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贵州人工杉木相容性立木材积和地上生物量方程的建立
引用本文:曾伟生,夏忠胜,朱松,罗洪章. 贵州人工杉木相容性立木材积和地上生物量方程的建立[J]. 北京林业大学学报, 2011, 33(4): 1-6
作者姓名:曾伟生  夏忠胜  朱松  罗洪章
作者单位:1 中国林业科学研究院资源信息研究所 2 贵州省森林资源管理站
基金项目:贵州省林业厅科研项目“贵州省人工杉木马尾松生物量通用模型研究”
摘    要:在国家级森林资源监测中增加森林生物量估计已成为必然趋势,而所需建立的生物量方程应该考虑与立木材积方程的相容性。本文以贵州省人工杉木立木材积和地上生物量数据为例,通过利用度量误差模型方法,研究建立了相容的立木材积方程、地上生物量方程及生物量转换函数。结果表明:在胸径基础上再增加树高因子,对立木材积方程的估计效果有明显改进...

关 键 词:立木材积  地上生物量  度量误差模型  平均预估误差  相容性  杉木
收稿时间:1900-01-01

Compatible tree volume and above-ground biomass equations for Chinese fir plantations in Guizhou
ZENG Wei-sheng,XIA Zhong-sheng,ZHU Song,LUO Hong-zhang. Compatible tree volume and above-ground biomass equations for Chinese fir plantations in Guizhou[J]. Journal of Beijing Forestry University, 2011, 33(4): 1-6
Authors:ZENG Wei-sheng  XIA Zhong-sheng  ZHU Song  LUO Hong-zhang
Affiliation:1 Institute of Forest Resources Information, Chinese Academy of Forestry, Beijing, 100091, P. R. China; 2 Forest Resources Administration Office of Guizhou Province, Guiyang, 550001, P. R. China.
Abstract:It has become a trend to supplement national forest resource monitoring with forest biomass estimation. Biomass equations to be developed should be compatible with volume equations. Based on the tree volume and above-ground biomass data of Chinese fir (Cunninghamia lanceolata) plantations of Guizhou Province in China, the compatible tree volume and above-ground biomass equations and biomass conversion functions were constructed using the error-in-variable modeling method. The results show that: 1) the regressions of volume equations improve significantly when tree height is used together with diameter at breast height (DBH), while the regressions of biomass equations improve slightly; 2) for biomass conversion function based on one variable, the conversion factor decreases with growing DBH; for conversion function based on two variables, the factor increases with rising DBH but decreases with growing tree height. Through the one variable-based compatible equations, the prediction precisions of tree volume and above-ground biomass estimates are more than 97% and 96% respectively; through the two variables-based equations, the prediction precision of tree volume estimates is more than 99%, but the precision of above-ground biomass estimates is only near 0.5 percentage higher than that through one-variable equation.
Keywords:tree volume  above-ground biomass  error-in-variable model  mean prediction error  compatibility  Chinese fir
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