Automatic Mapping in the Presence of Substitutive Errors: a Robust Kriging Approach
Fournier, Baptiste
Furrer, Reinhard
10.4225/03/58007202615d5
https://bridges.monash.edu/articles/journal_contribution/Automatic_Mapping_in_the_Presence_of_Substitutive_Errors_a_Robust_Kriging_Approach/3979617
Interpolation of a spatially correlated random process is used in many scientific domains. The best unbiased linear predictor (BLUP), often called kriging predictor in geostatistical science, is sensitive to outliers. The literature contains a few attempts to robustify the kriging predictor, however none of them is completely satisfactory. In this article, we present a new robust linear predictor for a substitutive error model. First, we derive a BLUP, which is computationally very expensive even for moderate sample sizes. A forward search type algorithm is used to derive the predictor resulting in a linear likelihood-weighted mean procedure that is robust with respect to substitutive errors. Monte Carlo simulations support the theoretical results. The new predictor is applied to the two SIC2004 data sets and is evaluated with respect to automatic interpolation and monitoring.
2016-10-14 05:49:52
monash:89946
1959.1/736926
SIC 2004
Automatic mapping
Automatic interpolation
Anomolies
Outliers
Radioactive contamination
Environmental data
Robust kriging
Mapping algorithms
Substitutive error
2005
collection(s) Applied GIS
text
journal article
1832-5505
Geography
Economic Geography
Geomatic Engineering not elsewhere classified