What are the correct names? 01, 02 and so on? Or were you
expecting something else? We don't have your data so we have no idea
what the right answer is.
How did you create your shapefile? In R? You don't say.
Please show is the code you used, or a simple example that illustrates
the problem. It
Dear Roger Bivand and list members,
I am looking for advice on how to interpret a correlogram of species
richness data collected from photographic transects of the seabed. I am
an amateur in R, and am completely new to spatial analysis, so please
forgive the naivety of my issue.
I have four
Dear R group,
I have a question about calculating and plotting probability of a
classification using a raster image.
My data consist of three different classes, in my case three tree species with
specific reference spectra. Linear discriminant analysis was used for
classifying the spectra
Here is my problem in R:
readOGR(dsn=C:/Users/abc/desktop/shapfile,SD06)
OGR data source with driver: ESRI Shapefile
Source: C:/Users/abc/desktop/shapfile, layer: SD06
with 66 features and 36 fields
Feature type: wkbPolygon with 2 dimensions
#Is the above program running correctly? Or, is this
On Wed, Jan 30, 2013 at 2:42 PM, Milan Sharma milansharma2...@yahoo.com wrote:
#in my shape file, column names have come
#SD_csv_O, SD_CSV_D,instead of open water,
#or other names like that because of my problem in creating shape file.
Well, we don't know how you created the shapefile so we
I am new to Raster and posting in stackoverflow. When I attempt to plot
stacked rasters or use the predict function I get an error: failure during
raster IO. I have googled the error message but have not found any useful
suggestions as to what could be causing the error. All of my packages are
Hi,
I would like to do coloring of map regions based on the region values
weight. The approach I am taking is first to break regions into equal
intervals,
classIntervals(spdf$weight,4)$brks #4 intervals in this case
and than coloring all regions within the interval with the same color
col =
On Wed, 30 Jan 2013, Jan Hornych wrote:
Hi,
I would like to do coloring of map regions based on the region values
weight. The approach I am taking is first to break regions into equal
intervals,
classIntervals(spdf$weight,4)$brks #4 intervals in this case
and than coloring all regions within
Hi all, Roger Bivand - thank-you for your assistance.
I have attempted to write a for loop to create an object named maxdepth
(see str(maxdepth)), but the loop overwrites the previous iteration.
Although I have 54 files that I will be processing, I am attempting this
for loop with only the first
Hello,
Is there a formula to convert x-/y-coordinates (latitude /longitude) into UTM.
My data is in the form of latitude and longitude, but the code I wish to use
relies on x_m and y_m which I believe are UTM measurements (x in meters and y
in meters).
Thanks
Abby
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This should help you get started:
floodfiles - list.files(pattern=.txt)
maxdepths - list()
length(maxdepths) - length(floodfiles)
for(i in seq(along=floodfiles)) {
cat('---',i,floodfiles[i],'--\n')
maxdepths[[i]] - readAsciiGrid(floodfiles[i])}
Of course it overwrites. You are
Hi all,
I got a question about conversion from a spatialploygondatafrme object to a
geojson string with rgdal library.
Currently I am doing in this way (code attached as below), using writeOGR to
write the targetDataFrame to a temporary file, and then read the geojson string
from the file.
Irucka,
This
maxdepth.plys - lapply(modeldepthsmore,
Grid2Polygons(modeldepthsmore, level = FALSE))
Should probably be something like:
maxdepth.plys - lapply(modeldepthsmore, function(i) Grid2Polygons(i, level
= FALSE))
Robert
On Sun, Jan 27, 2013 at 2:47 AM, Irucka Embry
spTransform function in rgdal will do this, but UTM is a family of
projections so you need at least to know which zone is appropriate and
whether it is even any kind of sensible choice for projecting your
coordinates to. What is the range of the data and for what purpose do you
need them
Anne,
you do this: Rprob - predict(D, lda.0x, type=probabilities)
But ?predict.lda does not say that you can use an argument like
type=probabilities
To get the posterior probabilities you could probably do:
Rprob - predict(D, lda.0x, fun=function(x){predict(x)$posterior})
(based on what
On Wed, Jan 23, 2013 at 5:17 PM, Michael Sumner mdsum...@gmail.com wrote:
Better depends on what was required, which wasn't specified - all
the coordinates, or just 1-d arrays of the unique ones. Our answers
are totally different, Thiago I trust that you see the difference?
It would be good
This function, and other functions in the raster package, are independent
of the file type in which the values may be stored. RH
On Thu, Jan 24, 2013 at 1:31 PM, ping yang pingyang@gmail.com wrote:
Hi,
Is this zonal function works on NetCDF file?
Ping
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Prajjwal,
As Thiago shows you can do such things directly via the ncdf(4) package;
raster does not provide too many options beyond setting variable names
(arguments varname, varunit, longname, xname, yname, zname, zunit), see
?writeRaster. It would be nice to expand that and allow for more
Narayani, This works for me:
library(dismo) # for the example data
fnames - list.files(path=paste(system.file(package=dismo), '/ex',
sep=''), pattern='grd', full.names=TRUE )
BioStack - stack(fnames)
BioPt1 = na.omit(rasterToPoints(BioStack))
pcaPt1 = princomp(BioPt1[,-c(1:2)], cor = TRUE)
Rajagopal Vijayaraghavan [vijayaragha...@smart.mit.edu] wrote:
I want to test the validity of a non-parametric model to simulate a 3D point
pattern. [...]
I use the F3est, K3est, pcf3Est and G3est functions to generate the envelopes
from
this non-parametric model to then see if
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