Design-unbiased estimation for point-to-tree distance sampling
Design-unbiased estimation for point-to-tree distance sampling
复制标题
DOI：
10.1139/x06-038
复制
发表时间：
2006-06
影响因子：
2.2
通讯作者：
C. Kleinn;F. Vilčko
中科院分区：
文献类型：
--
作者：
C. Kleinn;F. Vilčko
点到树距离抽样设计，有时也称为k树抽样或固定计数抽样，是森林资源清查和生态调查中实地抽样的实用响应设计选项。虽然从业者接受并使用几种方法来估计干密度和其他林分属性，从统计的角度来看，一个主要的问题是缺乏一个一般的无偏估计这类抽样策略。本文在基于设计的概率抽样的框架下分析了点到树距离抽样，并提出了一个适用于任何林分属性估计的无偏估计量。该估计器借鉴了在每棵树周围定义包含区的想法。如果一棵树的样本点福尔斯落在它的包含区内，那么它就是一棵样本树。因此，包含区的大小是当用随机样本点进行采样时个体树的包含概率的度量。一旦所有人都知道了包含概率...
Point-to-tree distance sampling designs, sometimes also referred to as k-tree sampling or fixed-count sampling, are practical response design options for field sampling in forest inventories and ecological surveys. While practitioners accept and use several approaches to estimate stem density and other stand attributes, a major concern from a statistical point of view is the lack of a general unbiased estimator for this class of sampling strategies. In this paper we analyse point-to-tree distance sampling in the framework of design-based probabilistic sampling and present an unbiased estimator valid for estimation of any stand attribute. This estimator draws upon the idea of defining an inclusion zone around each tree. A tree is taken as a sample tree if a selected sample point falls into its inclusion zone. The size of the inclusion zone is therefore a measure of the individual tree's inclusion probability when sampling is done with random sample points. Once the inclusion probabilities are known for all...