文献类型：期刊文献

中文题名：区域尺度杉木生物量估计的不确定性度量

英文题名：Uncertainty Assessment in Regional-Scale Above Ground Biomass Estimation of Chinese Fir

作者：傅煜[1] 雷渊才[1] 曾伟生[2]

第一作者：傅煜

机构：[1]中国林业科学研究院资源信息研究所;[2]国家林业局调查规划设计院

年份：2014

卷号：50

期号：12

起止页码：79-86

中文期刊名：林业科学

外文期刊名：Scientia Silvae Sinicae

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金：国家自然科学基金项目(31170588);国家"863"重点项目(2012AA12A306)

语种：中文

中文关键词：杉木;生物量;抽样误差;模型估测误差;不确定性度量

外文关键词：Chinese fir; above ground biomass; sampling error; model error; uncertainty assessment

分类号：S757

摘要：基于系统抽样体系江西省固定样地连续观测数据,以杉木立木生物量为估测对象,采用异速生长模型建立杉木单木地上生物量和各组分生物量估测模型,结合抽样理论和泰勒级数原理,以均方根误差为不确定性度量指标,分别测算由抽样误差和模型估测误差引起的生物量估计不确定性。结果显示:2009年江西省杉木地上生物量为19.34 t·hm-2,不确定性为0.92 t·hm-2,树干、树皮、树枝和树叶生物量分别为11.87,1.95,3.15,2.62 t·hm-2,其中地上总生物量和各组分(树干、树皮、树枝和树叶)生物量估计中模型不确定性分别占估计量的2.48%,3.67%,3.43%,7.27%和6.33%。胸径对树枝、树叶的解释能力低于树干和树皮,抽样误差对生物量估计准确度的影响明显大于模型估测误差。研究方法适用于基于森林资源连续清查数据的生物量和碳储量估测。
In this article, a method combining Taylor series principle with sampling theory was developed for uncertainty assessment, including both model and sampling errors, and continuous observation data from the permanent sample plot of Jiangxi Province in China was used. Models of above ground tree biomass and different components （stem,bark, branch and foliage） biomass for Chinese fir were fitted with a commonly used allometric model form, and widely recognized root mean square error（RMSE）were applied as measure index for uncertainty assessment. The study revealed that the above ground tree biomass of Chinese fir amounts to 19.34 t· hm^-2 with additional uncertainty of 0.92 t· hm^-2, and different above ground biomass components（stem, bark, branch and foliage）were respectively 11.87, 1.95, 3.15, 2.62 t. hm-2 with model-dependent RMSE ratio estimators of mean above ground biomass of 3.67% , 3.43% , 7.27% and 6.33%. The sampling error makes a greater contribution to uncertainly in above ground biomass estimation than the modeling error, and uncertainties of branch and foliage biomass estimation were higher compared with those of stem and bark due to relative lower interpret ability from diameter at breast height to above ground biomass（AGB） of corresponding components. The proposed method was well suited for uncertainty assessments for above ground biomass and carbon stocks estimation in connection with sample based surveys such as NFI.