Dear Colin:

Thank you again.

Given the nature of my project, I hope to do some data mining. I am on the
look out for spatially explicit forest and/or grassland vegetation data
along with environmental variable data. I am not sure of all the
databases/repositories regarding this sort of data. However, I will look
diligently to obtain this data.

Cheers,
Laura

On Tue, May 11, 2010 at 12:21 AM, Colin Beale <cb751@york.ac.uk> wrote:

> Dear Laura,
>
> > Given your comments below, I was was wondering what distribution and
> > autocorrelation model you think generally best represents naturally
> > occurring environmental variables.
>
> It depends on the underlying causes of the autocorrelation. If it's an
> intrinsic process like dispersal, something exponential is likely, or
> possibly something with a fatter tail - there's a large literature on
> dispersal kernels to explore. If it's some thing geological, geographers
> have concluded a Matern model is often the most appropriate. If it's some
> influence of man, this often has an extraordinarly steep structure (think
> clear-fell - sudden changes in the environment) that could be a step, or
> some extreme Matern. If it's topology, you're probably stuffed - hugely
> non-stationary patterns here: think long mountain chains with high
> variability, then large flat plains (we provided some code for simulating
> non-stationarity in the sup info (free) our Ecology Letters paper
> http://www3.interscience.wiley.com/journal/123241231/abstract, but you
> really need to think hard). Essentially, there's no substitue for thinking
> something about the ecology and real world that you want to simulate... (Why
> not start by measuring the actual structures and distributions of the
> covariates you want to simulate?)
>
> Colin
>
>
> Laura S wrote:
>
>> Dear Colin.
>>
>> Thank you very much. I greatly appreciate your time and comments.
>>
>> I am still interested in creating a landscape with environmental values
>> that follow a uniform frequency distribution, but I will keep the caveats of
>> strange autocorrelation in mind. I agree this representation of variables is
>> highly unrealistic.
>>
>>
>> Thank you again for your time and consideration,
>> Laura
>>
>>
>>
>> On Mon, May 10, 2010 at 11:16 PM, Colin Beale <cb751@york.ac.uk <mailto:
>> cb751@york.ac.uk>> wrote:
>>
>>    Hmmm, that's not a trivial problem. package geoRglm has functions to
>>    generate Poisson and Binomial surfaces. RandomFields is remarkably
>>    flexible. But there are good reasons why a uniform distribution is
>>    challenging to produce from a given spatial structure (think of
>>    'natural' autocorrelation as waves on the sea - there are only ever
>>    going to be a few high values and a few low values). So I don't know
>>    of any packages that do this 'off the shelf' - it really doesn't
>>    correspond to many real landscape covariates anyway, so are you sure
>>    you want to simulate such a landscape? If you are, I think I'd
>>    generate my uniform distribution using runif(), and then allocate
>>    values from this vector to some spatially autocorrelated structure
>>    generated with RandomFields using sort and order - something like:
>>
>>    library(RandomFields)
>>    #Generate a sorted vector of uniform distribution of required length:
>>    my.unifdist <- sort(runif(20*20))
>>    #Generate a landscape of autocorrelated values:
>>    my.landscape <- GaussRF (1:20,1:20,param = c(0,5,1,10),
>>                 method = "cutoff CE", model = "exponential", grid = T)
>>    #Place the sorted vector in the rank order of the landscape values:
>>    my.uniflandscape <- matrix(my.unifdist[rank(my.landscape)], ncol
>>                        = 20)
>>    #Have a look at the landscapes:
>>    par(mfrow = c(1,2))
>>    image(my.landscape, main = "Gaussian landscape")
>>    image(my.uniflandscape, main = "Uniform Landscape")
>>
>>    It's autocorrelated, and has a uniform distribution, but has a
>>    rather warped autocorrelation structure. Are you sure this is the
>>    sort of landscape you want to simulate?
>>
>>    Colin
>>
>>
>>
>>    Laura S wrote:
>>
>>        Dear all:
>>
>>        I would like to create a landscape of environmental values that
>>        follow a
>>        uniform frequency distribution and also have spatial
>>        autocorrelation in the
>>        landscape. I was wondering if there is an algorithm and/or
>>        package out there
>>        that creates autocorrelation of values that are distributed
>>        according to a
>>        non-normal frequency distribution.
>>
>>        Any suggestions are greatly appreciated.
>>
>>        Thank you,
>>        Laura
>>
>>
>>    --
>>    Dr Colin Beale
>>    Research Fellow
>>    University of York
>>
>>    Mob. +255 (0) 684 059 123
>>
>>
>>
>>
>> --
>> " Genius is the summed production of the many with the names of the few
>> attached for easy recall, unfairly so to other scientists"
>>
>> - E. O. Wilson (The Diversity of Life)
>>
>
> --
>
> Dr Colin Beale
> Research Fellow
> University of York
>
> Mob. +255 (0) 684 059 123
>



-- 
" Genius is the summed production of the many with the names of the few
attached for easy recall, unfairly so to other scientists"

- E. O. Wilson (The Diversity of Life)

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