

Thanks again for the fast reply,

 

In fact this problem is only a tiny part of the project and I'll need

to run this overlay operation over more than 600 polygons (watersheds)

to get mean values (and standard error) of ~10 environmental variables

(rasters that are not at the same resolution, i.e 2.5 degrees or 0.1

degrees). Furthermore I will have to overlay the watershed polygons

with polygons of landcover.

 

The scale of this project is regional (the whole Mediterranean basin)

thus the number (and size) of rasters preclude analyses to be run at

the entire scale of the project.

 

Thus I can imagine the following automated process :

 

1. calculate a buffer around the watershed polygon.

 

2. subset the grid area that overlay with the buffer (will it work

with big grid cells ?)

 

3. spsample the raster to a finer resolution (the number of new

samples will depend on the initial resolution of the raster), what

about using the bb argument of the spsample function ?

 

3. overlay this resampled raster with the watershed polygon.

 

4. get statistics (mean, sd, ...) from the resulting dataset.

 

As a newbie I would like to get some help (function names) for those

different steps (specifically 1 (buffer), 2 (grid subset)).

 

Thanks again for all your useful advices,

 

Laure.
 		 	   		  
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