Application of nearest-neighbour regression for generalizing sample tree information

被引：30

作者：

Korhonen, KT ^{[1
]}

Kangas, A ^{[1
]}

机构：

[1] FINNISH FOREST RES INST,KANNUS RES STN,FIN-80101 JOENSUU,FINLAND

来源：

SCANDINAVIAN JOURNAL OF FOREST RESEARCH | 1997年 / 12卷 / 01期

关键词：

inventory; models; nearest-neighbour regression; non-parametric regression; volume;

D O I：

10.1080/02827589709355389

中图分类号：

S7 [林业];

学科分类号：

0829 ; 0907 ;

摘要：

Nearest-neighbour regression was tested for generalizing sample tree information in data from the national forest inventory of Finland. The following variables were found to be good regressors: stem diameter, mean diameter, density and age of growing stock, and plot location. The nearest-neighbour estimator appears to maintain the natural variation of the variables to be estimated well. Reliable volume and height estimates can be obtained even when using only one nearest neighbour. Increasing the number of neighbours improves the accuracy of estimates.

引用

页码：97 / 101

页数：5

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