[R-sig-Geo] Simulating or bootstrapping of Spatial Data

[Edzer Pebesma]

Sanjay,

library(gstat)
demo(ugsim)

gives a demo of a sequential Gaussian unconditional simulation, which
you seem to want. Several other simulation methods are found in package
RandomFields.

On 09/01/17 20:56, LAMSAL, SANJAY [AG/1005] wrote:
> I have a spatial data of soil bacteria concentration and have its semivariogram model. I wanted to simulate spatial scenarios of bacterial concentration in other fields. I could see this as either bootstrapping the bacteria data on spatial grids placed over other fields such that the generated data is spatially autocorrelated (honors the semivariogram model).
> 
> In my case, we want to develop spatial patterns of bacterium across several fields, where spatial pattern differ among fields but all patterns honor the same semivariogram model. Can anyone suggest an approach to accomplish this? I see this as being different from sequential simulation using gstat object (package gstat) where the simulated maps are realizations of original scenario.
> 
> Thanks
> 
> Sanjay
> 
> 
> 
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-- 
Edzer Pebesma
Institute for Geoinformatics  (ifgi),  University of Münster
Heisenbergstraße 2, 48149 Münster, Germany; +49 251 83 33081
Journal of Statistical Software:   http://www.jstatsoft.org/
Computers & Geosciences:   http://elsevier.com/locate/cageo/

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