Classification accuracy for stratification with remotely sensed data

被引：0

作者：

Czaplewski, RL ^{[1
]}

Patterson, PL ^{[1
]}

机构：

[1] US Forest Serv, USDA, Rocky Mt Res Stn, Ft Collins, CO 80526 USA

来源：

FOREST SCIENCE | 2003年 / 49卷 / 03期

关键词：

forest inventory and monitoring; forest statistics;

D O I：

暂无

中图分类号：

S7 [林业];

学科分类号：

0829 ; 0907 ;

摘要：

Tools are developed that help specify the classification accuracy required from remotely sensed data. These tools are applied during the planning stage of a sample survey that will use poststratification, prestratification with proportional allocation, or double sampling for stratification. Accuracy standards are developed in terms of an "error matrix," which is familiar-to remote sensing specialists. In addition, guidance is provided to determine when new remotely sensed classifications are needed to maintain acceptable levels of statistical precision with stratification.

引用

页码：402 / 408

页数：7

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