Sample surveying to estimate the mean of a heterogeneous surface: reducing the error variance through zoning
Sample surveying to estimate the mean of a heterogeneous surface: reducing the error variance through zoning
复制标题
抽样测量估计异质表面的平均值：通过分区减少误差方差
DOI：
10.1080/13658810902873512
复制
发表时间：
2010-01-01
影响因子：
5.7
通讯作者：
Cao, Zhidong
中科院分区：
文献类型：
--
作者：
Wang, Jinfeng;Haining, Robert;Cao, Zhidong
与地理信息系统中地理数据有关的不确定性的主要来源之一是在地理数据是抽样过程的结果时产生的。众所周知，当从空间自相关的均匀表面采样时，分层降低了总体均值估计的误差方差。在这项研究中，我们评估不同的空间采样策略时，表面是不均匀的效率。当表面是一阶异质（表面的平均值在地图上变化），我们研究分层成一阶均匀区之前，通常分层的系统或分层随机样本的影响。我们研究了这种形式的空间异质性对估计总体均值及其误差方差的不同方法的性能的影响。我们通过区分待调查的真实的表面（表面）、包括分区选择的采样框架（采样框架）和统计估计量（统计估计量）来做到这一点。研究表明，分区提高估计效率时，采样的非均匀表面。系统的比较提供了经验法则的选择样本设计，样本统计和不确定性估计，考虑不同的空间异质性的基础上，在真实的表面。
One of the major sources of uncertainty associated with geographical data in GIS arises when they are the outcome of a sampling process. It is well known that when sampling from a spatially autocorrelated homogeneous surface, stratification reduces the error variance of the estimator of the population mean. In this study, we evaluate the efficiency of different spatial sampling strategies when the surface is not homogeneous. When the surface is first-order heterogeneous (the mean of the surface varies across the map), we examine the effects of stratifying it into first-order homogeneous zones prior to the usual stratification for a systematic or stratified random sample. We investigate the effect of this form of spatial heterogeneity on the performance of different methods for estimating the population mean and its error variance. We do so by distinguishing between the real surface to be surveyed (ℜ), the sampling frame (ℑ) including the choice of zoning, and the statistical estimators (Ψ). The study shows that zoning improves estimator efficiency when sampling a heterogeneous surface. Systematic comparison provides rules of thumb for choice of sample design, sample statistics and uncertainty estimation, based on considering different spatial heterogeneities on real surfaces.