On Mon, 13 Jul 2009, Barry Rowlingson wrote:
On Mon, Jul 13, 2009 at 3:26 PM, Matt Oliver<moli...@udel.edu> wrote:
Dear r-sig-geo,
I am trying to generate a kml for an image I am producing using image().
After reading about kml generation, I'm unsure if I sould be using
kmlOverlay() or writeOGR, or some other function.
This is the data
http://www.ceoe.udel.edu/cms/moliver/20071003.276.0237.n17.nc
require(ncdf)
require(fields)
f <- open.ncdf("20071003.276.0237.n17.nc")
lon <- get.var.ncdf(f, "lon")
lat <- get.var.ncdf(f, "lat")
mcsst <- get.var.ncdf(f, "mcsst")
plot(diff(lon)) #####notice decreasing
par(mar=c(0, 0, 0, 0))
par(bty="n")
image(lon, lat, mcsst, col = tim.colors(64)) #####image I want to make kml
for
I don't seem to be able to make a proper "Spatial" object because of the
unequally spaced geographic coordinates.This seems to be necessary to to
proceed with a kml generation.
I'm probably missing something simple so any help or example code would be
wonderful
KML does this kind of image overlay by taking an image file (PNG,
jpeg etc) and it's bounding box in lat-long. It can't cope with
irregular grids.
My first thought as a workaround was to turn every pixel into a
rectangular polygon. But then I got the data and saw we were dealing
with 1445626 pixels and that google earth would probably crawl...
So I think you'll need to resample your data onto a regular lat-long
grid, then save it as an image, and then write the relevant KML with
the bounds. The KML is quite simple:
http://code.google.com/apis/kml/documentation/kml_tut.html#ground_overlays
but the resampling might not be. I think I've written some resampling
code somewhere, it just works out where in the old array a bunch of
regularly spaced points are that will make the new array are, and
samples. There may be R code for doing interpolation - maybe the
rimage or RImageJ packages...
But no, I don't think anything existing can do it [waits for Roger to
prove him wrong again...].
Maybe ... ?
Something like (not yet ideal, some stripey artefacts caused by the cell
steppings interfering with each other):
require(ncdf)
f <- open.ncdf("20071003.276.0237.n17.nc")
lon <- get.var.ncdf(f, "lon")
lat <- get.var.ncdf(f, "lat")
mcsst <- get.var.ncdf(f, "mcsst")
require(fields)
image(lon, lat, mcsst, col = tim.colors(64))
obj <- list(x=lon, y=lat, z=mcsst)
library(sp)
crds <- expand.grid(lon, lat)
SPDF <- SpatialPointsDataFrame(SpatialPoints(crds,
proj4string=CRS("+proj=longlat +datum=WGS84")),
data=data.frame(mcsst=c(mcsst)))
summary(SPDF)
bb <- bbox(SPDF)
grd <- GridTopology(bb[,1], c(diff(bb[1,])/1200, diff(bb[2,])/1200),
c(1200,1200))
SG <- SpatialGrid(grd, CRS("+proj=longlat +datum=WGS84"))
o <- overlay(SG, SPDF)
oo <- tapply(SPDF$mcsst, o, mean, na.rm=TRUE)
df <- data.frame(mcsst=rep(NA, 1200*1200))
df$mcsst[as.integer(names(oo))] <- oo
summary(df)
SGDF <- SpatialGridDataFrame(grd, CRS("+proj=longlat +datum=WGS84"),
data=df)
x11()
image(SGDF, col = tim.colors(64), axes=TRUE)
from there follow ?kmlOverlay, using the example as a template, with
image() instead of plot(). At least it's something.
Roger
Barry
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: roger.biv...@nhh.no
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
