Nonlinear locally weighted kriging prediction for spatio-temporal environmental processes

被引:3
作者
Bodnar, Olha [1 ]
Schmid, Wolfgang [1 ]
机构
[1] European Univ Viadrina, Dept Stat, D-15207 Frankfurt, Oder, Germany
关键词
nonlinear predictor; LOESS method; non-stationary spatio-temporal process; environmental statistics; Kalman filter; AIR-QUALITY INDEXES;
D O I
10.1002/env.1005
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the paper, a nonlinear interpolation procedure for the spatial prediction of an environmental process is proposed. The suggested interpolation is based on the locally weighted scatterplot smoothing method of Cleveland in 1979. This approach is applied to a nonlinear spatio-temporal model. In an empirical study, the PM 10 concentration in the Berlin Brandenburg region of Germany is considered. It is shown that the local approach permits a more structured interpolation of the air pollution. Copyright (C) 2009 John Wiley & Sons, Ltd.
引用
收藏
页码:365 / 381
页数:17
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