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Activity Number: 83
Type: Contributed
Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract #317547
Title: Robust and Automated Spatial Interpolation with Applications to Atmospheric Science Data
Author(s): Joon Jin Song* and Soohyun Kwon and GyuWon Lee
Companies: Baylor University and Kyungpook National University and Kyungpook National University
Keywords: Spatial Interpolation ; Robust Analysis ; Geostatistics
Abstract:

Kriging is a simple and popular geostatistical interpolation method. Unfortunately, the method has some shortcomings. Kriging is sensitive to outliers and presumes that the spatial structure of the underlying process is known. However, it is very common to have outliers and unknown spatial structure in atmospheric science data sets. In this study, we propose a robust and automated spatial interpolation method, which minimizes the effect of outliers on spatial prediction and the specification of spatial structure. The method is illustrated using a real-world data set.

Authors who are presenting talks have a * after their name.

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