Dear Roger,
Regarding the shapefile question I think it was a memory problem because I had
88000 points and wen I reduced the number of points to half it worked fine.
Regarding the second question: thanks for the help and your solution almost
solves my problems, but I forgot to tell you that I am running this on Mac OS,
so rgdal doesn't run (at least that I know of). Because of this I am also
strugling to find the correct method to optmise the parameters to do the fiting
of the variogram (sill, range and nugget), that rgdal facilitates...
Can you recomend another package beside rgdal, or do you know of a version that
runs on Mac??
Best regards,
Carlos
Em 30/08/2007, às 23:16, Roger Bivand escreveu:
On Thu, 30 Aug 2007, Carlos Guerra wrote:
Dear useRs,
I am trying to convert the predictions of a kriging model into a
shapefile but I am getting some errors and I am getting nowere with
my solutions...
Without the error messages and the output of sessionInfo(), it isn't easy to
say.
This is the code I am running:
a <- data.frame(Id=seq(1,length(pred.grid[,1]),1),X=pred.grid[,
1],Y=pred.grid[,2])
a_dbf <- data.frame(Id=seq(1,length(pred.grid[,1]),1), data=kc2$predict)
shp_1 <- convert.to.shapefile(a, a_dbf, field="Id", type=1)
were pre.grid is determined by this code:
min_x <- 142794
max_x <- 152121
min_y <- 485080
max_y <- 508887
pred.grid <- expand.grid(seq(min_x, max_x, 50), seq(min_y, max_y, 50))
and kc2 is an object returned by the aplication of the function
krige.conv:
kc2 <- krige.conv(dados_g, loc=pred.grid, krige=krige.control
(obj.m=vario_fit2))
Although you are free to use the shapefiles package, your questions suggest
that you might be better served by using sp classes and either maptools or
rgdal to read and write your files. If you read the points data with readOGR()
or readShapePoints(), created a GridTopology for your grid, and used the
overlay() method from sp to cookie-cut the grid with a SpatialPolygonsDataFrame
object read by readShapePoly() or readOGR(), and then simply passed
coordinates() of the SpatialPixelsDataFrame object created after the overlaying
to the loc= argument, you would be very close. Use bbox() of the imported
SpatialPointsDataFrame object to find out what the grid should be. Consider
reading the vignette of the sp package - and finally just output the
SpatialPixelsDataFrame augmented with the prediction as a new column as a
GeoTiff file using writeGDAL() in rgdal, choosing only the predictions.
There are a number of steps to take, but it does work.
Hope this helps,
Roger
Another question:
as you can see I am predicting my values to a square set of points...
my question is how can I can I generate a set of point that match a
specific area (because I have a specific limite(area) in an esri's
shapefile).
Thanks in advance.
Carlos
Carlos GUERRA
Gabinete de Sistemas de Informacao Geografica
Escola Superior Agraria de Ponte de Lima
Mosteiro de Refoios do Lima
4990-706 Ponte de Lima
Tlm: +351 91 2407109
Tlf: +351 258 909779
Be a Mac user... update your self!
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--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: [EMAIL PROTECTED]
Carlos GUERRA
Gabinete de Sistemas de Informacao Geografica
Escola Superior Agraria de Ponte de Lima
Mosteiro de Refoios do Lima
4990-706 Ponte de Lima
Tlm: +351 91 2407109
Tlf: +351 258 909779
Be a Mac user... update your self!
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