On 06/13/2011 03:37 PM, Christopher Fusting wrote:
> Second, have a look at the CRAN 'spacetime' package for R. Although this
> will not solve your query, it may offer a different perspective.
Looking at packages is always good advice. There was also some discussion at
https://stat.ethz.ch/pip
On Mon, 13 Jun 2011, afischbach wrote:
For shape files the package maptools has worked for me.
require(rgdal)
require(maptools)
prj <- CRS("+proj=aeqd +lat_0=70 +lon_0=-170") #Azimuthal Equadistant -170,
70
fileName <- 'YourShapeFile.shp'
shape=readShapeLines(fileName, proj4string=prj, verbos
For shape files the package maptools has worked for me.
require(rgdal)
require(maptools)
prj <- CRS("+proj=aeqd +lat_0=70 +lon_0=-170") #Azimuthal Equadistant -170,
70
fileName <- 'YourShapeFile.shp'
shape=readShapeLines(fileName, proj4string=prj, verbose=FALSE, repair=FALSE,
delete_null_obj=FA
Hello,
Sorry for my beginner question.
I have created a Personal Geodatabase (Created in ArcCatalog - ArcGIS),
with shapefiles and raster maps of my project.
I would like to import these files in R, directly from this Geodatabase.
Is it possible? I used the odbcConnectAccess2007 command from the
Hey Alexandre,
This is an interesting problem. I have two ideas to offer. First, consider
layering your NDVI time series as bands and running a supervised
classification in GRASS. This will effectively turn time into spectral
bands, and will enable your classification tools to view it as such a
On 06/13/2011 10:48 AM, Malcolm Fairbrother wrote:
Dear Luca,
Are you looking for something like this?
N<- 300 # set the number of units
W<- matrix(rbinom(N^2, 1, 0.25), N, N)*upper.tri(matrix(1, N, N)) # build a
connectivity matrix, randomly
W<- W + t(W) # make the connectivity matrix symmetr
Dear Luca,
Are you looking for something like this?
N <- 300 # set the number of units
W <- matrix(rbinom(N^2, 1, 0.25), N, N)*upper.tri(matrix(1, N, N)) # build a
connectivity matrix, randomly
W <- W + t(W) # make the connectivity matrix symmetrical
W <- W/apply(W, 1, sum) # row-standardise the
