Moving window kriging with geographically weighted variograms


Harris, Paul and Charlton, Martin and Fotheringham, Stewart (2010) Moving window kriging with geographically weighted variograms. Stochastic Environmental Research and Risk Assessment, 24 (8). pp. 1193-1209. ISSN 1436-3240

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Abstract

This study adds to our ability to predict the unknown by empirically assessing the performance of a novel geostatistical-nonparametric hybrid technique to provide accurate predictions of the value of an attribute together with locally-relevant measures of prediction con- fidence, at point locations for a single realisation spatial process. The nonstationary variogram technique employed generalises a moving window kriging (MWK) model where classic variogram (CV) estimators are replaced with information-rich, geographically weighted variogram (GWV) estimators. The GWVs are constructed using ker- nel smoothing. The resultant and novel MWK–GWV model is compared with a standard MWK model (MWK– CV), a standard nonlinear model (Box–Cox kriging, BCK) and a standard linear model (simple kriging, SK), using four example datasets. Exploratory local analyses suggest that each dataset may benefit from a MWK application. This expectation was broadly confirmed once the models were applied. Model performance results indicate much promise in the MWK–GWV model. Situations where a MWK model is preferred to a BCK model and where a MWK–GWV model is preferred to a MWK–CV model are discussed with respect to model performance, parameteri- sation and complexity; and with respect to sample scale, information and heterogeneity.

Item Type: Article
Keywords: Geostatistics; Kriging; Nonstationary; Nonparametric; Variogram;
Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID: 5765
Identification Number: 10.1007/s00477-010-0391-2
Depositing User: Martin Charlton
Date Deposited: 03 Feb 2015 15:58
Journal or Publication Title: Stochastic Environmental Research and Risk Assessment
Publisher: Springer Verlag
Refereed: Yes
URI:

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