A multivariate, nonparametric stem-curve prediction method

Author:

Lappi Juha

Abstract

The paper presents a general method for predicting the stem curve, volume, and merchantable height of a tree if breast height diameter (DBH) is measured, or if DBH and total height (H) as well as diameters at any heights are measured. Estimates for prediction variances are obtained both for diameters and volumes. The approach is multivariate and nonparametric. At the estimation stage, a multivariate model is developed for the total height and a fixed set of diameters: four diameters at absolute heights below breast height and eight diameters at relative distances between the breast height and the top of the tree. The expected values and variances of the dimensions and the correlations between dimensions are expressed as functions of DBH. These functions were estimated using smoothing splines. The model is applied by predicting unobserved dimensions from the observed dimensions using a linear predictor. If total height is not measured, then prediction is done using an approach based on two-point distributions. Correlation of total heights of different trees in the same stand is also modeled, and with this model, measured total heights in a stand can be used to predict unmeasured total heights. The approach provides both a detailed analysis of variation and covariation of stem curves and a practical prediction method.

Publisher

Canadian Science Publishing

Subject

Ecology,Forestry,Global and Planetary Change

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3