Hi Herry,
I am not entirely sure I understand your problem, but I suggest to do the
following:
1st alternative
1. load your shape files
2. set the bounding box of the polygon to match your grid scheme
3. use spsample() to sample the polygon in a regular fashion
4. assign to those points that
On Wed, 28 Jan 2009, Xingli Giam wrote:
Hi everyone,
I hope someone can point me to the right direction in printing the eigenvalues
of selected eigenvectors using ME() of spdep. I've communicated with Dr. Pedro
Peres-Neto and he has been really helpful in answering some of my questions
about
Dear Herry,
If I understand what you problem, one solution is to use R+SAGA. You should
first convert the
polygon map to the same grid, and then you can load it to R and do any type of
aggregation:
library(maptools)
library(rgdal)
library(RSAGA)
# load the gridded map:
rastermap -
Hi list,
I try to explain my problem a bit better.
1) Vector and raster have the same extent.
2) Vector data:
Several polygones with different attribute values
3) raster data:
A raster with points over the areas (and also NAs for areas where it is not
possible to have a value from polygones).
My appologies. The previous script had few (5) typos:
library(rgdal)
library(RSAGA)
# load the gridded map:
rastermap - readGDAL(rastermap.asc)
rsaga.esri.to.sgrd(in.grids= rastermap.asc, out.sgrds= rastermap.sgrd,
in.path=getwd())
# convert the polygon map to a raster map:
cellsize -
Hi Herry,
ok I think this should be pretty simple.
you should be able to do that with overlay(). Just use your raster and overlay
it with every polygon (in which the value is its ID) singly.
If you use a loop (for n in your.p...@plotorder) and
overlay(raster,
Hi Robert,
Thank you so much for your help. It works very nicely i wonder why the
extension was grd nowhere on the site from where i downloaded the data it
said it is a netCDF file
Monica
Date: Wed, 28 Jan 2009 09:58:23 +0800
Subject: Re: [R-sig-Geo] reading *.grd files
Alexander, below is a reproducible example that uses a polygon data set
from package maptools. You should read your polygons e.g. through
readOGR (package rgdal) and your grid through readGDAL.
If your grid comes from readGDAL, then 2 and 3 can be omitted, and 5
simplifies to:
out$SID79 =
Thanks Edzer,
That would do it. Unfortunately I can't read the (ESRI) grid, it is too large:
raster1 has GDAL driver AIG
and has 73772 rows and 80264 columns
Error in array(dim = as.integer(c(rev(output.dim), length(band :
'dim' specifies too large an array
I 'll have to cut into
Hi List,
I get an error using readGDAL{rgdal}: cannot allocate vector of size 3.1 Gb
I am using Linux 64bit (opensuse 11) with 4 gig swap and 4 gig Ram and R 2.8.0.
The load monitor shows that most of Ram is used up and then when Swap use
starts increasing, R returns the error.
Is there
Hi ALL,
I have done a number of interpolations using kriging and idw with gstat,
and use krige.cv to produce the cross-validation (nfold=5) as well.
How can I evaluate the results of cross-validation for individual
variables based on the me, mspe, rmse, Mean square normalized error, r
Well, this doesn't come as a surprise; if it did for you then you didn't
read the list archives well.
R has been designed for analysing statistical data, which usually
doesn't outnumber billions of observations, and not for
analysis/processing of large grids/imagery.
rgdal has
On Thu, 29 Jan 2009, alexander.h...@csiro.au wrote:
Hi List,
I get an error using readGDAL{rgdal}: cannot allocate vector of size 3.1
Gb
This is a tile of your 73K by 80K raster, right? One possibility is to use
smaller tiles, another to get more memory (as Edzer wrote), a third to use
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