If you extract the information from your rasters into a dataframe (one
column per raster), can you use the predict.randomForest function in the
randomForest package?

If yes, you can then input your predictions back into a raster of the same
dimensions as the environmental variables.

I don't have any experience with random forest model, but that's what I do
with my Boosted Regression Tree predictions.

Nicole K.S. Barker
Ph.D Student / Étudiante au Doctorat
Laval University / Université Laval
Ducks Unlimited Canada / Canards Illimités Canada
LinkedIn: www.linkedin.com/in/nksbarker
Phone: 647-470-3207




On Tue, Mar 5, 2013 at 5:21 AM, Li Wen <li01.wen@gmail.com> wrote:

> Dear list member
>
>
>
> I have fitted a Random Forest model for species distribution, and want to
> use it to project the model to a defined landscape (i.e. forecasting for
> all
> grids in an area) . The landscape has all the environment covariates
> (rasters) and cover a large region (over 1000*1000 grids). I wonder if
> there
> is package in R to do this. Thank you for your help in advance.
>
>
>
> Cheers
>
> Li
>
>
>
>
>
>
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