Hello,
The spatial support in R gives you many options, one I know is to use
contourLines() with an image() grid, and then converting that to a
SpatialLinesDataFrame with ContourLines2SLDF() in the maptools package.
The SLDF can then be written to shapefile with writeOGR() in rgdal
package. For example:
library(splancs)
library(rgdal)
library(maptools)
data(bodmin)
img <- kernel2d(as.points(bodmin), bodmin$poly, h0=2, nx=100, ny=100)
img.contours <- ContourLines2SLDF(contourLines(img))
writeOGR(img.contours, "contours.shp", "contours", "ESRI Shapefile")
# check the result
tst <- readOGR("contours.shp", "contours")
image(img)
plot(tst, add = TRUE)
HTH
Cheers, Mike.
Daniel Rainham wrote:
Hello,
I have collected GPS data on individuals (humans) at one second intervals for
approximately seven days. The file is read into R and the coordinates are
converted from decimal degrees to UTM. I then calculate two measures: 1.
Minimum convex polygon (using the ASPACE packge) 2. Kernel density estimate
(using SPLANCS, kernel2d function)
The first measure, MCP, can be output to a shapefile using makeshapes in the
ASPACE package for further analysis in a GIS package.
I would like to be able to do the same with the KDE, either as a raster (grid if
using ArcGIS), or would also be happy with polyline contours if possible in
.shp format. Why? Because I would like to extract information from other layers
in the GIS that correspond to the boundaries and intensities of the KDE
surface.
Is this currently possible from within R? If so, can anyone share with me the
process or code to achieve the conversion?
Thanks in advance for your help. I can send my full R code if required.
Daniel Rainham
Dalhousie University
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