relationship between the number of in-growth trees and the mean DBH at the former period of time. Then,the two parts are combined with the weights which were calculated with their R2s.The result shows that R2s of the two parts are 0.892 1 and 0.682 5 for modeling data,and 0.713 and 0.8077 for test data.The relative error of estimated number of in-growth trees of total plots in this period is 0.69%.This may prove that this model is suitable for projection of number of in-growth trees in the population level with which the model was developed.

Key words: In-growth, number of in-growth trees, fixed sample plot

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