Michael Sumner wrote:
Here's one way. I'm not sure about how to control the aspect ratio
(something I've been meaning to check for a while now).
somewhat of a non-newby answer to Michael: asp is set in plot.Spatial,
and if the default value of NA is passed, set to:
if (is.na(asp)) asp
Here's one way. I'm not sure about how to control the aspect ratio
(something I've been meaning to check for a while now).
library(sp)
data(volcano)
x <- 10*(1:nrow(volcano))
y <- 10*(1:ncol(volcano))
## image xyz list
imlist <- list(x = x, y = y, z = volcano)
## SpatialGridDataFrame (image2Grid
At the suggestion of Walmes Zeviani I downloaded and am taking a look at the sp
package.
In an attempt to get going, can someone offer a suggestion about how to convert
the below over to a version that uses the sp package?
data(volcano)
x <- 10*(1:nrow(volcano))
y <- 10*(1:ncol(volcano))
imag
Hi,
Check out the spatial task view [1] and the R wiki [2].
cheers,
Paul
[1] http://cran.r-project.org/web/views/Spatial.html
[2] http://wiki.r-project.org/rwiki/doku.php?id=tips:spatial-data
GRIGNOLA, FERNANDO E [AG/6042] wrote:
Hello,
I'm working on a project using weather data mostly on t
Hello,
I'm working on a project using weather data mostly on the statistical
aspects of it, i.e. environmental classification. I have a bunch of
shape files (*.dbf, *.prj, *.sbn, *.sbx, *.shp, *.shx) from different
world regions and I would like to start using R to do the mapping of
different clust
AIL PROTECTED]>
Subject: [R-sig-Geo] Newbie question: Reclassifying raster (ndvi)
using fisher method
To: [EMAIL PROTECTED], "r-sig-geo@stat.math.ethz.ch"
Message-ID:
<[EMAIL PROTECTED]>
Content-Type: text/plain
Hi all,
I am not sure as to which list
Hi all,
I am not sure as to which list this best fits (Grass or R-sig-geo).
I am trying to reclass a raster map (ndvi) into 5 different zones using the
fisher method, ultimatley i am trying to reclass as natural breaks.
The point of this exercise is for precision agriculture. I want to determine
Just an addition to the question I have asked before:
one easy way would be to fit:
- a global constant (to account for the average of the points of the
matrix);
- a plane to account for linear terms (in the example below, it should be a
plane with both negative partial derivatives with respect "
Hello,
I am new in this list. I have a problem and I think that the solution to
this problem can be found using spatial statistics, but I do not know how.
My problem is the following: I have a matrix of data, of around 6 rows and 5
columns. In reality, I have a time series, where at each point i
