Temporal analysis of spatial covariance of SO2 in Europe

被引：4
|
作者：
Giannitrapani, Marco
Bowman, Adrian
Scott, Marian
Smith, Ron
机构：
[1] Univ Glasgow, Dept Stat, Univ Gardens, Glasgow G12 8QQ, Lanark, Scotland
[2] CEH Edinburgh, Penicuik EH26 0QB, Midlothian, Scotland
来源：
ENVIRONMETRICS | 2007年 / 18卷 / 04期
关键词：
variogram; local linear regression; non-parametric smoothing; spatial modelling;
D O I：
10.1002/env.819
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
In recent years, the number of applications of spatial statistics has enormously increased in environmental and ecological sciences. A typical problem is the sampling of a pollution field, with the common objective of spatial interpolation. In this paper, we present a spatial analysis across time, focusing on sulphur dioxide (SO(2)) concentrations monitored from 1990 to 2001 at 125 sites across Europe. Four different methods of trend estimation have been used, and comparisons among them are shown. Spherical, Exponential and Gaussian variograms have been fitted to the residuals and compared. Time series analyses of the range, sill and nugget have been undertaken and a suggestion for defining a unique spatial correlation matrix for the overall time period of analysis is proposed. Copyright (c) 2006 John Wiley & Sons, Ltd.
引用
收藏
页码：409 / 420
页数：12
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