R help - Apr 2013 - How to make a raster image in R from my own data set

Hi R-user,
I was trying to make a raster map with WGS84 projection in R, but I could not
make it. I found one data set in Google that data is almost the same format as
of mine. I wanted to make a raster map of temperature with 1 degree spatial
resolution for the global scale.
I could make it in GIS software but I do have many variables (to be many raster
images) and ultimately I am importing them to R for further analysis. Therefore,
I wanted to make them in R, if possible.

It would be great if you give some hints on how script look like  in creating a
raster map from my own data set (I have provided link for your references, this
is an example data set).

I am really appropriating for your help.

#--------------------------------------------------
#create a raster map from scratch

install.packages("raster", dependencies=TRUE)
library(raster)  # raster data
install.packages("rgdal", dependencies=TRUE)
library(rgdal)  # input/output, projections
install.packages("rgeos", dependencies=TRUE)
library(rgeos)  # geometry ops
install.packages("spdep", dependencies=TRUE)
library(spdep)  # spatial dependence
install.packages("pastecs", dependencies=TRUE)
library(pastecs)
pts<-read.table.url("https://www.betydb.org//miscanthusyield.csv",
header=T, sep=",")
proj4string(pts)=<- CRS("+proj=longlat +datum=WGS84")
#---------------------------------------------------------------------------

Cheers,
Kristi
 		 	   		  
	[[alternative HTML version deleted]]

Hi R-User



 		 	   		  
	[[alternative HTML version deleted]]

Hi Kristi,

it takes a few extra steps to create a raster layer from your example 
data set, as it is not a gridded map in Lat lon (probably in some 
projection though). How exactly to do it depends on your data, but here 
are some hints:

1. If you actually need to read the data set from a link, then 
read.table.url is depreceted, just use read.table. You might need to 
call setInternet2(TRUE) first, as the example data is on an https-url.
2. Raster can read a range of inputs, but I am not sure if .csv is one 
of them, and definitely not if the data is not gridded. You can then 
first do interpolation with a Spatial*-object. Set the coordinates of 
your object, this creates a Spatial*-object, and add the projection:
coordinates(pts) = ~lon+lat
proj4string(pts) = CRS("+proj=longlat +datum=WGS84")
3. You will have to create your reference grid (spsample, from raster, 
or another existing grid you have available), and interpolate to this 
grid, using one of the many interpolation packages, such as geoR, 
automap, gstat, intamap.
4. The resulting object can easily be converted to raster through 
raster(interpolationResult[,resultname])

I hope this can help you getting started.
Generally you get quicker response to spatial questions from the 
r-sig-geo list.

Jon



On 24-Apr-13 16:56, Kristi Glover wrote:
> Hi R-user,
> I was trying to make a raster map with WGS84 projection in R, but I could
not make it. I found one data set in Google that data is almost the same format
as of mine. I wanted to make a raster map of temperature with 1 degree spatial
resolution for the global scale.
> I could make it in GIS software but I do have many variables (to be many
raster images) and ultimately I am importing them to R for further analysis.
Therefore, I wanted to make them in R, if possible.
>
> It would be great if you give some hints on how script look like  in
creating a raster map from my own data set (I have provided link for your
references, this is an example data set).
>
> I am really appropriating for your help.
>
> #--------------------------------------------------
> #create a raster map from scratch
>
> install.packages("raster", dependencies=TRUE)
> library(raster)  # raster data
> install.packages("rgdal", dependencies=TRUE)
> library(rgdal)  # input/output, projections
> install.packages("rgeos", dependencies=TRUE)
> library(rgeos)  # geometry ops
> install.packages("spdep", dependencies=TRUE)
> library(spdep)  # spatial dependence
> install.packages("pastecs", dependencies=TRUE)
> library(pastecs)
>
pts<-read.table.url("https://www.betydb.org//miscanthusyield.csv",
header=T, sep=",")
> proj4string(pts)=<- CRS("+proj=longlat +datum=WGS84")
>
#---------------------------------------------------------------------------
>
> Cheers,
> Kristi
>   		 	   		
> 	[[alternative HTML version deleted]]
>
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-- 
Jon Olav Sk?ien
Joint Research Centre - European Commission
Institute for Environment and Sustainability (IES)
Land Resource Management Unit

Via Fermi 2749, TP 440,  I-21027 Ispra (VA), ITALY

jon.skoien at jrc.ec.europa.eu
Tel:  +39 0332 789206

Disclaimer: Views expressed in this email are those of the individual and do not
necessarily represent official views of the European Commission.