%0 Journal Article
%A Larocque, G.
%A Dutilleul, P.
%A Pelletier, B.
%A Fyles, J.W.
%T Conditional Gaussian co-simulation of regionalized components of soil variation
%B Geoderma
%D 2006
%V 134
%P 1-16
%N 1-2
%Z 00167061 (ISSN) Export Date: 26 April 2007 Source: Scopus CODEN:
GEDMA doi: 10.1016/j.geoderma.2005.08.008 Language of Original Document:
English Correspondence Address: Larocque, G.; Department of Natural
Resource Sciences; McGill University; Macdonald Campus, 21, 111
Lakeshore Ste-Anne-de-Bellevue, Que. H9X 3V9, Canada; email: guillaume.larocque@mcgill.ca
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%X Stochastic simulations are increasingly used to represent and characterize
the spatial structure and uncertainty of soil properties. Due to
the potential presence of scale dependencies, simulations of the
total variables can represent a mixture of spatial components operating
at different scales, which may be better interpreted separately.
While coregionalization analysis and factorial kriging provide means
to characterize and estimate scale-specific components of variation,
no methods are available that allow a proper representation of their
spatial structure and an assessment of their spatial uncertainty.
In this paper, the formulation of cokriging of regionalized components
and regionalized factors is first reviewed, after which a method
for the conditional Gaussian co-simulation of regionalized components
and regionalized factors is presented. We highlight the need for
performing conditional simulations for all structures jointly to
reduce the correlation between components for different structures
and avoid any bias on the sum of simulated components. Simulations
obtained with this method adequately represent both the specific
features of, and the uncertainty associated with, each scale of
variation, as modeled in a coregionalization analysis. The method
is applied to an agronomic dataset to characterize the spatial uncertainty
of regionalized components of plant available phosphorous and potassium
in the soil and illustrate advantages of this new simulation approach.
© 2005 Elsevier B.V. All rights reserved.
%K Conditional stochastic simulations Coregionalization analysis Factorial
kriging Scale dependence Spatial uncertainty
%# brugerolles
%F LarocqueDutilleulPelletierEtAl2006
%3 BibTeX type = ARTICLE